Comparative Greenness Assessment in Pharmaceutical Analysis: Case Studies, Tools, and Best Practices

Abstract

This article provides a comprehensive examination of greenness assessment methodologies in pharmaceutical analysis, addressing the critical need for sustainable laboratory practices. It explores foundational principles of Green Analytical Chemistry (GAC) and introduces key metric tools including AGREE, AGREEprep, BAGI, and Analytical Eco-Scale. Through detailed case studies spanning antiviral, anticancer, and antibiotic drug analysis, we demonstrate practical applications across chromatographic and electrophoretic techniques. The content systematically addresses troubleshooting common implementation challenges, validates method performance through comparative studies, and establishes optimization frameworks that balance environmental responsibility with analytical efficacy. This resource equips researchers and drug development professionals with evidence-based strategies to advance sustainable analytical practices while maintaining rigorous quality standards.

Principles and Paradigms: Establishing the Framework for Green Analytical Chemistry

Green Analytical Chemistry (GAC) has emerged as a critical subdiscipline dedicated to minimizing the environmental footprint of analytical practices while maintaining high-quality analytical results. Originating in 2000 as an extension of green chemistry, GAC specifically addresses the unique challenges and opportunities within analytical chemistry [1]. This field motivates analytical chemists to address health, safety, and environmental issues throughout the analytical process, representing a fundamental shift in how analytical challenges are approached while striving for environmental benignity [1]. The core objectives focus on eliminating or reducing dangerous solvents, reagents, and materials while developing rapid, energy-saving methodologies that maintain robust validation parameters [1].

While the original 12 principles of green chemistry provided a foundational framework, they were primarily designed for synthetic chemistry and proved inadequate for fully addressing the specific needs of analytical chemistry [2]. This limitation prompted the development of a tailored set of 12 principles specifically for GAC, offering clear, concise guidelines to help analysts implement greener laboratory practices [2] [3]. These principles emphasize known concepts such as reduction in reagent and energy use, waste elimination, and risk minimization, alongside innovative ideas including the use of natural reagents [2]. To enhance practical adoption, the SIGNIFICANCE mnemonic was developed as a memory aid, encapsulating the essential concepts of green analytical practices into an easily recallable format [2].

The 12 Principles of GAC and the SIGNIFICANCE Mnemonic

The 12 principles of Green Analytical Chemistry provide a comprehensive framework for greening analytical methods. The SIGNIFICANCE mnemonic serves as a practical tool to help researchers remember and implement these core principles in their daily work [2]. The following table systematically presents each principle alongside its corresponding element in the mnemonic.

Table 1: The 12 Principles of Green Analytical Chemistry and the SIGNIFICANCE Mnemonic

Mnemonic Letter	Principle Concept	Detailed Explanation of Principle
S	Sample direct preparation	Direct analytical techniques should be applied to avoid sample treatment [2].
I	In-situ measurements	In-situ measurements should be performed whenever possible [2].
G	Green energy and reagents	Methods should use natural reagents or less dangerous chemicals [2].
N	No waste generation	Generation of large waste volumes should be avoided, and proper management implemented [2].
I	Integration of processes	Analytical processes and operations should be integrated to save energy and reduce reagents [2].
F	Fast method development	Methods should be fast to minimize energy consumption and increase throughput [2].
I	Instantaneous analysis	Automated and miniaturized methods should be selected for efficiency [2].
C	Clean, safe, and safe	The safety of the operator should be increased, and the risk of accidents minimized [2].
A	Avoid derivatization	Derivatization should be avoided due to its time, reagent, and waste generation [2].
N	No excess samples	Minimal sample size and minimal number of samples should be used [2].
C	Calibration with safe standards	The use of toxic reagents should be eliminated wherever possible [2].
E	Eco-friendly and biodegradable	Methods should be chosen that use biodegradable reagents [2].

The relationships between these principles and the key components they aim to address in analytical practice are visualized in the following diagram:

Diagram 1: GAC Principles and Key Goals Relationship Map. This diagram illustrates how the 12 principles of GAC collectively address the four key goals of greening analytical methods: reducing chemical use, minimizing energy consumption, improving waste management, and increasing operator safety.

Methodologies for Assessing Greenness in Analytical Chemistry

Evolution of Greenness Assessment Metrics

The progression of greenness assessment tools reflects the analytical community's growing commitment to sustainability. The field has evolved from basic binary indicators to sophisticated, multi-dimensional models that provide comprehensive environmental profiles of analytical methods [1]. Early tools like the National Environmental Methods Index (NEMI) offered simple pictograms indicating whether a method met four basic environmental criteria, but their binary nature limited the ability to distinguish degrees of greenness [1]. Subsequent metrics introduced more quantitative approaches, such as the Analytical Eco-Scale, which assigns penalty points for non-green attributes subtracted from a base score of 100 [1]. The development of the Green Analytical Procedure Index (GAPI) provided a more comprehensive, visually intuitive approach using a five-part, color-coded pictogram to assess the entire analytical process [1]. Recent advancements include tools like AGREE (Analytical Greenness), which provides both a circular pictogram and a numerical score based on the 12 principles of GAC, and newer frameworks such as AGSA (Analytical Green Star Analysis) that use star-shaped diagrams for multi-criteria evaluation [1]. The latest innovations also address specific aspects like sample preparation (AGREEprep) and climate impact (Carbon Footprint Reduction Index - CaFRI) [1].

Comprehensive Assessment Frameworks

Recent developments have produced increasingly sophisticated assessment frameworks. The Environmental, Performance, and Practicality Index (EPPI), introduced in 2025, represents a comprehensive dual-index system that evaluates not only environmental impact but also analytical performance and real-world practicality [4]. This framework includes the Environmental Impact (EI) Index, which integrates GAC and Green Sample Preparation (GSP) principles, and the Performance and Practicality Index (PPI), which assesses analytical performance and applicability [4]. Similarly, the Greenness Evaluation Metric for Analytical Methods (GEMAM), developed in 2025, offers a simplified yet comprehensive approach based on both the 12 principles of GAC and the 10 factors of sample preparation, presenting results on a 0-10 scale with a hexagonal pictogram [5]. These modern tools are designed to minimize subjectivity through predefined scoring criteria, enabling fair comparison between different analytical methods [4] [5].

Table 2: Comparison of Major Greenness Assessment Metrics

Metric Tool	Type of Output	Scope of Assessment	Scoring System	Key Advantages	Key Limitations
NEMI	Binary pictogram	Basic environmental criteria	Pass/Fail on 4 criteria	Simple, accessible	Lacks granularity, limited scope [1]
Analytical Eco-Scale	Numerical score	Non-green attributes	Penalty points from 100	Facilitates method comparison	Lacks visual component, subjective [1]
GAPI	Color-coded pictogram	Entire analytical process	Qualitative color coding	Comprehensive, visual	No overall score, somewhat subjective [1]
AGREE	Circular pictogram + score	12 GAC principles	0-1 numerical score	Comprehensive, user-friendly	Limited pre-analytical assessment [1]
AGREEprep	Pictogram + score	Sample preparation only	0-1 numerical score	Addresses critical high-impact stage	Must be used with broader tools [1]
AGSA	Star-shaped diagram	Multiple green criteria	Area calculation + score	Intuitive visual comparison	Newer, less established [1]
CaFRI	Numerical score	Carbon emissions	Reduction percentage	Focuses on climate impact	Narrow focus on carbon footprint [1]
GEMAM	Hexagonal pictogram + score	21 criteria across 6 dimensions	0-10 scale	Simple, flexible, comprehensive	Newer, requires validation [5]
EPPI	Numerical score + pie chart	Environmental, performance, practicality	1-100 scale	Holistic assessment across three domains	More complex calculation [4]

Comparative Case Study: Applying Multiple Metrics to a Microextraction Method

Experimental Protocol and Methodology

A recent case study demonstrates the practical application of multiple GAC assessment tools to evaluate the environmental profile of a Sugaring-Out-Induced Homogeneous Liquid-Liquid Microextraction (SULLME) method developed for determining antiviral compounds [1]. This method represents a modern approach that incorporates several green chemistry principles, particularly miniaturization. The experimental protocol involves using small sample volumes (1 mL) and employs a sugaring-out phenomenon to induce phase separation for analyte extraction [1]. The method is semiautomated, avoids derivatization steps, and utilizes some bio-based reagents, reflecting the application of several SIGNIFICANCE principles including miniaturization (letter I), avoidance of derivatization (letter A), and use of greener reagents (letter G) [1] [2]. The methodology was evaluated using four complementary assessment tools: Modified GAPI (MoGAPI), AGREE, AGSA, and the Carbon Footprint Reduction Index (CaFRI), providing a multidimensional perspective on its sustainability [1].

Essential Research Reagent Solutions

The following table details key reagents and materials commonly used in green analytical methods like microextraction techniques, along with their functions in promoting sustainable practices.

Table 3: Essential Research Reagent Solutions for Green Analytical Chemistry

Reagent/Material	Function in Green Analytical Methods	Green Chemistry Principle Addressed
Bio-based Reagents	Replace synthetic, hazardous chemicals with natural alternatives	Use of natural, renewable materials [2]
Water-based Solvents	Substitute organic solvents with aqueous systems	Safer solvents and auxiliaries [1]
Ionic Liquids	Serve as green solvent alternatives with low volatility	Reduced vapor pressure, increased safety [2]
Miniaturized Extraction Devices	Enable significant reduction in solvent consumption	Miniaturization, waste reduction [1] [2]
Renewable Sorbents	Provide biodegradable solid-phase extraction materials	Eco-friendly, biodegradable materials [2]

Comparative Results from Multiple Assessment Tools

The application of multiple metrics to the SULLME method provided a comprehensive yet nuanced evaluation of its greenness, with each tool highlighting different aspects of its environmental performance [1]. The methodology achieved a MoGAPI score of 60, indicating moderate greenness, with strengths in green solvent use and microextraction (limiting consumption to <10 mL per sample) but drawbacks in specific storage requirements, use of moderately toxic substances, vapor emissions, and waste generation exceeding 10 mL per sample without treatment strategies [1]. The AGREE evaluation yielded a score of 56, recognizing benefits from miniaturization, semiautomation, absence of derivatization, and small sample volume, while noting concerns about toxic and flammable solvents, low throughput (2 samples/hour), and moderate waste generation [1]. The AGSA tool assigned a score of 58.33, highlighting strengths in semi-miniaturization and avoided derivatization, but limitations in manual handling, pretreatment steps, lack of process integration, multiple hazard pictograms, mixed renewable/non-renewable reagent use, and absent waste management reporting [1]. Finally, the CaFRI assessment resulted in a score of 60, noting positive aspects in relatively low analytical energy consumption (0.1-1.5 kWh per sample) and no energy-intensive equipment, but identifying limitations in absent clean/renewable energy sources, lack of CO2 emissions tracking, long-distance transportation via non-eco-friendly vehicles, undefined waste disposal procedures, and organic solvent use exceeding 10 mL per sample [1].

The workflow for this comprehensive assessment and the interrelationships between the different evaluation metrics are visualized below:

Diagram 2: Multi-Metric Greenness Assessment Workflow. This diagram outlines the process of applying four different greenness assessment metrics (MoGAPI, AGREE, AGSA, and CaFRI) to a Sugaring-Out Liquid-Liquid Microextraction (SULLME) method, showing the specific strengths and weaknesses identified by each tool that contribute to an overall comprehensive assessment.

The evolution of greenness assessment metrics from simple binary tools to sophisticated, multi-dimensional frameworks demonstrates the analytical chemistry community's growing commitment to environmental responsibility [1]. The SIGNIFICANCE mnemonic provides an essential foundation by encapsulating the 12 core principles of GAC into an actionable framework that guides method development and optimization [2]. The case study examining the SULLME method using complementary metrics reveals a crucial insight: no single assessment tool can provide a complete picture of a method's environmental impact [1]. Each metric offers unique perspectives and highlights different aspects of sustainability, suggesting that comprehensive evaluation requires multiple complementary approaches [1]. As GAC continues to evolve, future developments will likely focus on standardizing assessment criteria, reducing subjectivity in evaluations, and incorporating emerging sustainability concerns such as carbon footprint and full lifecycle analysis [1] [4]. For researchers and drug development professionals, understanding and applying these principles and assessment tools is no longer optional but essential for developing analytical methods that are both scientifically robust and environmentally sustainable.

The relentless pursuit of sustainable practices in analytical laboratories has catalyzed a significant evolution in methodological philosophy. Green Analytical Chemistry (GAC) has served as a crucial foundation, primarily focusing on minimizing the environmental impact of analytical procedures by reducing hazardous waste, energy consumption, and the use of toxic reagents [6]. However, a key limitation became apparent: an exclusive focus on environmental goals could sometimes compromise a method's analytical performance or practical feasibility [6] [7]. This challenge has spurred the development of a more holistic framework known as White Analytical Chemistry (WAC).

Emerging as the next iteration of sustainable analytical chemistry, WAC is an integrated paradigm that strengthens traditional GAC by adding balanced criteria for assessing both the analytical performance and the practical usability of methods [8] [6]. The core innovation of WAC is its RGB model, which evaluates methods across three independent dimensions: Red for analytical performance, Green for environmental impact, and Blue for practical and economic aspects [8] [9]. The ultimate goal is to achieve "whiteness"—a balanced and optimal compromise where a method is environmentally sound, analytically reliable, and practically feasible [8]. This guide provides a comparative analysis of this emerging framework, underpinned by experimental data and case studies relevant to researchers and drug development professionals.

The RGB Model: Deconstructing the Principles of Whiteness

The RGB model functions as the operational backbone of White Analytical Chemistry, providing a structured framework for the comprehensive evaluation of analytical methods [8]. The "whiteness" of a method is determined by how harmoniously it blends these three primary attributes.

The Green (G) Component: Environmental Sustainability

The Green dimension incorporates the established principles of GAC [6]. It focuses on minimizing the negative environmental and safety impacts of an analytical procedure. Key criteria include:

• Prevention of waste generation.
• Minimization of reagent and solvent consumption, with a preference for safer, greener alternatives.
• Enhancement of energy efficiency.
• Ensuring operator safety [8] [6]. This dimension is the direct descendant of the 12 principles of Green Chemistry and GAC, ensuring that the method's ecological footprint is a primary consideration.

The Red (R) Component: Analytical Performance

The Red dimension addresses the core functionality of an analytical method—its ability to produce reliable, high-quality data. This pillar ensures that the pursuit of greenness does not undermine analytical validity. Key metrics include:

• Accuracy and precision of the results.
• Sensitivity, often defined by low limits of detection (LOD) and quantification (LOQ).
• Selectivity or specificity for the target analytes.
• A broad linear range and good reproducibility [8] [6]. A method with strong red attributes is fundamentally fit-for-purpose from a scientific and regulatory standpoint.

The Blue (B) Component: Practicality and Economic Feasibility

The Blue dimension introduces a crucial, often-overlooked aspect of method applicability in real-world settings, such as routine quality control laboratories. It assesses the practical and economic factors that determine whether a method will be widely adopted. Key considerations include:

• Cost-effectiveness of instrumentation and reagents.
• Analysis time and throughput.
• Simplicity of operation and the possibility for automation.
• Availability of the required equipment [8] [6]. A method scoring high in blue is not only sound in principle but also viable and efficient in daily practice.

Table 1: The Three Pillars of the White Analytical Chemistry (WAC) RGB Model

Color Dimension	Core Focus	Key Evaluation Criteria
Red (R)	Analytical Performance	Accuracy, precision, sensitivity (LOD/LOQ), selectivity, linearity, reproducibility
Green (G)	Environmental Sustainability	Waste generation, energy consumption, reagent toxicity, operator safety
Blue (B)	Practicality & Economic Feasibility	Cost, analysis time, throughput, simplicity, automation, equipment availability

Comparative Case Studies: WAC in Pharmaceutical Analysis

The theoretical superiority of the WAC framework is best demonstrated through its practical application. The following case studies from recent literature provide tangible evidence of how WAC guides the development and selection of more balanced and sustainable methods.

Case Study 1: Analysis of Anti-COVID-19 Antivirals via HPTLC

A 2025 study directly compared the "whiteness" of a normal-phase (NP) and a reversed-phase (RP) High-Performance Thin-Layer Chromatography (HPTLC) method for the concurrent quantification of three antiviral agents: Remdesivir, Favipiravir, and Molnupiravir [10].

Experimental Protocol: The NP method used a mobile phase of ethyl acetate:ethanol:water, while the greener RP method used only ethanol:water. Both methods were validated for linearity, accuracy, precision, and robustness per ICH guidelines. Their sustainability was evaluated using multiple metrics: AGREE and Analytical Eco-Scale for greenness, BAGI for blueness, and the RGB12 algorithm for overall whiteness [10].

Results and WAC Assessment: The quantitative results from the trichromatic assessment are summarized below.

Table 2: Comparative WAC Assessment of NP-HPTLC vs. RP-HPTLC for Antiviral Analysis [10]

Method	Greenness (AGREE Score)	Blueness (BAGI Score)	Whiteness (RGB12 Score)	Key Findings
Normal-Phase (NP) HPTLC	0.64	65	65	Good analytical performance and practicality, but lower greenness due to mobile phase composition.
Reversed-Phase (RP) HPTLC	0.80	70	75	Superior greenness and practicality, leading to a higher overall whiteness score.

The study concluded that the RP-HPTLC method, with its higher whiteness score, represents a more sustainable and balanced choice, successfully integrating the greenness of its ethanol-water mobile phase with excellent analytical performance and high practicality [10].

Case Study 2: Quantification of Gabapentin and Methylcobalamin via RP-HPLC

Another 2025 study developed an inventive RP-HPLC method for the simultaneous quantification of Gabapentin and Methylcobalamin in pharmaceutical products, with a deliberate focus on a green and white analytical approach [11].

Experimental Protocol: Separation was achieved on a C8 column using a green mobile phase of potassium phosphate buffer (pH 6.9) and a minimal amount of acetonitrile (5% v/v). The method was rigorously validated. Its sustainability was evaluated using a comprehensive suite of ten metrics, including AGREE (score = 0.70), Analytical Eco-Scale (score = 80), and BAGI [11].

Results and WAC Assessment: The method's exceptionally low organic solvent consumption (a 5% ACN mobile phase) drastically reduced its environmental impact compared to previous methods that used 30-50% ACN. This resulted in a high greenness score. Furthermore, the method offered a fast analysis time (10 minutes), high precision (RSD < 0.1%), and superior sensitivity, contributing to high red and blue scores. The authors highlighted that this dual green and white evaluation proved the method was not only eco-friendly but also functionally robust and practical for routine pharmaceutical quality control [11].

The Scientist's Toolkit: Essential Reagents and Metrics for WAC

Implementing the WAC framework requires familiarity with both practical laboratory tools and modern digital metrics for objective assessment.

Table 3: Essential Research Reagent Solutions and Assessment Tools for WAC

Tool / Reagent	Function / Purpose	Relevance to WAC Dimension
Ethanol	Green solvent for extraction and as a mobile phase component	Green (replaces more toxic solvents like methanol or acetonitrile)
Water	Primary solvent in reversed-phase chromatography	Green (non-toxic, safe, and inexpensive)
Magnetic Nanoparticles (e.g., PEI@SiO2@Fe3O4)	For Magnetic Solid-Phase Extraction (MSPE) to pre-concentrate analytes	Green & Blue (reduces solvent use, simplifies separation via magnet)
AGREE & AGREEprep Software	Calculates a greenness score (0-1) based on 12 GAC principles	Green
BAGI (Blue Applicability Grade Index) Software	Evaluates and scores the practicality and cost-effectiveness of a method	Blue
RGB12 / RGBfast Model	Integrates R, G, and B scores to compute an overall "whiteness" pictogram and score	White (Holistic Assessment)

Experimental Workflow and Signaling Pathways

The process of developing and validating an analytical method under the WAC framework follows a logical and iterative workflow, which integrates sustainability assessment at every stage. The diagram below visualizes this pathway toward achieving method "whiteness."

White Analytical Chemistry represents a significant and necessary evolution in the field of sustainable science. By moving beyond the singular, eco-centric focus of Green Analytical Chemistry, WAC offers a balanced, holistic, and pragmatic framework through its RGB model. It acknowledges that for a method to be truly sustainable and widely adopted, it must simultaneously excel in analytical performance (Red), environmental sustainability (Green), and practical feasibility (Blue).

As demonstrated by the cited case studies, this triad approach provides a more comprehensive and realistic metric for evaluating analytical procedures in pharmaceutical analysis and drug development. The ongoing development of user-friendly metric tools like AGREE, BAGI, and RGBfast is making this assessment increasingly accessible. For researchers and industry professionals, adopting the WAC paradigm is no longer a luxury but a critical step towards developing innovative, high-quality, and responsible analytical methods that meet the complex demands of modern science and regulatory environments.

The growing emphasis on sustainability in laboratory practices has propelled the development of Green Analytical Chemistry (GAC), which aims to minimize the environmental impact of chemical analyses [12]. Several metric tools have emerged to evaluate and quantify the greenness of analytical methods, each with distinct approaches, scoring systems, and applications [13] [14]. These tools help researchers identify areas for improvement, compare methods, and make more environmentally conscious choices in method development [12]. This guide provides a comprehensive comparison of four prominent metrics: AGREE, AGREEprep, BAGI, and Analytical Eco-Scale, focusing on their fundamental principles, applications, and comparative performance in assessing analytical procedures. The evolution of these tools reflects a broader shift toward White Analytical Chemistry (WAC), which seeks to balance environmental sustainability (green) with analytical performance (red) and practical/economic efficiency (blue) [15] [16] [17]. Understanding these tools' distinct characteristics enables researchers to select the most appropriate metric for their specific assessment needs.

AGREE (Analytical GREEnness Metric Approach)

AGREE is a comprehensive greenness assessment tool that evaluates analytical methods against all 12 principles of GAC [15]. It uses a user-friendly software calculator to generate an easy-to-interpret pictogram [15]. The output is a circular diagram divided into 12 sections, each corresponding to one GAC principle [14]. The tool provides a final score on a 0-1 scale, where higher scores indicate greener methods [14]. The color gradient in each segment (from red to green) and the overall score provide both qualitative and quantitative assessment capabilities [14].

AGREEprep (Analytical Greenness Metric for Sample Preparation)

AGREEprep is the first dedicated metric specifically designed to evaluate the environmental impact of the sample preparation step in analytical methods [12] [18]. It addresses the critical need for specialized assessment of this resource-intensive analytical stage [12]. The tool is based on 10 assessment criteria aligned with the principles of green sample preparation (GSP) [12]. These criteria include solvent choice, waste generation, energy consumption, sample size, throughput, and operator safety [12] [19]. AGREEprep employs an open-access software that generates a circular pictogram with 10 segments, each representing one GSP principle [12]. The software allows users to assign different weights to criteria based on their relative importance, enhancing assessment flexibility [12]. The final score ranges from 0-1, with higher scores indicating greener sample preparation procedures [12].

BAGI (Blue Applicability Grade Index)

BAGI represents a shift in focus from environmental impact to practical methodology [16]. Unlike the greenness-focused metrics, BAGI evaluates the practicality and economic efficiency of analytical methods, corresponding to the "blue" component of the White Analytical Chemistry concept [16] [19]. It assesses 10 key attributes including type of analysis, number of simultaneously determined analytes, sample throughput, instrumentation requirements, automation degree, and sample amount [16]. BAGI uses a simple scoring system with four discrete levels (2.5, 5.0, 7.5, and 10 points) for each attribute [16]. The results are visualized through an asteroid-shaped pictogram with color intensity indicating performance in each criterion, from white (poor) to dark blue (excellent) [16]. The final score ranges from 25-100, with higher scores indicating better practicality [16].

Analytical Eco-Scale

The Analytical Eco-Scale is a semi-quantitative assessment tool that employs a penalty points system [14]. It establishes an ideal green analysis as a baseline (score of 100 points) and subtracts penalty points for hazardous reagents, energy consumption, waste generation, and other environmental impacts [14]. The penalty points are assigned based on the amount and hazard level of each substance used, as well as energy consumption and waste produced [14]. A higher final score indicates a greener method, with scores above 75 considered excellent, 50-75 acceptable, and below 50 inadequate [14]. This approach provides a simple, intuitive assessment that considers both the type and quantity of substances used in the analytical procedure [14].

Comparative Analysis of Metric Tools

Table 1: Direct Comparison of Key Characteristics of the Four Metric Tools

Feature	AGREE	AGREEprep	BAGI	Analytical Eco-Scale
Primary Focus	Overall analytical method greenness [15]	Sample preparation greenness [12]	Method practicality & economic efficiency [16]	Overall environmental impact [14]
Assessment Basis	12 principles of GAC [15]	10 principles of GSP [12]	10 practicality attributes [16]	Penalty points system [14]
Scoring System	0-1 scale [14]	0-1 scale [12]	25-100 scale [16]	0-100 scale (100 = ideal) [14]
Visual Output	12-segment circle [14]	10-segment circle [12]	10-point asteroid [16]	Numerical score only [14]
Software Availability	Yes [15]	Yes [12]	Yes (desktop & web) [16]	No (manual calculation) [14]
Quantitative/Qualitative	Both [14]	Both [12]	Both [16]	Primarily quantitative [14]
Key Application	Comprehensive method greenness assessment [15]	Sample preparation step evaluation [12]	Practicality assessment for routine labs [16]	Quick environmental impact profiling [14]

Table 2: Assessment Criteria Comparison Across the Four Metric Tools

Assessment Category	AGREE	AGREEprep	BAGI	Analytical Eco-Scale
Reagents/Solvents	Yes [15]	Yes (emphasis) [12]	Yes (type & availability) [16]	Yes (penalty points) [14]
Energy Consumption	Yes [15]	Yes [12]	Indirectly	Yes (penalty points) [14]
Waste Generation	Yes [15]	Yes (emphasis) [12]	Indirectly	Yes (penalty points) [14]
Operator Safety	Yes [15]	Yes [12]	Indirectly	Yes [14]
Sample Throughput	Indirectly	Yes [12]	Yes (emphasis) [16]	No
Instrumentation	Indirectly	Indirectly	Yes (emphasis) [16]	No
Multi-analyte Capacity	No	No	Yes (emphasis) [16]	No
Automation Degree	Indirectly	Yes [12]	Yes (emphasis) [16]	No

Complementary Nature of Different Metrics

The four metrics demonstrate significant complementary relationships rather than direct competition [19]. AGREE and AGREEprep focus primarily on environmental aspects, with AGREEprep providing specialized assessment for the sample preparation step [12]. BAGI addresses the practical and economic aspects that are largely overlooked by greenness-focused metrics [16]. Analytical Eco-Scale offers a simpler, more rapid assessment suitable for initial screening [14]. For holistic method evaluation, researchers are increasingly using multiple metrics in combination [20] [19]. This integrated approach aligns with the White Analytical Chemistry concept, which emphasizes balancing environmental, practical, and analytical performance considerations [15] [17].

Case Study Applications and Experimental Data

Experimental Protocol for Comparative Metric Assessment

To illustrate the application of these metrics, we examine a published study that simultaneously determined glibenclamide, metoprolol tartrate, and phenol red using HPLC-PDA [20]. The method was applied in rat intestinal permeability studies using the Single Pass Intestinal Perfusion (SPIP) technique [20]. The analytical procedure involved:

• Sample Preparation: Biological samples were processed using a simplified protein precipitation approach [20].
• Chromatographic Conditions: Separation was achieved using a C18 column with a mobile phase consisting of phosphate buffer and acetonitrile in gradient elution mode [20].
• Detection: Photodiode array detection was employed with wavelength optimization for each compound [20].
• Method Validation: The procedure was validated according to ICH guidelines for specificity, linearity, accuracy, precision, and robustness [20].

Assessment Results and Interpretation

The method was evaluated using all four metric tools alongside additional metrics (GAPI, MoGAPI, RAPI) [20]:

Table 3: Case Study Assessment Results for the HPLC-PDA Method

Metric Tool	Score	Performance Interpretation
AGREE	0.75 [20]	Good greenness performance with room for improvement
AGREEprep	0.68 [20]	Moderately green sample preparation approach
BAGI	78 [20]	Good practicality for routine application
Analytical Eco-Scale	82 [20]	Excellent environmental performance

The case study demonstrates the value of multi-metric assessment. The method performed well in practical aspects (BAGI) and overall environmental impact (Analytical Eco-Scale), while the specialized AGREEprep metric identified specific opportunities for improvement in the sample preparation stage [20].

Essential Research Reagent Solutions

Table 4: Essential Reagents and Materials in Green Analytical Chemistry

Reagent/Material	Function in Analytical Chemistry	Green Considerations
Safer Solvents (e.g., ethanol, water, ethyl acetate)	Replacement for hazardous organic solvents in extraction and separation [12]	Reduced toxicity, biodegradability, renewable sourcing [12]
Solid-Phase Microextraction (SPME) Fibers	Solventless extraction and concentration of analytes [19]	Minimizes or eliminates solvent use, reusable materials [19]
Dispersive Solid-Phase Extraction (dSPE) Sorbents	Matrix clean-up and analyte purification [19]	Reduced solvent consumption compared to conventional SPE [19]
Renewable Sorbent Materials (e.g., biopolymers, natural materials)	Extraction and concentration of analytes [12]	Sustainable sourcing, biodegradability, reduced environmental persistence [12]
Miniaturized Extraction Devices	Small-scale analyte extraction and preconcentration [19]	Reduced reagent consumption, smaller sample volumes, less waste generation [19]

Assessment Workflow and Tool Selection Guide

Tool Selection Workflow

This workflow visualization illustrates the strategic approach to selecting and applying the most appropriate metric tools based on specific assessment objectives. For comprehensive method evaluation, researchers should employ multiple tools to gain complementary insights into environmental, practical, and sample preparation-specific aspects [19]. The iterative nature of the process enables continuous improvement through method optimization and reassessment [12].

AGREE, AGREEprep, BAGI, and Analytical Eco-Scale each offer unique strengths for evaluating different aspects of analytical methods. AGREE provides the most comprehensive greenness assessment against all 12 GAC principles, while AGREEprep offers specialized evaluation of the critical sample preparation step [12] [15]. BAGI complements these tools by addressing the practical and economic aspects essential for method implementation in routine laboratories [16]. Analytical Eco-Scale remains valuable for rapid initial screening of environmental impact [14]. The growing trend toward using multiple metrics in combination reflects the analytical community's recognition that sustainable method development requires balancing environmental, practical, and performance considerations [20] [19]. As Green Analytical Chemistry continues to evolve, these metric tools will play an increasingly important role in guiding researchers toward more sustainable laboratory practices without compromising analytical quality or practical utility.

The field of analytical chemistry is undergoing a profound transformation, driven by the global imperative for sustainability. Modern laboratories face increasing pressure to align their practices with environmental goals, moving beyond mere analytical performance to incorporate ecological impact as a core criterion for method selection and development. This shift is propelled by a complex framework of global regulatory initiatives and standardized compliance requirements that are redefining professional standards for researchers, scientists, and drug development professionals worldwide [21].

The traditional "take-make-dispose" model in analytical chemistry is increasingly recognized as unsustainable, creating what has been termed a "coordination failure" within the field [21]. This linear approach relies heavily on energy-intensive processes, non-renewable resources, and waste-generating practices that contradict the environmental stewardship mission of many scientific organizations [21]. In response, a paradigm shift toward circular analytical chemistry (CAC) and green analytical chemistry (GAC) principles is gaining momentum, facilitated by new metric tools that quantify environmental impact and regulatory frameworks that mandate sustainable practices [21] [22].

This article examines the key regulatory drivers and global initiatives shaping sustainable analytical practices, providing a comprehensive comparison of assessment methodologies and their practical applications in pharmaceutical and environmental analysis. By framing these developments within the broader context of comparative greenness assessment case studies research, we aim to equip scientific professionals with the knowledge needed to navigate this rapidly evolving landscape while maintaining analytical rigor and compliance.

Global Regulatory Framework

International Standards and Directives

The regulatory landscape for sustainable analytical practices is characterized by a multifaceted array of international standards, regional directives, and reporting requirements that collectively establish compliance obligations for laboratories and research facilities.

Table 1: Key International Regulations and Standards Influencing Sustainable Analytical Practices

Regulation/Standard	Jurisdiction	Key Requirements	Relevance to Analytical Chemistry
Corporate Sustainability Reporting Directive (CSRD) [23] [24]	European Union	Mandates detailed public disclosure of environmental and social impacts using the "double materiality" concept	Requires laboratories to report on green chemistry principles, solvent consumption, energy use, and waste management
ISO 14001:2025 Environmental Management [24]	International	Revised standard requiring stronger controls on energy consumption, greenhouse gas emissions, and waste reduction	Promotes systematic approach to minimizing environmental footprint of analytical operations through measurable improvements
ISO 9001:2025 [24]	International	Emphasizes integrating sustainability into quality objectives and aligning quality systems with environmental responsibility	Connects analytical method validation and quality control with sustainable practices
Taskforce on Nature-Related Financial Disclosures (TNFD) [25]	International	Framework for assessing and disclosing nature-related risks, including biodiversity impacts	Encourages assessment of analytical chemistry's impact on ecosystems through reagent sourcing and waste disposal
Global Biodiversity Framework [26] [25]	International	Commits governments to address biodiversity loss through conservation and sustainable use	Impacts laboratories through emphasis on nature-based solutions and biodiversity protection in operations

The EU's Corporate Sustainability Reporting Directive (CSRD) represents one of the most significant regulatory drivers, requiring companies to publicly disclose information about their sustainability performance according to the concept of "double materiality," which considers both financial materiality and impact on society or the environment [23]. For analytical laboratories, this means increased accountability for their environmental footprint, including solvent consumption, energy use, and waste generation [24].

Simultaneously, updated ISO management standards are integrating sustainability goals into core operational requirements. The 2025 revisions to ISO 14001 (Environmental Management) and ISO 9001 (Quality Management) emphasize measurable improvements in environmental performance rather than mere policy declarations, directly impacting how analytical methods are developed, validated, and implemented [24].

Regional Policy Variations

The global policy landscape for sustainability is increasingly fragmented, with different jurisdictions adopting varied approaches to environmental regulation. Following major elections in 2024, countries are implementing diverse strategies that affect how organizations approach their sustainability initiatives, including analytical practices [23].

In the United States, federal policy has shifted toward "energy dominance," with plans to dismantle regulations supporting climate change mitigation and environmental protection [23]. However, this federal retreat has been countered by strengthened state-level policies, particularly in California, where binding climate disclosure laws for large public and private companies maintain pressure on corporate environmental reporting [23] [25]. This patchwork regulatory environment creates compliance challenges for multinational organizations operating laboratories across different jurisdictions.

Meanwhile, the European Union continues to advance ambitious environmental regulations, with the CSRD now applying to more companies and requiring detailed reporting on environmental and social impacts [24]. Similar trends are emerging in Asia, with countries like India implementing updated environmental regulations and energy-efficiency norms that reflect national net-zero ambitions [24].

Greenness Assessment Methodologies

Principles of Green Analytical Chemistry

Green Analytical Chemistry (GAC) has emerged as a specialized discipline focused on minimizing the environmental impact of chemical analyses while maintaining analytical performance. The foundation of GAC rests on twelve core principles that address waste reduction, energy efficiency, and operator safety [27] [28]. These principles provide a framework for developing and evaluating analytical methods that align with sustainability goals.

A critical distinction in this field is the difference between sustainability and circularity. Sustainability is a normative concept tied to what people think is important, balancing three interconnected pillars: economic, social, and environmental – the "triple bottom line" [21]. Circularity, meanwhile, focuses primarily on minimizing waste and keeping materials in use for as long as possible, but doesn't necessarily consider all three dimensions of sustainability [21]. In analytical chemistry, circular practices represent a stepping stone toward broader sustainability goals, with innovation serving as the bridge between the two concepts [21].

The transition from traditional linear analytical methods to circular approaches faces two primary challenges: the lack of clear direction toward greener practices, and coordination failures between stakeholders including manufacturers, researchers, routine labs, and policymakers [21]. Overcoming these barriers requires collaboration across traditionally siloed segments of the analytical community.

Assessment Tools and Metrics

Multiple metric tools have been developed to evaluate the environmental impact of analytical methods, each with distinct approaches, scoring systems, and areas of emphasis. These tools enable objective comparison of method greenness and facilitate continuous improvement in sustainable analytical practices.

Table 2: Comparison of Major Greenness Assessment Tools for Analytical Methods

Assessment Tool	Scope	Assessment Criteria	Scoring System	Key Strengths	Key Limitations
AGREE (Analytical Greenness Metric) [27] [22]	Entire analytical procedure	12 principles of GAC	0-1 scale (1 = ideal); pictogram output	Comprehensive coverage of GAC principles; intuitive visual output	Does not specifically emphasize sample preparation
AGREEprep (Analytical Greenness Metric for Sample Preparation) [21] [27] [22]	Sample preparation	10 green sample preparation (GSP) principles	0-1 scale (1 = ideal); score >0.5 = green method	Focuses on often-overlooked sample preparation stage; user-modifiable weighting	Limited to sample preparation only
GAPI (Green Analytical Procedure Index) [22] [28]	Entire analytical procedure	Multiple stages from sampling to final determination	Pictogram with color-coded segments	Visualizes environmental impact across method lifecycle	Less quantitative than other tools
NEMI (National Environmental Methods Index) [27] [28]	Analytical method	Persistence, bioaccumulation, toxicity, corrosivity	Pictogram (pass/fail for 4 criteria)	Simple, quick assessment	Lacks granularity; binary scoring
AES (Analytical Eco-Scale) [27] [28]	Analytical procedure	Reagent quantity, energy consumption, waste	Penalty points subtracted from 100; higher score = greener	Simple calculation; single score output	Oversimplifies complex environmental impacts

The AGREE metric exemplifies the modern approach to greenness assessment, evaluating analytical procedures against all 12 principles of GAC and presenting results in an intuitive clock-like pictogram where the final score and color are shown in the center (ranging from green to red) [27]. This tool has gained popularity due to its comprehensive coverage and open-access availability.

For sample preparation – often the most environmentally impactful stage of analysis – the AGREEprep metric provides specialized evaluation based on 10 green sample preparation principles [21] [27]. A recent evaluation of 174 standard methods from CEN, ISO, and Pharmacopoeias using AGREEprep revealed concerning results, with 67% of methods scoring below 0.2 on the 0-1 scale, highlighting the urgent need to update official methods to incorporate greener techniques [21].

The emerging concept of White Analytical Chemistry (WAC) represents an extension of GAC, evaluating methodologies based on the triad of analytical and ecological quality, practicality, and economic feasibility [27] [28]. This holistic approach acknowledges that environmental benefits must be balanced against practical implementation requirements in regulated environments like pharmaceutical laboratories.

Comparative Case Studies

Pharmaceutical Analysis

The application of greenness assessment tools to pharmaceutical analysis reveals significant opportunities for improving the sustainability of standard methodologies while maintaining regulatory compliance and analytical performance.

Table 3: Greenness Assessment of Chromatographic Methods for UV Filter Analysis in Cosmetics

Method Number	Analytical Technique	Sample Preparation Method	AGREE Score	AGREEprep Score	Key Greenness Findings
1 [27]	LC-UV	Dissolution in solvent, filtration	0.41	0.32	High solvent consumption; poor waste management
2 [27]	LC-DAD	Ultrasonic-assisted dissolution	0.46	0.38	Moderate energy use; limited solvent recovery
3 [27]	GC-MS	Solvent extraction with derivatization	0.35	0.28	Derivatization increases hazard and waste
4 [27]	LC-MS/MS	Solid-phase extraction (SPE)	0.52	0.45	Better than conventional methods but moderate solvent use
5 [27]	LC-MS/MS	Pressurized liquid extraction (PLE)	0.48	0.41	Reduced solvent but high energy consumption
6 [27]	LC-MS/MS	Microextraction by packed sorbent (MEPS)	0.68	0.62	Miniaturization improves greenness significantly
7 [27]	GC-MS	Micro-MSPD	0.71	0.65	Low solvent consumption; high throughput
8 [27]	LC-UV	Dispersive solid-phase microextraction (DSPME)	0.74	0.69	Excellent greenness profile; minimal waste
9 [27]	LC-UV	Ultrasound-assisted dispersive liquid-liquid microextraction (US-VA-DLLME)	0.70	0.66	Energy-assisted microextraction balances parameters
10 [27]	LC-UV	Dynamic HF-LPME	0.76	0.72	Highest scores; exemplifies green sample preparation

A comprehensive assessment of ten chromatographic methods for determining UV filters in cosmetic samples demonstrates the significant environmental advantages of microextraction techniques over conventional approaches [27]. The study employed both AGREE and AGREEprep metrics to evaluate methods ranging from standard dissolution techniques to advanced microextraction approaches.

The results clearly showed that microextraction methods (Methods 6-10) consistently outperformed conventional sample preparation techniques, with Dynamic HF-LPME (Method 10) achieving the highest greenness scores (AGREE: 0.76; AGREEprep: 0.72) [27]. These methods demonstrated superior performance across multiple greenness parameters, including reduced solvent consumption, minimal waste generation, lower energy requirements, and enhanced operator safety.

In contrast, the European standard method (Method 1) and other conventional approaches scored poorly on greenness metrics, primarily due to high solvent consumption, inadequate waste management, and limited energy efficiency [27]. This performance gap highlights the critical need to update official pharmacopoeial methods to incorporate modern, environmentally sustainable techniques that have matured sufficiently for standardization.

Environmental Monitoring

The application of greenness assessment in environmental monitoring reveals similar trends, with microextraction and miniaturized techniques demonstrating significant environmental advantages over traditional approaches.

A comparative study of analytical methods for pollutant monitoring in water samples evaluated solid-phase extraction (SPE), liquid-liquid extraction (LLE), and solid-phase microextraction (SPME) using the AGREE metric [22]. The findings indicated that SPME achieved a greenness score approximately 40% higher than conventional SPE and nearly 60% higher than LLE, primarily due to dramatic reductions in organic solvent use (from hundreds of milliliters to virtually zero) and minimized waste generation [22].

These environmental benefits are further enhanced when green sample preparation techniques are coupled with sustainable solvent choices. For instance, methods employing ethanol-water mixtures or supercritical CO₂ as extraction solvents demonstrate significantly improved greenness profiles compared to those using traditional acetonitrile or methanol [22]. This alignment with GAC principles reinforces the importance of considering both methodological approach and chemical selection in developing sustainable analytical practices.

Implementation Strategies

Method Migration Framework

Transitioning from traditional analytical methods to sustainable alternatives requires a systematic approach that maintains data quality while improving environmental performance. The following workflow outlines a standardized process for method migration aligned with regulatory requirements and sustainability goals.

Sustainable Method Migration Workflow

This systematic approach ensures that method transitions maintain analytical validity while achieving sustainability improvements. The process begins with a comprehensive assessment of current methods against green chemistry principles, followed by identification of alternative techniques that offer improved environmental profiles without compromising analytical performance [21].

Laboratories should prioritize method modifications that address the most significant environmental impacts first, typically focusing on sample preparation (often the most resource-intensive stage) and solvent selection (major contributors to waste and hazard) [21] [27]. The implementation of greenness assessment tools early in method development provides quantitative metrics to guide decision-making and justify method changes to regulatory bodies.

Overcoming Implementation Barriers

The transition to sustainable analytical practices faces several significant barriers that must be addressed through strategic approaches:

• Regulatory Inertia: Official standard methods from CEN, ISO, and Pharmacopoeias often score poorly on greenness metrics, with 67% scoring below 0.2 on the AGREEprep scale [21]. Overcoming this requires active engagement with regulatory agencies to establish clear timelines for phasing out outdated methods and integrating green metrics into method validation and approval processes [21].

• Coordination Failures: The field of analytical chemistry suffers from limited cooperation between key stakeholders including industry, academia, and manufacturers [21]. Building effective university-industry partnerships can bridge the commercialization gap for innovative green methods, aligning academic research with market needs [21].

• Economic Considerations: Implementing sustainable practices may require initial investments in new equipment or training. However, these costs are frequently offset by long-term savings through reduced solvent consumption, waste disposal costs, and improved efficiency [21]. Organizations can further mitigate cost concerns by leveraging financial incentives for early adopters, such as tax benefits, grants, or reduced regulatory fees [21].

• Rebound Effects: Laboratories must guard against the "rebound effect" in green analytical chemistry, where efficiency gains lead to increased overall resource use through more frequent testing [21]. Mitigation strategies include optimizing testing protocols, using predictive analytics to identify necessary tests, and fostering a mindful laboratory culture where resource consumption is actively monitored [21].

Essential Research Reagents and Solutions

The implementation of sustainable analytical practices requires careful selection of reagents and materials that minimize environmental impact while maintaining analytical performance. The following table details key research reagent solutions aligned with green chemistry principles.

Table 4: Sustainable Research Reagent Solutions for Analytical Chemistry

Reagent Category	Sustainable Alternatives	Key Functions	Environmental Advantages
Extraction Solvents [21] [27]	Ethanol-water mixtures, supercritical CO₂, deep eutectic solvents (DES)	Sample preparation, compound extraction	Reduced toxicity, biodegradability, renewable sourcing
Sorbents [27]	Bio-based sorbents, molecularly imprinted polymers (MIPs)	Sample clean-up, compound isolation	Enhanced selectivity, reusability, reduced disposal impact
Derivatization Agents [27]	Water-compatible reagents, catalyst-based systems	Analyte modification for detection	Reduced toxicity, minimized waste generation
Mobile Phase Components [27]	Ethanol-water, acetone-water mixtures	Chromatographic separation	Reduced acetonitrile use, lower environmental persistence
Calibration Standards [21]	In-situ preparation methods, stable isotope-labeled analogs	Instrument calibration, quantification	Reduced packaging waste, minimized shipping impacts

The shift toward bio-based solvents represents a significant opportunity for improving the sustainability profile of analytical methods. Ethanol-water mixtures, particularly when sourced from renewable feedstocks, offer dramatically reduced environmental impact compared to traditional acetonitrile-based mobile phases while maintaining comparable chromatographic performance for many applications [27].

Similarly, advances in sorbent technology have enabled the development of highly selective extraction materials that minimize solvent requirements while improving analytical performance. Bio-based sorbents derived from agricultural waste streams exemplify the circular economy principles in analytical chemistry, transforming waste materials into valuable analytical tools while reducing environmental impact [27].

Emerging Trends

The field of sustainable analytical practices continues to evolve rapidly, driven by technological innovations, regulatory developments, and increasing stakeholder expectations. Several emerging trends are poised to shape the future landscape of green analytical chemistry:

• AI Integration: Artificial intelligence is emerging as a dual-purpose tool in analytical chemistry, offering opportunities to optimize resource use and enhance energy efficiency while posing potential environmental challenges through increased computational demands [23] [25]. AI applications in method development can identify greener analytical pathways and predict environmental impacts before experimental validation [25].

• Advanced Automation: Automated systems align perfectly with GSP principles by saving time, reducing reagent and solvent consumption, and minimizing waste generation [21]. Next-generation automation platforms incorporate sustainability parameters as core optimization criteria, moving beyond traditional focus on throughput and precision alone [21].

• Standardization Initiatives: Momentum is building for global harmonization in sustainability assessment methodologies, with leading standard-setters like the Global Reporting Initiative (GRI) and International Sustainability Standards Board (ISSB) focusing on interoperability and collaboration [23]. These initiatives will likely enhance the quality and comparability of sustainability information globally, including analytical method greenness [23].

• Circular Economy Integration: The transition from linear "take-make-dispose" models to circular analytical chemistry frameworks continues to gain traction, driven by both environmental imperatives and economic opportunities [21] [26]. This shift requires unprecedented collaboration across manufacturers, researchers, routine laboratories, and policymakers to establish closed-loop systems for analytical consumables [21].

The regulatory landscape for sustainable analytical practices is undergoing rapid transformation, driven by global sustainability initiatives, evolving compliance requirements, and stakeholder demands for environmentally responsible operations. The emergence of standardized assessment methodologies like AGREE and AGREEprep provides scientific professionals with objective tools to evaluate and improve the environmental performance of their analytical methods.

Comparative case studies consistently demonstrate that microextraction techniques and miniaturized approaches offer significantly improved greenness profiles compared to conventional methodologies, without compromising analytical performance. The implementation of these sustainable practices requires systematic method migration frameworks that address regulatory, technical, and economic considerations while avoiding potential rebound effects.

As the field continues to evolve, the integration of artificial intelligence, advanced automation, and circular economy principles will further enhance the sustainability of analytical practices. However, realizing these benefits requires coordinated action across the analytical community – including manufacturers, researchers, routine laboratories, and policymakers – to break down traditional silos and build collaborative bridges [21].

For researchers, scientists, and drug development professionals, the message is clear: sustainable analytical practices are no longer optional enhancements but essential components of modern, responsible laboratory operations. By embracing the principles of green analytical chemistry, implementing objective assessment methodologies, and staying abreast of evolving regulatory requirements, the scientific community can significantly reduce its environmental footprint while maintaining the analytical rigor required for groundbreaking research and development.

The paradigm of analytical chemistry is shifting to incorporate environmental responsibility as a core pillar, leading to the emergence of Green Analytical Chemistry (GAC). This discipline aims to minimize the environmental footprint of analytical methods by reducing or eliminating hazardous solvents, reagents, and materials, while also promoting energy-saving and rapid methodologies [1]. The assessment of a method's "greenness" has evolved from a peripheral concern to a fundamental aspect of method development and validation, particularly within the context of drug development where solvent use and operator safety are critical [1]. This guide provides a comparative framework for researchers to objectively evaluate the environmental and safety performance of analytical techniques, focusing on the quantification of waste, energy consumption, and operator hazards.

The evaluation of analytical procedures has matured into a structured model, often visualized as a triad of components. Within this model, the "green component" focuses squarely on environmental sustainability, while the "blue" assesses methodological practicality, and the "red" evaluates analytical performance [1]. This guide focuses on the tools and metrics developed to quantify the green component, enabling scientists to make informed, data-driven decisions that align with both research objectives and sustainability goals.

A variety of metrics have been developed to assess the environmental impact of analytical methods. The table below summarizes the key tools, their assessment focus, and scoring mechanism.

Table 1: Key Greenness Assessment Tools for Analytical Methods

Tool Name	Primary Assessment Focus	Scoring/Output Mechanism	Key Strengths	Key Limitations
NEMI (National Environmental Methods Index) [1]	Basic environmental criteria (toxicity, waste, safety)	Binary pictogram (pass/fail per criterion)	Simple, user-friendly	Lacks granularity; cannot distinguish degrees of greenness
Analytical Eco-Scale [1]	Non-green attributes (hazardous reagents, energy demand)	Penalty points subtracted from a base score of 100	Facilitates direct numerical comparison between methods	Relies on expert judgment; lacks visual component
GAPI (Green Analytical Procedure Index) [1]	Entire analytical process (sample collection to detection)	Five-part, color-coded pictogram	Visually identifies high-impact stages within a method	No overall score; some subjectivity in color assignment
AGREE (Analytical GREEnness Metric) [1]	12 principles of Green Analytical Chemistry	Pictogram and a numerical score from 0 to 1	Comprehensive coverage; user-friendly; facilitates comparison	Does not fully account for pre-analytical processes
AGREEprep [1]	Sample preparation stage exclusively	Visual and quantitative outputs	Addresses a often high-impact part of the workflow	Must be used with other tools for a full method evaluation
MoGAPI (Modified GAPI) [1]	Entire analytical process	Pictogram with a cumulative scoring system	Improves comparability over GAPI	Retains some complexity of the original GAPI pictogram
AGSA (Analytical Green Star Analysis) [1]	Multiple green criteria (toxicity, waste, energy)	Star-shaped diagram with an integrated score	Intuitive visualization; combines multiple factors	Newer tool with less established track record
CaFRI (Carbon Footprint Reduction Index) [1]	Carbon emissions associated with analytical procedures	Index score	Aligns with climate-focused sustainability goals	Narrow focus on carbon footprint

Experimental Protocols for Greenness Assessment

Implementing a robust greenness assessment requires a structured methodology. The following workflow outlines the standard protocol for evaluating an analytical method using a suite of complementary tools.

Phase 1: Data Collection and Documentation

The first phase involves meticulously documenting every aspect of the analytical method. This includes:

• Reagents and Solvents: Precise types and volumes used per sample, noting their safety data sheet (SDS) information, particularly hazard classifications.
• Energy Consumption: The power rating (kWh) of all equipment used (e.g., HPLC, ICP-OES, ovens) and the duration of their operation per sample.
• Waste Generation: The total volume and mass of waste generated per sample, categorized by type (e.g., organic solvent, aqueous, solid) and its associated hazard.
• Operator Safety: Documented exposure risks, required personal protective equipment (PPE), and the presence of any procedural hazards like vapor generation [1].

Phase 2: Application of Assessment Tools

In this phase, the collected data is input into the selected metrics.

• Holistic Evaluation: Tools like AGREE and MoGAPI are applied first to gain an overview of the method's environmental performance across its entire lifecycle. AGREE provides a unified score and pictogram based on the 12 principles of GAC, while MoGAPI offers a detailed breakdown of each procedural step [1].
• Specialized Evaluation: Depending on the method, specialized tools are then used. AGREEprep is critical if the sample preparation is complex and solvent-intensive. The Carbon Footprint Reduction Index (CaFRI) is used to quantify the climate impact, considering energy sources and transportation of materials [1].

Phase 3: Synthesis and Interpretation

The final phase involves synthesizing the outputs from the various tools. The numerical scores (from AGREE, Analytical Eco-Scale) and visual outputs (from GAPI, AGSA) are compared to identify consistent strengths and weaknesses. For instance, a method might score well on waste generation but poorly on reagent toxicity, pointing to a clear avenue for optimization [1].

Case Study: Greenness Assessment of a Microextraction Method

To illustrate a practical application, a published sugaring-out-induced homogeneous liquid–liquid microextraction (SULLME) method for determining antiviral compounds was assessed using multiple metrics [1]. The quantitative results from this multi-tool assessment are summarized below.

Table 2: Multi-Tool Greenness Assessment of a SULLME Method [1]

Assessment Tool	Score	Key Strengths	Key Weaknesses
MoGAPI	60 / 100	Use of green solvents; microextraction (<10 mL/sample); no further sample treatment.	Specific storage conditions; moderately toxic substances; vapor emissions; >10 mL waste/sample.
AGREE	56 / 100	Miniaturization; semiautomation; no derivatization; small sample volume (1 mL).	Use of toxic/flammable solvents; low throughput (2 samples/hour); moderate waste generation.
AGSA	58.33 / 100	Semi-miniaturization; avoidance of derivatization.	Manual handling; ≥6 hazard pictograms; no waste management reported.
CaFRI	60 / 100	Low analytical energy (0.1–1.5 kWh/sample).	No renewable energy; no CO2 tracking; long-distance transport; >10 mL organic solvents/sample.

Interpretation of Case Study Results

The case study demonstrates the power of a multi-metric assessment. While the method's miniaturization and avoidance of derivatization are consistent strengths, the converging scores from different tools highlight recurring issues: inefficient waste management, the use of hazardous reagents, and a lack of climate-conscious practices [1]. This multidimensional view prevents a one-sided interpretation and provides a clear, evidence-based roadmap for making the method more sustainable, such by seeking safer solvent substitutes and implementing waste treatment.

The Scientist's Toolkit: Essential Reagents and Solutions

The move toward greener analytical methods relies on both new assessment tools and the adoption of safer, more sustainable materials. The following table details key reagents and solutions pivotal for advancing green chemistry in drug development.

Table 3: Research Reagent Solutions for Green Analytical Chemistry

Item / Solution	Function / Application	Greenness & Safety Considerations
Green Solvents (e.g., Cyrene, Ethyl Lactate) [29]	Replacement for hazardous solvents like DMF, NMP, and chlorinated solvents in extraction and chromatography.	Biobased, renewable feedstocks; lower toxicity; reduced environmental persistence and bioaccumulation.
Inductively Coupled Plasma Optical Emission Spectroscopy (ICP-OES) [30]	Multi-element quantification for environmental monitoring of trace metals (Cd, Pb, Hg, As).	High precision reduces need for repeat analysis; methods can be assessed for greenness using GAPI, AGREE, etc.
Solvent Selection Guides (SSGs) [29]	Framework for scoring solvents based on Environmental, Health, Safety, and Waste (EHSW) criteria.	Enables data-driven solvent choice; guides substitution of hazardous with greener alternatives.
Machine Learning Models for Solvent Assessment [29]	Predict sustainability metrics for thousands of solvents, expanding beyond limited experimental SSG data.	Accelerates discovery of novel green solvents; balances sustainability with performance and cost.

The systematic quantification of waste, energy consumption, and operator safety is no longer optional but a fundamental component of modern analytical science, particularly in regulated fields like drug development. As demonstrated, a suite of complementary assessment tools—including AGREE, MoGAPI, AGSA, and CaFRI—provides a robust, multidimensional framework for evaluating and comparing the environmental impact of analytical methods. The case study confirms that no single metric gives a complete picture; a synthesized assessment is essential for identifying true sustainability and areas for improvement. The ongoing development of tools that incorporate life-cycle thinking and machine learning, combined with the creation of greener reagent solutions, empowers researchers to make informed choices that uphold both scientific integrity and environmental responsibility.

Practical Implementations: Greenness Assessment Tools in Action Across Pharmaceutical Analyses

The growing demand for sustainable analytical chemistry has driven the development of comprehensive metrics to evaluate the environmental impact of pharmaceutical analysis methods. Within the context of antiviral drug development and quality control, green assessment tools provide standardized frameworks for quantifying ecological footprints and promoting the adoption of environmentally conscious practices. This case study focuses on the comparative application of two significant greenness assessment tools—AGREE (Analytical Greenness Metric) and BAGI (Blue Applicability Grade Index)—to the analysis of three prominent COVID-19 antiviral agents: ritonavir, favipiravir, and molnupiravir.

The AGREE metric employs a comprehensive 0-1 scoring system based on the 12 principles of green analytical chemistry, evaluating factors such as energy consumption, waste generation, and toxicity of reagents. Meanwhile, the BAGI tool assesses practical methodological aspects including throughput, cost, and operational complexity, providing a balanced perspective on both environmental and practical applicability. Together, these tools offer researchers a multidimensional view of method sustainability, enabling informed decisions that balance ecological concerns with analytical needs in pharmaceutical quality control and research settings [31] [32].

Analytical Methods for Antiviral Drugs

Chromatographic Methods

Reversed-phase high-performance liquid chromatography (RP-HPLC) represents one of the most widely employed techniques for simultaneous analysis of antiviral medications. A recently developed method for the simultaneous determination of five COVID-19 antiviral drugs—including favipiravir, molnupiravir, nirmatrelvir, and ritonavir—utilizes a Hypersil BDS C18 column (4.5 × 150 mm, 5 μm) with an isocratic mobile phase consisting of water and methanol (30:70 v/v, pH 3.0) at a flow rate of 1 mL/min. This method demonstrates excellent separation with retention times of 1.23 min for favipiravir, 1.79 min for molnupiravir, 2.47 min for nirmatrelvir, and 4.34 min for ritonavir, achieving complete analysis within 6 minutes [31].

Another innovative approach applies micellar liquid chromatography (MLC) for favipiravir determination using a solvent-free mobile phase consisting of 0.02 M Brij-35, 0.15 M SDS, and 0.02 M disodium hydrogen phosphate (pH 5.0). This method completely eliminates organic solvents, traditionally the most environmentally problematic aspect of HPLC, while maintaining excellent analytical performance with a retention time of 3.8 minutes for favipiravir. The green advantages of this method include using biodegradable surfactants, aqueous mobile phases, and mobile phase recycling between injections, significantly reducing waste generation [33].

Spectrophotometric Methods

Mathematical spectrophotometric methods provide powerful alternatives for analyzing antiviral drug mixtures with overlapping spectra without requiring physical separation. Recent research has developed six selective spectrophotometric methods for the determination of COVID-19 antivirals, including ratio derivative, ratio difference, mean centering of ratio spectra, area under the curve, Q-analysis, and bivariate calibration. These methods successfully resolve the significant spectral overlap between drugs like remdesivir and moxifloxacin, demonstrating excellent linearity over concentration ranges of 1–15 μg/mL [34].

For the analysis of favipiravir and remdesivir in spiked human plasma, ratio-manipulating spectrophotometric methods have been employed, including the ratio difference and first derivative of ratio spectra techniques. These methods effectively address spectral overlap challenges while offering the advantages of simplified procedures, reduced solvent consumption, and minimal waste generation compared to chromatographic approaches. The methods were validated according to ICH guidelines and successfully applied to pharmaceutical formulations and biological samples [35].

Spectrofluorimetric Methods

Green spectrofluorimetric methods represent another sustainable approach for antiviral drug analysis. A recently developed method for favipiravir determination employs Britton-Robinson buffer (pH 4) to enhance the native fluorescence of the drug, with measurement at 436 nm after excitation at 323 nm. This approach demonstrates exceptional sensitivity with a linear range of 20–350 ng/mL, making it suitable for low-concentration determination while using predominantly aqueous, environmentally benign solutions [33].

Table 1: Comparison of Analytical Methods for Antiviral Drugs

Method Type	Key Features	Analysis Time	Environmental Advantages
RP-HPLC	Simultaneous determination of 5 antivirals, good resolution	6 min	Reduced solvent consumption compared to conventional HPLC
Micellar LC	Solvent-free mobile phase, biodegradable surfactants	3.8 min	Elimination of organic solvents, mobile phase recycling
Spectrophotometric	No separation needed, mathematical resolution of spectra	<5 min	Minimal reagent consumption, no organic solvents
Spectrofluorimetric	High sensitivity, aqueous-based solutions	<5 min	Very low reagent volume, non-toxic chemicals

Greenness Assessment Using AGREE and BAGI

AGREE Evaluation

The AGREE metric provides a comprehensive assessment of method greenness based on twelve principles of green analytical chemistry, generating a score between 0-1, where higher scores indicate superior environmental performance. The AGREE assessment of the reported RP-HPLC method for simultaneous determination of five antiviral drugs yielded a favorable score of 0.70, indicating good environmental performance. This score reflects strategic solvent selection (aqueous methanol mobile phase), minimal sample preparation requirements, and reasonable energy consumption patterns [31].

Notably, the micellar liquid chromatography method for favipiravir analysis achieved an even higher AGREE score, attributable to its complete elimination of organic solvents through the use of biodegradable surfactants (Brij-35 and SDS) in the mobile phase. Additionally, the practice of mobile phase recycling between chromatographic runs further enhanced the greenness profile by significantly reducing waste generation. The spectrofluorimetric method also demonstrated excellent performance in AGREE assessment due to its minimal reagent consumption and use of predominantly aqueous, non-toxic solutions [33].

BAGI Evaluation

The BAGI tool complements AGREE by focusing on practical methodological aspects, including throughput, cost-effectiveness, operational simplicity, and reliability. The RP-HPLC method for simultaneous antiviral analysis achieved a BAGI score of 82.5, indicating excellent practical applicability for routine pharmaceutical quality control analysis. This high score reflects the method's advantages in terms of cost-effectiveness, accessibility in standard analytical laboratories, and ability to analyze multiple analytes in a single run [31].

Similarly, a GC-MS method for pharmaceutical analysis reported in the literature also received a BAGI score of 82.5, further validating the strong practical performance of chromatographic methods that balance greenness with analytical efficiency. The spectrophotometric and spectrofluorimetric methods generally achieved good BAGI scores due to their operational simplicity, rapid analysis times, and minimal equipment requirements, though with some limitations in specificity for complex samples compared to chromatographic approaches [32].

Table 2: AGREE and BAGI Scores for Different Analytical Methods

Method Type	AGREE Score	BAGI Score	Key Strengths	Limitations
RP-HPLC	0.70	82.5	Multi-analyte capability, good sensitivity	Moderate organic solvent use
Micellar LC	>0.70 (inferred)	Not specified	Solvent-free, biodegradable reagents	Limited application range
Spectrophotometric	0.70-0.85 (similar methods)	High (inferred)	Rapid, minimal reagents	Spectral interference possible
Spectrofluorimetric	>0.80 (inferred)	High (inferred)	Very sensitive, minimal waste	Requires native fluorescence

Comparative Greenness Assessment

Direct comparison of the greenness profiles reveals that each analytical approach offers distinct environmental advantages. The micellar LC method demonstrates superiority in solvent elimination but may have limitations in application scope. The RP-HPLC method strikes a balance between comprehensive analyte coverage and reduced environmental impact through optimized mobile phase composition. The spectroscopic methods excel in minimal reagent consumption and energy efficiency but may face challenges with complex sample matrices.

When evaluating the three target antivirals, the analytical methods show comparable greenness profiles across different drug molecules, suggesting that the environmental impact is more dependent on the analytical technique itself rather than the specific antiviral being analyzed. This observation is significant for method development strategies, indicating that green analytical principles can be universally applied across this drug class [31] [33].

Experimental Protocols

RP-HPLC Method for Simultaneous Determination

The RP-HPLC method for simultaneous analysis of favipiravir, molnupiravir, nirmatrelvir, and ritonavir employs the following protocol. Stock standard solutions (1000 μg/mL) are prepared by accurately weighing 100 mg of each reference standard into separate 100 mL volumetric flasks, dissolving in approximately 70 mL of methanol, sonicating for 10 minutes, and diluting to volume with methanol. Working standard solutions (100 μg/mL) are prepared daily by diluting stock solutions with methanol [31].

Chromatographic separation is achieved using a Hypersil BDS C18 column (150 mm × 4.6 mm; 5 μm particle size) maintained at 25 ± 2°C. The isocratic mobile phase consists of water and methanol in the ratio of 30:70% v/v, with pH adjusted to 3.0 using 0.1% ortho-phosphoric acid. The mobile phase is filtered through a 0.45 μm membrane filter and degassed ultrasonically before use. The flow rate is maintained at 1.0 mL/min, with UV detection at 230 nm and injection volume of 20 μL. The total run time is 6 minutes, with retention times of 1.23 min (favipiravir), 1.79 min (molnupiravir), 2.47 min (nirmatrelvir), and 4.34 min (ritonavir) [31].

Green Spectrofluorimetric Method

The spectrofluorimetric method for favipiravir analysis utilizes entirely aqueous solutions. A stock solution of favipiravir (20.0 μg/mL) is prepared in Britton-Robinson buffer (pH 4). Aliquots of the standard solution (10-175 μL) are transferred to 10 mL volumetric flasks and diluted to volume with Britton-Robinson buffer (pH 4) to obtain final concentrations of 20-350 ng/mL. The relative fluorescence intensity is measured at 436 nm using an excitation wavelength of 323 nm [33].

Method validation demonstrates excellent linearity with correlation coefficients >0.999, precision (RSD <1.1%), and accuracy (99.59-100.08%). The method is successfully applied to pharmaceutical dosage forms and spiked human plasma samples, with recovery values ranging from 99.98 to 100.7% and no significant interference from excipients. The greenness of the method is evaluated using AGREE and GAPI metrics, confirming its excellent environmental profile [33].

Analytical Method and Green Assessment Workflow. The diagram illustrates the comprehensive workflow from sample preparation through greenness assessment, highlighting the integrated approach to sustainable method development.

The Scientist's Toolkit: Essential Research Reagents

Table 3: Essential Research Reagents for Antiviral Drug Analysis

Reagent/Equipment	Function in Analysis	Greenness Considerations
Hypersil BDS C18 Column	Chromatographic separation of antiviral compounds	Long column lifetime reduces waste
Methanol (HPLC grade)	Mobile phase component	Preferred over acetonitrile for lower toxicity
Brij-35 surfactant	Mobile phase component in micellar LC	Biodegradable, replaces organic solvents
SDS surfactant	Mobile phase component in micellar LC	Biodegradable, enables solvent-free analysis
Britton-Robinson buffer	pH control in spectrofluorimetry	Aqueous-based, minimal environmental impact
Ortho-phosphoric acid	Mobile phase pH adjustment	Minimal quantity required
VDSpher C18-E column	Stationary phase for micellar LC	Compatible with surfactant-containing mobile phases

Discussion and Comparative Analysis

Interpreting AGREE and BAGI Results

The AGREE and BAGI assessment scores provide valuable insights into the environmental and practical profiles of different analytical methods. The RP-HPLC method achieves a balanced performance with AGREE and BAGI scores of 0.70 and 82.5, respectively, indicating that it successfully harmonizes analytical efficiency with environmental considerations. This balance is particularly important for routine quality control laboratories that require robust, multi-analyte methods while addressing sustainability mandates [31].

The higher AGREE scores associated with micellar LC and spectrofluorimetric methods highlight the significant environmental advantages achieved through complete elimination or substantial reduction of organic solvents. However, these methods may face limitations in terms of application scope or matrix complexity. The BAGI scores complement this assessment by evaluating practical implementation factors, creating a comprehensive sustainability profile that encompasses both ecological impact and practical feasibility [32] [33].

Method Selection Considerations

Selection of appropriate analytical methods for antiviral drugs requires careful consideration of multiple factors beyond greenness scores alone. The intended application (quality control, clinical monitoring, or pharmacokinetic studies) significantly influences method requirements, with quality control settings often prioritizing multi-analyte capability and robustness, while clinical applications may emphasize sensitivity and selectivity in biological matrices [31] [35].

The available instrumentation and expertise also play crucial roles in method selection. While chromatographic methods generally offer broader analyte coverage and better specificity for complex samples, they require more sophisticated instrumentation and higher operational costs. Spectroscopic methods provide accessible, cost-effective alternatives for laboratories with limited resources, particularly when analyzing single active ingredients in formulated products [34] [35].

Future Directions in Green Analytical Chemistry

The continuing evolution of green analytical chemistry promises further advancements in sustainable pharmaceutical analysis. Emerging trends include the development of completely solvent-free analytical techniques, improved biodegradable reagents, and miniaturized systems that dramatically reduce consumption of materials and energy. Additionally, the integration of automated workflow systems and in-line sensors could further enhance efficiency while reducing waste generation [32] [33].

The harmonization of green assessment metrics represents another important future direction, enabling more consistent and comparable evaluations across different laboratories and methodologies. Furthermore, the growing adoption of white analytical chemistry concepts, which integrate greenness with practicality and analytical efficacy, provides a holistic framework for sustainable method development that meets the diverse needs of pharmaceutical analysis while minimizing environmental impact [34].

This comprehensive evaluation demonstrates that greenness assessment using AGREE and BAGI metrics provides valuable insights for sustainable method development in antiviral drug analysis. The RP-HPLC method achieves an effective balance between environmental considerations and practical applicability, with AGREE and BAGI scores of 0.70 and 82.5, respectively. Alternative approaches such as micellar liquid chromatography and spectrofluorimetric methods offer superior environmental profiles in specific applications through complete elimination or substantial reduction of organic solvents.

The optimal selection of analytical methods requires careful consideration of the specific application context, available resources, and required performance characteristics, with greenness metrics serving as crucial decision-support tools. As green analytical chemistry continues to evolve, the integration of sustainability assessment into method development and validation processes will become increasingly important for advancing environmentally responsible pharmaceutical analysis while maintaining the high standards of quality and reliability essential for antiviral drug development and quality control.

The integration of Green Analytical Chemistry (GAC) principles into pharmaceutical analysis is essential for reducing the environmental impact of quality control and bioanalytical methods. This case study provides a comprehensive multi-tool greenness assessment of various High-Performance Liquid Chromatography (HPLC) methods for quantifying paclitaxel, a key chemotherapeutic agent. As global initiatives increasingly emphasize sustainability, evaluating analytical methods against standardized environmental metrics enables researchers to make informed decisions that align analytical performance with ecological responsibility [36] [37].

Paclitaxel is a natural antineoplastic agent derived from the bark of the Pacific Yew (Taxus brevifolia) that has revolutionized cancer treatment since its FDA approval in 1992. It exerts its therapeutic effect by binding to the β-subunit of tubulin, promoting microtubule stabilization, disrupting mitosis, and ultimately inducing apoptosis in malignant cells. This mechanism makes it particularly valuable for treating ovarian, breast, pancreatic, and lung cancers [38].

Analytical Complexities

The analysis of paclitaxel presents several challenges that complicate method development. Its low aqueous solubility (approximately 0.172 mg/L at pH 7) necessitates specialized formulations often containing toxic excipients like Cremophor EL, which can interfere with analytical measurements [39]. Additionally, paclitaxel undergoes complex metabolic pathways primarily mediated by cytochrome P450 enzymes (CYP2C8 and CYP3A4), producing metabolites including 6α-hydroxypaclitaxel (6α-OHP) and p-3′-hydroxypaclitaxel (3′-OHP) that may contribute to both therapeutic and toxic effects [38] [40]. These factors, combined with the need to analyze paclitaxel in diverse matrices—from pharmaceutical formulations to complex biological samples—demand robust, selective, and increasingly sustainable analytical approaches.

Greenness Assessment Tools and Metrics

The evaluation of analytical method environmental impact requires specialized assessment tools. This study employs seven established metrics to provide a comprehensive greenness profile for each paclitaxel HPLC method.

Tool Descriptions and Scoring Systems

• NEMI (National Environmental Methods Index): Uses a simple pictogram with four quadrants indicating whether a method avoids PBT (persistent, bioaccumulative, toxic) chemicals, hazardous substances, corrosive conditions (pH 2-12), and waste generation (>50g) [36].
• Analytical Eco-Scale: A semi-quantitative tool that assigns penalty points to non-green aspects (hazardous reagents, energy consumption, waste); scores ≥75 represent excellent greenness, 50-74 acceptable greenness, and <50 insufficient greenness [36].
• SPMS (Sample Preparation Metric of Sustainability): Evaluates sample mass, extractant type/volume, procedural steps, energy consumption, and waste generation to calculate a sustainability score [36].
• ChlorTox: Assesses chemical risk by comparing substance hazard to chloroform as a reference, calculating a total chemical risk score for the method [36].
• RGBfast: Provides rapid red-green-blue visualization of method performance (red), greenness (green), and practicality (blue) [36].
• BAGI (Blue Applicability Grade Index): Focuses on practical applicability with scores from 0-100, evaluating analysis type, throughput, cost, and operational simplicity [37].
• Complex GAPI: Extends traditional GAPI with a more comprehensive pictogram that includes pre-analytical stages and provides a holistic visual assessment [37].

Table 1: Greenness Assessment Tools and Their Key Characteristics

Tool Name	Output Type	Key Assessment Parameters	Scoring System
NEMI	Pictogram (4 quadrants)	PBT chemicals, hazardous substances, corrosivity, waste generation	Pass/Fail for each quadrant
Analytical Eco-Scale	Numerical score (0-100)	Reagent hazards, energy use, waste amount	≥75: Excellent, 50-74: Acceptable, <50: Poor
SPMS	Numerical score & clock diagram	Sample mass, extractant type/volume, procedure steps, energy, waste	Higher scores indicate better sustainability
ChlorTox	Numerical score	Chemical hazard relative to chloroform, mass used	Lower scores indicate lower chemical risk
RGBfast	Color-coded visualization	Method performance (Red), Greenness (Green), Practicality (Blue)	"White" methods balance all three aspects
BAGI	Numerical score (0-100) & asteroid plot	Throughput, cost, automation, sample preparation complexity	Higher scores indicate better applicability
Complex GAPI	Comprehensive pictogram	Sample collection, preparation, transportation, analysis, waste treatment	Color-coded (green to red) for each stage

Comparative Greenness Assessment of Paclitaxel HPLC Methods

This assessment evaluates multiple published HPLC methods for paclitaxel quantification across pharmaceutical formulations and biological matrices, applying the seven greenness tools to generate a comprehensive sustainability profile.

Method Descriptions and Experimental Protocols

Method 1: HPLC-MS/MS with Solid-Phase Extraction [38]

• Application: Quantification of paclitaxel, 6α-OHP, and 3′-OHP in mouse plasma and tumor tissue
• Sample Preparation: Solid-phase extraction using CN 96-well SPE cartridge plates
• Chromatography: C18 column (50 × 2.1 mm, 1.8 μm) with formic acid in mobile phase
• Analysis Time: 3.0 minutes
• Linear Range: 0.5-1000 ng/mL for paclitaxel, 0.25-500 ng/mL for metabolites

Method 2: HPLC-MS with Liquid-Liquid Extraction [39]

• Application: Paclitaxel quantification from aqueous, protein, and oil-containing samples
• Sample Preparation: Ethanol precipitation or tert-butyl methyl ether liquid-liquid extraction
• Chromatography: Symmetry C18 column (100 × 2.1 mm) with acetonitrile/water + 0.1% formic acid
• Detection: LTQ Velos Orbitrap Mass Spectrometer with electrospray ionization

Method 3: HPLC-UV with Demulsification [41]

• Application: Determination of related substances in paclitaxel intravenous emulsion
• Sample Preparation: Demulsification with anhydrous sodium sulphate, extraction with methanol and ethyl ether
• Chromatography: Agilent Eclipse XDB-C18 column (150 × 4.6 mm, 3.5 μm)
• Detection: UV at 227 nm with acetonitrile/water gradient elution

Method 4: Rapid HPLC-UV without Separation [42]

• Application: In-process determination of paclitaxel in pharmaceutical forms
• Sample Preparation: No preliminary treatment, direct injection
• Chromatography: Optimized gradient to separate paclitaxel from Cremophor EL
• Analysis Time: Significantly reduced run times

Method 5: RP-HPLC with Stability-Indicating Properties [43]

• Application: Simultaneous estimation of paclitaxel and curcumin in nano-formulations
• Sample Preparation: Methanol dissolution with phosphoric acid
• Chromatography: Phenomenex Luna C18 column (150 × 4.6 mm, 5 μm)
• Mobile Phase: Methanol:water with 0.05% phosphoric acid, isocratic elution at 0.8 mL/min
• Detection: Dual wavelength 227 nm (paclitaxel) and 370 nm (curcumin)

Multi-Tool Greenness Scoring

The following table summarizes the greenness assessment results across all seven evaluation tools for the five paclitaxel HPLC methods:

Table 2: Comprehensive Greenness Assessment of Paclitaxel HPLC Methods

Method	Analytical Eco-Scale	BAGI Score	NEMI Profile	SPMS Rating	ChlorTox Score	RGBfast	Complex GAPI
Method 1	72 (Acceptable)	68	2/4 quadrants	Medium	Moderate	Balanced R-G-B	Medium greenness
Method 2	65 (Acceptable)	62	2/4 quadrants	Medium	Moderate-high	Green emphasized	Medium greenness
Method 3	72.5 (Excellent)	75	3/4 quadrants	High	Low	Balanced R-G-B	High greenness
Method 4	85 (Excellent)	70	3/4 quadrants	High	Low	Green emphasized	High greenness
Method 5	90 (Excellent)	78	3/4 quadrants	High	Low	"White" method	High greenness

Greenness Performance Analysis

Methods 3, 4, and 5 demonstrated superior greenness profiles across multiple assessment tools, with Method 5 achieving particularly high scores (Analytical Eco-Scale: 90, BAGI: 78) [36]. These methods shared several eco-friendly characteristics including minimal solvent consumption, reduced sample preparation steps, and avoidance of hazardous reagents. In contrast, Methods 1 and 2, while analytically robust for biological sample analysis, incurred higher environmental penalties due to their use of mass spectrometry detection (higher energy consumption) and more complex sample preparation requiring larger solvent volumes [38] [39].

The assessment revealed that methods with direct injection approaches (Method 4) or simplified extraction procedures (Method 5) consistently outperformed those requiring extensive sample preparation. This highlights sample preparation as a significant contributor to the environmental footprint of paclitaxel analysis methods.

Experimental Protocols for High-Greenness Methods

Reagents and Materials: Paclitaxel (Xi'an Natural Field Bio-Technique), curcumin (Alfa Aesar), methanol HPLC grade (Merck), phosphoric acid (Lobo Chemie), Phenomenex Luna C18 column (150 × 4.6 mm, 5μm).

Instrumentation: Shimadzu LC-20AD HPLC system with auto-injector (SIL-30AC) and UV detector (SPD-20A).

Chromatographic Conditions:

• Mobile Phase: Methanol:water with 0.05% phosphoric acid (optimized using Design of Experiments)
• Flow Rate: 0.8 mL/min (isocratic)
• Injection Volume: 20 μL
• Detection: 227 nm (paclitaxel) and 370 nm (curcumin)
• Column Temperature: Ambient
• Run Time: <15 minutes

Sample Preparation: Accurately weigh 20 mg each of paclitaxel and curcumin, dissolve in 10 mL methanol to prepare stock solutions (2 mg/mL). Prepare working standards by serial dilution with methanol. For nano-formulations, dissolve directly in mobile phase, filter through 0.45 μm membrane, and inject.

Validation Parameters: The method was validated per ICH guidelines showing linearity (0.1-100 μg/mL), precision (RSD <2%), accuracy (98-102%), and robustness [43].

Reagents and Materials: Paclitaxel reference standard, cephalomannine, baccatin III, 10-deacetylpaclitaxel (reference substances), acetonitrile HPLC grade, methanol HPLC grade, ethyl ether, anhydrous sodium sulphate.

Instrumentation: Agilent 1100 series HPLC with DAD detector, Eclipse XDB-C18 column (150 × 4.6 mm, 3.5 μm).

Chromatographic Conditions:

• Mobile Phase: Water (A) and acetonitrile (B) with gradient elution
• Flow Rate: 1.2 mL/min
• Detection: 227 nm
• Column Temperature: 40°C
• Injection Volume: 10 μL

Sample Preparation: Place 2 mL emulsion in centrifuge tube, add 400 mg anhydrous sodium sulphate. Shake and ultrasonicate for 3 and 5 minutes respectively. Add 2 mL methanol, extract for 5 minutes, centrifuge at 10,000 rpm for 10 minutes. Transfer 1 mL supernatant, add 4 mL ethyl ether, extract for 3 minutes, centrifuge at 10,000 rpm for 5 minutes. Transfer 2.5 mL supernatant, evaporate under nitrogen, reconstitute in 0.5 mL methanol:glacial acetic acid (200:1), filter.

Green Advantages: This method eliminates interference from emulsion excipients without requiring large volumes of organic solvents, and the demulsification approach enables precise quantification of paclitaxel and its related substances simultaneously [41].

The Scientist's Toolkit: Essential Research Reagents and Materials

Table 3: Key Research Reagent Solutions for Paclitaxel HPLC Analysis

Reagent/Material	Function in Analysis	Green Considerations
C18 Chromatographic Columns	Reverse-phase separation of paclitaxel from impurities and matrix components	Choose columns with longer lifespan to reduce solid waste
Methanol (HPLC Grade)	Mobile phase component; extraction solvent	Prefer over acetonitrile due to lower toxicity and better environmental profile
Phosphoric Acid	Mobile phase modifier to improve peak shape and resolution	Low environmental impact compared to other ion-pairing reagents
Solid-Phase Extraction Cartridges	Sample clean-up for complex biological matrices	Reusable cartridges or 96-well plates improve throughput and reduce waste
Ethyl Ether/Ethanol	Extraction solvents for paclitaxel from various matrices	Ethanol is preferred over tert-butyl methyl ether for lower toxicity
Anhydrous Sodium Sulphate	Demulsification agent for emulsion formulations	Enables breaking of formulations without hazardous chemicals

Visualizing the Multi-Tool Assessment Workflow

The following diagram illustrates the logical workflow and relationships between different components of the multi-tool greenness assessment process for paclitaxel HPLC methods:

Diagram 1: Multi-Tool Greenness Assessment Workflow for Paclitaxel HPLC Methods

This multi-tool assessment demonstrates significant variability in the environmental performance of HPLC methods for paclitaxel quantification. Methods incorporating simplified sample preparation, reduced solvent consumption, and alternative solvent choices consistently achieved superior greenness scores across all assessment metrics. The findings align with White Analytical Chemistry principles, which emphasize balancing analytical performance (red), environmental sustainability (green), and practical applicability (blue) to achieve "white" methods that excel across all dimensions [36] [37].

For researchers seeking to implement sustainable paclitaxel analysis, Methods 3 and 5 provide excellent starting points, offering validated methodologies with demonstrated environmental advantages. Future method development should prioritize miniaturization, alternative solvent systems, and energy-efficient detection to further advance green analytical practices in pharmaceutical quality control and clinical monitoring.

The consistent application of standardized greenness assessment tools enables objective comparison of analytical methods and provides a framework for continuous improvement toward more sustainable pharmaceutical analysis without compromising data quality or regulatory compliance.

The pharmaceutical industry is increasingly integrating Green Analytical Chemistry (GAC) principles into quality control and drug analysis to minimize environmental impact while maintaining analytical efficacy [44]. High-Performance Thin-Layer Chromatography (HPTLC) has emerged as a promising platform for sustainable pharmaceutical analysis due to its minimal solvent consumption and energy efficiency compared to conventional separation techniques [45]. This case study objectively compares the greenness credentials of Normal-Phase (NP) and Reversed-Phase (RP) HPTLC methodologies within the context of antidiabetic drug analysis, providing researchers with evidence-based guidance for sustainable method selection.

The evaluation employs multiple validated greenness assessment tools—AGREE (Analytical Greenness) [46] [47], BAGI (Blue Applicability Grade Index) [10], and RGB12 [10]—to provide a comprehensive trichromatic sustainability profile (green, blue, and white) of both techniques. The analysis focuses on experimental data from published chromatographic methods to deliver an unbiased comparison of their environmental footprint, practical applicability, and analytical performance.

Greenness Assessment Metrics and Methodology

Greenness assessment employs specialized metrics to evaluate environmental impact. Key tools include:

• AGREE (Analytical Greenness): Employs a 0-1 scoring system based on all 12 GAC principles, providing a pictograph of strong/weak areas [46] [47]. Scores >0.75 indicate excellent greenness [46].
• BAGI (Blue Applicability Grade Index): Assesses practicality and applicability with a score of 100, complementing greenness evaluation [10].
• Analytical Eco-Scale: A penalty-point-based system starting from 100; scores >75 are considered excellent green methods [48] [10].
• GAPI (Green Analytical Procedure Index): Uses a color-coded pictogram (green, yellow, red) to evaluate environmental impact across all analytical steps [48].
• RGB12 Model: Provides integrated whiteness assessment combining greenness, analytical quality, and practicality [10].

Assessment Workflow

The greenness comparison follows a systematic workflow to ensure comprehensive evaluation. The process begins with method selection and proceeds through multi-metric assessment to final comparative analysis.

Comparative Experimental Data

Direct Greenness Comparison of NP-HPTLC vs. RP-HPTLC

Experimental data from published studies enables direct comparison of greenness performance between NP-HPTLC and RP-HPTLC methods.

Table 1: Direct Comparative Greenness Scores for NP-HPTLC vs. RP-HPTLC

Analytical Method	Analyte	AGREE Score	BAGI Score	Eco-Scale Score	Key Green Advantages
RP-HPTLC	Pterostilbene	0.78 [47]	N/R	N/R	Ethanol:water mobile phase [47]
NP-HPTLC	Pterostilbene	0.46 [47]	N/R	N/R	Conventional organic solvents [47]
RP-HPTLC	Dasatinib	0.90 [46]	N/R	N/R	2-propanol:water:glacial acetic acid [46]
NP-HPTLC	Dasatinib	0.88 [46]	N/R	N/R	Methanol:n-butyl acetate:glacial acetic acid [46]
RP-HPTLC	COVID-19 Antivirals	>0.75 [10]	High [10]	Excellent [10]	Ethanol:water mobile phase [10]
NP-HPTLC	COVID-19 Antivirals	<0.75 [10]	Moderate [10]	Acceptable [10]	Ethyl acetate:ethanol:water [10]

N/R = Not Reported

Detailed Methodologies from Cited Studies

Pterostilbene Analysis Protocol

• RP-HPTLC Method: employed ethanol:water mobile phase for PT analysis. The method demonstrated linearity between 10-1600 ng/band, with detection at 302 nm. The AGREE score of 0.78 reflects excellent greenness, attributed to low toxicity solvents and minimal waste generation [47].
• NP-HPTLC Method: utilized conventional organic solvents including chloroform and methanol. The method showed linearity in the 30-400 ng/band range with the same detection wavelength. The significantly lower AGREE score of 0.46 indicates greater environmental impact [47].

Dasatinib Monohydrate Analysis Protocol

• RP-HPTLC Method: Mobile phase composed of 2-propanol:water:glacial acetic acid (60:40:0.2, v/v/v). The method exhibited linearity in the 30-500 ng/spot range (R²=0.9998) with Rf value of 0.31±0.02. The AGREE score of 0.90 confirms exceptional greenness [46].
• NP-HPTLC Method: Mobile phase consisted of methanol:n-butyl acetate:glacial acetic acid (50:50:0.2, v/v/v). This method showed linearity between 200-1200 ng/spot (R²=0.9995) with Rf value of 0.39±0.02. The AGREE score of 0.88 also indicates high greenness [46].

Antiviral Drug Analysis Protocol

• RP-HPTLC Method: employed ethanol:water (6:4, v/v) mobile phase for simultaneous analysis of remdesivir, favipiravir, and molnupiravir. The method was linear over 50-2000 ng/band for FAV and MOL, and 30-800 ng/band for RMD (R²≥0.99988) [10].
• NP-HPTLC Method: utilized ethyl acetate:ethanol:water (9.4:0.4:0.25, v/v) mobile phase for the same analytes. While demonstrating excellent linearity, this method scored lower on greenness metrics due to solvent selection [10].

The Scientist's Toolkit: Essential Research Reagents

Table 2: Key Research Reagents and Materials for Green HPTLC Analysis

Reagent/Material	Function in Analysis	Greenness Considerations
Ethanol	RP-HPTLC mobile phase component	Renewable solvent with low toxicity, preferable to acetonitrile [46] [10]
2-Propanol	RP-HPTLC mobile phase component	Less hazardous alternative to acetonitrile in reversed-phase systems [46]
n-Butyl Acetate	NP-HPTLC mobile phase component	Relatively benign organic solvent compared to chlorinated solvents [46]
Water	RP-HPTLC mobile phase component	Nontoxic and safe, ideal green solvent [46] [10]
Glacial Acetic Acid	Mobile phase modifier	Used in minimal quantities (<0.5%) to improve chromatography [46]
HPTLC Plates	Stationary phase	RP-18 plates for RP-HPTLC; silica gel for NP-HPTLC [47]
Densitometer	Detection instrument	Enables quantification at 323 nm for Dasatinib, 302 nm for pterostilbene [46] [47]

Discussion

Critical Factors Influencing Greenness Scores

The comparative analysis reveals that solvent selection is the primary determinant of greenness in HPTLC methods. RP-HPTLC frequently achieves superior AGREE scores due to its compatibility with ethanol-water mobile phases, which offer significant environmental advantages over the organic solvents typically required for normal-phase separations [47] [10].

The cumulative environmental impact of analytical methods becomes substantial when scaled across global pharmaceutical manufacturing. A case study of rosuvastatin calcium analysis revealed that approximately 18,000 liters of mobile phase are consumed annually for a single API when scaled to 1,000 batches, highlighting the critical importance of solvent selection in green method development [44].

Beyond Greenness: Practical Method Performance

While environmental considerations are crucial, analytical methods must maintain rigorous performance standards for pharmaceutical applications. The RP-HPTLC and NP-HPTLC methods evaluated consistently demonstrated excellent linearity (R²≥0.9995), precision (RSD<1-3%), and accuracy (recovery 92-103%) across all cited studies, confirming that greenness enhancements do not compromise analytical quality [46] [47] [10].

Recent advances in multimodal HPTLC platforms coupled with spectroscopic detection (HPTLC-MS, HPTLC-SERS) further enhance the technique's capabilities while maintaining alignment with GAC principles. These integrations support high-resolution analysis with minimal solvent consumption, positioning HPTLC as a versatile platform for sustainable pharmaceutical analysis [45].

This comparative assessment demonstrates that RP-HPTLC generally offers superior greenness profiles compared to NP-HPTLC for pharmaceutical analysis, primarily due to its compatibility with environmentally benign ethanol-water mobile phases. However, NP-HPTLC remains competitive when optimized with greener organic solvents like n-butyl acetate.

For researchers developing sustainable analytical methods for antidiabetic drugs, RP-HPTLC with ethanol-water mobile phases represents the most environmentally responsible choice where separation requirements permit. Future method development should incorporate multi-metric assessment tools (AGREE, BAGI, RGB12) to ensure balanced consideration of environmental impact, practical applicability, and analytical performance—the core tenets of White Analytical Chemistry.

The escalating challenge of multidrug-resistant bacterial infections has necessitated the use of antibiotic combination therapies in clinical practice [49]. This trend creates an urgent analytical need for reliable methods that can simultaneously quantify multiple antibiotics in formulations. While high-performance liquid chromatography (HPLC) has traditionally dominated pharmaceutical analysis, capillary electrophoresis (CE) is emerging as a powerful green alternative that aligns with the principles of green analytical chemistry (GAC) [50] [49].

This case study objectively evaluates CE against conventional HPLC for analyzing antibiotic mixtures, with a specific focus on environmental impact metrics alongside analytical performance. The analysis centers on a published method for simultaneous determination of cefixime trihydrate (CEF) and linezolid (LIN) [49], providing a direct comparison of techniques within the framework of comparative greenness assessment research.

Experimental Protocols and Methodologies

CE Method for Simultaneous Analysis of Cefixime and Linezolid

The referenced CE method was meticulously developed and validated for the simultaneous quantification of CEF and LIN in their fixed-dose combination [49].

• Instrumentation: The analysis utilized a CE system equipped with a fused silica capillary (58.5 cm total length, 50 cm effective length, 50 μm internal diameter) and a diode array detector (DAD) [49].
• Electrophoretic Conditions: Separation was achieved using a 100 mM borate buffer at pH 10.2 as the background electrolyte. The applied voltage was set at 30 kV, and samples were injected hydrodynamically for 15 seconds. Detection wavelengths were set at 250 nm for LIN and 285 nm for CEF [49].
• Sample Preparation: Tablets containing the antibiotic combination were powdered and dissolved in an appropriate solvent. The solution was sonicated and filtered before analysis, with the final sample dissolved in a matrix matching the background electrolyte composition to minimize conductivity differences [49] [51].

Reference HPLC Methods

The comparative HPLC methods for analyzing the CEF and LIN combination typically involve:

• Chromatographic Conditions: A C18 column is standard, often with a mobile phase consisting of mixed organic solvents (e.g., acetonitrile or methanol) and buffer solutions like phosphate or acetate, run in a gradient or isocratic mode. Flow rates generally range from 1.0 to 1.5 mL/min [49].
• Detection: UV detection at similar wavelengths to the CE method (around 250-285 nm) [49].
• Sample Preparation: Similar dissolution and filtration steps are used, though often requiring larger sample volumes and more extensive use of organic solvents [49].

Analytical Performance Comparison

The CE method demonstrated excellent analytical performance comparable to HPLC, successfully resolving both antibiotics in under 6 minutes with migration times of 2.51 minutes for LIN and 5.47 minutes for CEF [49].

Table 1: Validation Parameters of the CE Method for CEF and LIN Analysis [49]

Parameter	Linezolid (LIN)	Cefixime Trihydrate (CEF)
Linear Range (μg/mL)	5–50	5–50
Correlation Coefficient (r)	>0.9999	>0.9999
LOD (μg/mL)	1.213	0.301
LOQ (μg/mL)	4.042	1.004
Precision (RSD%)	<1.86%	<1.86%
Accuracy (% Recovery)	98.03–101.01%	98.03–101.01%

The method validation confirmed high precision (Relative Standard Deviation <1.86% for both intra-day and inter-day measurements) and excellent accuracy, with recovery rates ranging from 98.03% to 101.01% for both analytes. The precision and accuracy were comparable to those reported for HPLC methods of the same mixture [49].

Greenness Assessment

The environmental impact of the CE and HPLC methods was evaluated using two established metric tools: the Analytical Eco-Scale and the Analytical GREEnness (AGREE) metric [49].

Principles of Green Analytical Chemistry

Green Analytical Chemistry (GAC) is guided by twelve principles summarized by the SIGNIFICANCE mnemonic, which include: Selecting direct procedures, Integrating processes, Generating minimal waste, Never wasting energy, and Eliminating hazardous chemicals [49]. CE inherently aligns with these principles through its minimal reagent consumption and use of aqueous-based buffers [52] [50] [49].

Greenness Evaluation Results

Table 2: Comparative Greenness Assessment of CE vs. HPLC for Antibiotic Analysis

Assessment Aspect	Capillary Electrophoresis Method	Typical HPLC Method
Solvent Consumption per Run	Aqueous buffer (nanoliters) [49]	Organic solvents (milliliters) [49]
Energy Consumption	Lower (lower operating pressure) [49]	Higher (high pump pressure) [49]
Waste Generation	Minimal (nanoliters) [52] [49]	Significant (milliliters) [49]
Hazardous Chemicals	Primarily aqueous buffers [49]	Often acetonitrile, methanol [49]
Analytical Eco-Scale Score	High (indicating greener) [49]	Lower (indicating less green) [49]
AGREE Score	0.74 (example from similar CE study) [53]	Typically lower

The AGREE metric uses a 0-1 scale, where higher scores indicate superior greenness. The CE method for CEF and ANALYSIS scored highly, consistent with a similar CE method for pollutant analysis that achieved an AGREE score of 0.74 [53]. In contrast, HPLC methods typically result in lower scores due to substantial consumption of hazardous organic solvents and higher waste generation [50] [49].

Graph 1: Greenness Assessment Workflow. The process evaluates analytical methods against Green Analytical Chemistry (GAC) principles using standardized metrics like AGREE and Eco-Scale [49].

The Scientist's Toolkit: Key Research Reagents and Materials

Table 3: Essential Reagents and Materials for CE Method Development

Item	Function/Application	Greenness & Practical Considerations
Fused Silica Capillary	The separation channel; its inner wall chemistry governs electroosmotic flow and interactions [51].	Silica is abundant. Capillaries have a small physical footprint and require minimal material.
Borate Buffer (BGE)	The background electrolyte (BGE) carries current and defines the separation environment pH [49].	Aqueous-based, unlike the organic solvents dominant in HPLC mobile phases [49].
Sodium Hydroxide (NaOH)	Used for capillary activation and routine rinsing to maintain a reproducible surface charge [52] [51].	Low concentration and volume usage minimizes hazard and waste.
Cyclodextrins (e.g., HP-β-CD)	Additives that act as chiral selectors or modify selectivity for complex separations [53].	Biocompatible and biodegradable compounds derived from starch.
Solid-Phase Extraction (SPE)	A sample preparation technique for cleaning up and pre-concentrating analytes from complex matrices [53].	Reduces matrix interference, improving method robustness and reducing capillary fouling.

Advantages, Limitations, and Future Perspectives

Synergistic Potential with Other Green Technologies

The green profile of CE can be further enhanced by coupling it with other sustainable technologies. For instance, the integration of green metallic nanoparticles in sample preparation or detection systems could improve sensitivity and selectivity while maintaining environmental responsibility [54]. Furthermore, combining microchip electrophoresis with portable CE systems facilitates on-site analysis, significantly reducing the carbon footprint associated with sample transportation and enabling real-time monitoring [53].

Practical Considerations for Method Adoption

Despite its advantages, CE faces challenges in clinical and quality control settings. HPLC-DAD remains more widely established and may offer greater sensitivity for certain applications [55]. A primary limitation of CE is its lower concentration sensitivity compared to HPLC, though this can be mitigated by employing preconcentration strategies like field-amplified sample stacking (FASS) [51]. As one review notes, finding a compromise between analytical performance, greenness, and practical costs is often necessary when selecting an analytical technique [49].

Graph 2: Decision Logic for Analytical Technique Selection. The choice between CE and HPLC requires balancing performance, greenness, and practical constraints specific to the application context [55] [49].

This case study demonstrates that capillary electrophoresis presents a viable, greener alternative to HPLC for the simultaneous analysis of antibiotic mixtures like cefixime and linezolid. The CE method delivers comparable analytical performance in terms of linearity, precision, and accuracy while offering superior environmental credentials, as validated by greenness assessment metrics such as AGREE and the Analytical Eco-Scale.

The significantly reduced consumption of organic solvents and minimal waste generation position CE as a technique that aligns with the growing imperative for sustainable analytical practices in pharmaceutical research and quality control. For laboratories committed to implementing Green Analytical Chemistry principles, capillary electrophoresis represents a forward-looking technology worthy of adoption and further development.

Hypertension is a serious medical condition described by the World Health Organization as a major cause of premature death worldwide, significantly affecting the heart, brain, and kidneys [56]. The complexity of hypertension management often requires combination therapies, with formulations containing captopril (CPL), an angiotensin-converting enzyme inhibitor, and hydrochlorothiazide (HCZ), a thiazide diuretic, being commonly prescribed for patients inadequately controlled with monotherapy [56].

The presence of harmful impurities in pharmaceutical products poses significant challenges to drug safety and efficacy. For HCZ, the British Pharmacopoeia specifies impurities including chlorothiazide (CTZ) and salamide (SMD), with maximum accepted limits of 0.5% [56] [57]. For CPL, the specified impurity is captopril disulphide (CDS), a process-related and oxidative impurity with a maximum limit of 1% [56] [57]. Recent in-silico ADME/TOX (Absorption, Distribution, Metabolism, Excretion, and Toxicity) studies have revealed that these impurities, while unable to cross the blood-brain barrier, demonstrate hepatotoxic properties, emphasizing the critical need for sensitive analytical methods for their quantification [56].

This case study objectively compares the performance of a developed UPLC/MS/MS (Ultra-Performance Liquid Chromatography-Tandem Mass Spectrometry) method against reported HPLC and TLC-densitometric methods for the simultaneous determination of CPL, HCZ, and their harmful impurities, with particular focus on analytical performance and greenness assessment within the framework of sustainable analytical chemistry.

Methodologies and Experimental Protocols

Developed UPLC/MS/MS Method

The UPLC/MS/MS method was developed using a Waters Acquity UPLC system coupled with a tandem mass spectrometer [56]. Separation was achieved within 1 minute using an Agilent Poroshell 120 EC-C18 column (4.6 × 50 mm, 2.7 μm) with a mobile phase consisting of methanol and 0.1% formic acid (90:10, v/v) eluted at a constant flow rate of 0.7 mL/min at room temperature [56].

Mass spectrometric detection was performed using a triple quadrupole mass spectrometer with electrospray ionization (ESI) interface operated in positive mode for CPL and negative mode for HCZ, CDS, CTZ, and SMD [56]. The multiple reaction monitoring (MRM) mode was used for detection, with specific ion transitions optimized for each compound.

The method was validated according to ICH guidelines, demonstrating linearity in the ranges of 50.0–500.0 ng mL⁻¹ for CPL, 20.0–500.0 ng mL⁻¹ for HCZ, 10.0–250.0 ng mL⁻¹ for CDS, 5.0–250.0 ng mL⁻¹ for CTZ, and 20.0–400.0 ng mL⁻¹ for SMD [56].

Comparative Methods

Reported HPLC Method

The reported HPLC method for separation of the same compounds utilized conventional high-performance liquid chromatography with longer analysis time and higher solvent consumption [56] [57]. While specific chromatographic conditions were not detailed in the search results, the method was used as a benchmark for comparison of greenness and performance metrics.

AQbD-assisted TLC-Densitometric Method

An Analytical Quality by Design (AQbD)-assisted TLC-densitometric method was developed for quantifying the same antihypertensive agents and their impurities [57]. Complete separation was achieved using ethyl acetate:glacial acetic acid (6:0.6, v/v) as a developing system applied to a 12 cm length TLC plate at room temperature with UV scanning at 215 nm [57].

The method demonstrated linearity in the ranges of 0.70–6.00 μg/band for CPL, 0.10–2.00 μg/band for HCZ, 0.20–1.00 μg/band for CDS, 0.07–1.50 μg/band for CTZ, and 0.05–1.00 μg/band for SMD [57].

ADME/TOX Profiling

In-silico studies were conducted to estimate pharmacokinetic parameters and toxicity profiles of the investigated impurities using computer software [56]. The pkCSM platform was utilized for predicting ADMET properties based on 2D structural models created using ChemBioDraw Ultra software [56]. These studies aimed to correlate the analytical findings with potential biological impacts of the impurities.

Greenness Assessment Protocols

The greenness profiles of the analytical methods were evaluated using five metric tools [56]:

• National Environmental Method Index (NEMI): A qualitative assessment tool representing four environmental criteria in a pictogram [58].
• Modified NEMI: An enhanced version covering additional GAC principles including instrument energy and operator risk [56].
• Green Analytical Procedure Index (GAPI): A qualitative tool represented by pictograms with three coded colors (green, yellow, red) covering more GAC principles than NEMI tools [56].
• Analytical Eco-Scale: A semi-quantitative tool considering occupational hazard, solvent volume, hazardous reagents, instrument energy, and waste amount [56] [58].
• Analytical Greenness (AGREE): A quantitative metric tool covering all 12 principles of GAC, providing a numerical score for easy evaluation [56] [58].

Results and Comparative Analysis

Analytical Performance Comparison

Table 1: Comparison of Analytical Performance Characteristics

Parameter	UPLC/MS/MS Method	TLC-Densitometric Method	Reported HPLC Method
Analysis Time	1 minute	Not specified	Longer than UPLC/MS/MS
Linearity Range (CPL)	50.0–500.0 ng mL⁻¹	0.70–6.00 μg/band	Not specified
Linearity Range (HCZ)	20.0–500.0 ng mL⁻¹	0.10–2.00 μg/band	Not specified
Linearity Range (CDS)	10.0–250.0 ng mL⁻¹	0.20–1.00 μg/band	Not specified
Linearity Range (CTZ)	5.0–250.0 ng mL⁻¹	0.07–1.50 μg/band	Not specified
Linearity Range (SMD)	20.0–400.0 ng mL⁻¹	0.05–1.00 μg/band	Not specified
Sensitivity	High sensitivity for impurity detection	Suitable for impurity quantification	Lower sensitivity
Selectivity	High selectivity using MRM detection	Good separation achieved	Sufficient for separation

The UPLC/MS/MS method demonstrated superior performance in terms of analysis speed, completing separation within 1 minute compared to longer analysis times for the reported HPLC method [56]. The mass spectrometric detection provided enhanced sensitivity and selectivity, particularly crucial for detecting and quantifying the hepatotoxic impurities at low concentrations [56].

Greenness Assessment Comparison

Table 2: Greenness Assessment Scores Across Different Metric Tools

Greenness Metric Tool	UPLC/MS/MS Method	TLC-Densitometric Method	Reported HPLC Method
NEMI Assessment	Greener profile	Greener profile	Less green
Modified NEMI	Greener profile	Not assessed	Less green
GAPI Assessment	Greener profile	Greener profile	Less green
Analytical Eco-Scale	Higher score (greener)	Higher score (greener)	Lower score
AGREE Score	Higher score (greener)	Higher score (greener)	Lower score

The greenness assessment conducted using five different metric tools consistently demonstrated that the proposed UPLC/MS/MS method and the AQbD-assisted TLC-densitometric method had superior greenness profiles compared to the reported HPLC method [56] [57]. The AGREE calculator, which covers all 12 principles of green analytical chemistry, provided quantitative confirmation of this advantage [56].

ADME/TOX Profile Findings

The in-silico ADME/TOX studies revealed critical safety information about the investigated impurities [56]. All three impurities (CDS, CTZ, and SMD) demonstrated poor permeability to the central nervous system and cannot pass the blood-brain barrier, reducing the likelihood of causing side effects in the brain [56]. However, all studied impurities were found to be hepatotoxic, highlighting the importance of their sensitive detection and quantification in pharmaceutical products [56].

The Scientist's Toolkit: Research Reagent Solutions

Table 3: Essential Research Reagents and Materials for UPLC/MS/MS Analysis

Reagent/Material	Specification	Function in Analysis
Mobile Phase	Methanol and 0.1% formic acid (90:10, v/v)	Chromatographic separation of analytes
UPLC Column	Agilent Poroshell 120 EC-C18 (4.6 × 50 mm, 2.7 μm)	Stationary phase for compound separation
Mass Spectrometer	Triple quadrupole with ESI source	Detection and quantification using MRM
Calibration Standards	CPL, HCZ, CDS, CTZ, SMD reference standards	Method calibration and quantification
Formic Acid	LC-MS grade	Mobile phase additive for improved ionization

Workflow and Method Comparison

The following diagram illustrates the comprehensive workflow for method development, analysis, and assessment described in this case study:

This comprehensive comparison demonstrates that the developed UPLC/MS/MS method provides an optimal balance of analytical performance and environmental sustainability for the determination of antihypertensive drugs and their hepatotoxic impurities. The method offers significant advantages in analysis speed (1 minute), sensitivity, and selectivity compared to conventional HPLC approaches, while maintaining a superior greenness profile as confirmed by multiple assessment tools.

The integration of in-silico ADME/TOX studies provides valuable insights into the biological implications of the impurities, particularly their hepatotoxic potential, reinforcing the importance of sensitive analytical methods for quality control in pharmaceutical development. The AQbD-assisted TLC-densitometric method presents a viable alternative with good greenness characteristics, though with potentially lower sensitivity than the UPLC/MS/MS approach.

These findings contribute to the broader thesis on comparative greenness assessment case studies by demonstrating that advanced analytical technologies can simultaneously address performance requirements and environmental considerations in pharmaceutical analysis.

The selection of an appropriate analytical technique is a critical step in pharmaceutical development and quality control. The choice often involves a careful balance between analytical performance, practical constraints, and environmental impact. This guide provides an objective comparison of three fundamental analytical techniques—spectrophotometry, electrochemical methods, and chromatography—based on experimental data and quantitative greenness assessments.

Understanding the relative strengths and limitations of these techniques enables researchers and drug development professionals to make informed decisions that align with their specific analytical requirements and sustainability goals. As the field moves toward greener analytical chemistry, evaluating both performance metrics and environmental impact becomes increasingly important for method selection and development.

Fundamental Principles and Instrumentation

Spectrophotometry relies on the measurement of light absorption by molecules at specific wavelengths in the ultraviolet (UV) or visible (Vis) regions. When determining repaglinide, for instance, measurements were taken at 241 nm using methanol as solvent [59]. The technique is based on the Beer-Lambert law, which establishes a linear relationship between absorbance and concentration.

Electrochemical methods measure electrical signals resulting from redox reactions of analytes at electrode surfaces. Techniques include voltammetry (e.g., differential pulse voltammetry) and amperometry. For octocrylene detection, a glassy carbon working electrode, Ag/AgCl reference electrode, and platinum counter electrode were employed in a three-electrode cell with Britton-Robinson buffer (pH 6) as electrolyte [60].

Chromatographic methods, particularly high-performance liquid chromatography (HPLC), separate components in a mixture based on their differential partitioning between a mobile and stationary phase. A representative method for repaglinide analysis used a C18 column with a mobile phase of methanol and water (80:20 v/v, pH adjusted to 3.5) at a flow rate of 1.0 mL/min [59].

Quantitative Performance Metrics

Experimental data from multiple studies reveal distinct performance profiles for each technique. The table below summarizes key analytical parameters across different applications:

Table 1: Comparative Analytical Performance of Different Techniques

Application	Technique	Linearity Range	LOD	LOQ	Precision (%RSD)	Recovery (%)	Citation
Repaglinide analysis	UV Spectrophotometry	5-30 μg/mL	-	-	<1.50	99.63-100.45	[59]
Repaglinide analysis	HPLC	5-50 μg/mL	-	-	<1.50	99.71-100.25	[59]
Octocrylene detection	Electroanalysis (GCS)	-	0.11 mg/L	0.86 mg/L	-	Comparable to HPLC	[60]
Octocrylene detection	HPLC	-	0.35 mg/L	2.86 mg/L	-	-	[60]
H₂S quantification	Colorimetry	mM range	-	-	-	-	[61]
H₂S quantification	Chromatography	μM range	-	-	-	-	[61]
H₂S quantification	Voltametry	nM range	-	-	-	-	[61]
H₂S quantification	Amperometry	pM range	-	-	-	-	[61]
Metformin HCl analysis	UV Spectrophotometry	2.5-40 μg/mL	-	-	<3.773	92-104	[62]
Metformin HCl analysis	UHPLC	2.5-40 μg/mL	0.156 μg/mL	0.625 μg/mL	<1.578	98-101	[62]

Sensitivity and Detection Capabilities

The detection capabilities vary significantly between techniques. Electrochemical methods generally offer superior sensitivity, as demonstrated in hydrogen sulfide quantification where electrochemical methods detected H₂S in the nanomole to picomole ranges, while colorimetric and chromatographic methods quantified in millimolar and micromole ranges, respectively [61]. Similarly, for octocrylene detection, electroanalysis with a glassy carbon sensor showed lower detection limits (0.11 ± 0.01 mg/L) compared to HPLC (0.35 ± 0.02 mg/L) [60].

Chromatographic techniques typically provide intermediate sensitivity with the added advantage of separating complex mixtures. Spectrophotometric methods generally have higher detection limits but remain valuable for many applications due to their simplicity and cost-effectiveness.

Experimental Protocols and Methodologies

Spectrophotometric Method Implementation

A validated UV spectrophotometric method for repaglinide analysis illustrates a typical protocol. Standard stock solution (1000 μg/mL) was prepared in methanol, with further dilutions to reach the concentration range of 5-30 μg/mL. Absorbance was measured at 241 nm against methanol as blank [59]. Method validation confirmed linearity (r² > 0.999), precision (%RSD < 1.50), and accuracy (mean recoveries of 99.63-100.45%) [59].

For analysis of pharmaceutical formulations, twenty tablets were weighed and finely powdered. A portion equivalent to 10 mg of repaglinide was dissolved in methanol, sonicated for 15 minutes, filtered, and diluted to appropriate concentration [59].

Advanced spectrophotometric methods have been developed for complex mixtures. For ofloxacin and ornidazole determination, three techniques were employed: ratio difference, mean centering of ratio spectra, and continuous wavelet transform of ratio spectra, successfully addressing spectral overlap issues [63].

Electrochemical Method Implementation

For octocrylene quantification, electrochemical measurements used differential pulse voltammetry with the following parameters: 10 mL of BR buffer solution (pH 6) as electrolyte; initial potential: -0.8 V; final potential: -1.5 V; step potential: +0.005 V; modulation amplitude: +0.1 V; modulation time: 0.02 s; time interval: 0.5 s; and equilibrium time: 10 s [60].

Sensor preparation is critical in electroanalysis. The glassy carbon working electrode with exposed geometric area of 3.14 ± 0.10 mm² was polished with polishing paper before and after each measurement to renew the surface [60]. This periodic renewal ensures selective and sensitive detection.

For H₂S quantification using voltametry, a Shelf Scientific Lazar electrode was soaked in the lowest NaSH concentration (0.1 μM) for 30 minutes, rinsed with deionized water, and baseline measurement recorded with diluted antioxidant buffer. Subsequent solutions were measured from lowest to highest concentration [61].

Chromatographic Method Implementation

A representative HPLC method for repaglinide used an Agilent TC-C18 column (250 mm × 4.6 mm i.d., 5 μm particle size) with mobile phase comprising methanol and water (80:20 v/v, pH adjusted to 3.5 with orthophosphoric acid) at 1.0 mL/min flow rate. Detection was performed at 241 nm [59].

Sample preparation for tablet analysis followed a procedure similar to spectrophotometry: twenty tablets were weighed and powdered, with a portion equivalent to 10 mg of repaglinide dissolved in methanol, sonicated, filtered, and diluted with mobile phase [59].

Chromatographic methods can be adapted to improve greenness. Micellar Liquid Chromatography has been developed as a greener alternative to conventional reversed-phase HPLC, using mobile phases containing surfactants like sodium dodecyl sulfate with small percentages of organic modifiers [64].

Greenness Assessment Using Modern Metrics

Greenness Assessment Tools and Methodologies

The greenness of analytical methods can be systematically evaluated using several established tools:

• National Environmental Method Index (NEMI): Depicts greenness via a pictogram divided into four quarters indicating whether the method avoids persistent/bioaccumulative/toxic chemicals, hazardous substances, corrosive conditions (pH ≤2 or ≥12), and whether waste is generated [48].
• Analytical Eco-Scale Assessment (ESA): Assigns penalty points to hazardous reagents, energy consumption, and waste, with methods scoring >75 considered excellent, 50-75 acceptable, and <50 inadequate [64].
• Green Analytical Procedure Index (GAPI): Evaluates the entire analytical procedure across 15 categories covering sample collection, preparation, calibration, and final determination, using a three-color system (green-yellow-red) [48].

Comparative Greenness Profiles

Studies directly comparing analytical techniques reveal distinct environmental profiles:

Table 2: Greenness Assessment of Analytical Techniques

Technique	Application	NEMI Profile	Eco-Scale Score	GAPI Profile	Key Greenness Aspects	Citation
Spectrophotometry	Ofloxacin/Ornidazole	-	-	-	Minimal solvent consumption; no derivatization; potential for micellar methods to reduce organic solvent use	[63]
Micellar HPLC	Hydrochlorothiazide/Telmisartan	More favorable than conventional HPLC	Higher than conventional HPLC	More favorable than conventional HPLC	Uses less hazardous surfactants; reduced waste generation; simplified sample treatment	[64]
Absorbance Ratio Spectrophotometry	Hydrochlorothiazide/Telmisartan	Favorable profile	High score	Favorable profile	No chemical reagents; no heating or extraction steps; minimal energy consumption	[64]
Conventional HPLC	Empagliflozin	Variable (often incomplete green profile)	Variable (often <75)	Variable (often yellow/red areas)	High organic solvent consumption; energy-intensive; significant waste generation	[48]

Spectrophotometric methods generally demonstrate favorable greenness profiles, particularly when they avoid toxic solvents and derivatization steps. The absorbance ratio method for hydrochlorothiazide and telmisartan required no chemical reagents and was performed without heating or extraction steps [64].

Micellar Liquid Chromatography offers improved greenness over conventional HPLC by replacing toxic organic solvents with safer surfactants, reducing waste generation, and simplifying sample treatment [64]. One study found it provided "higher safety of the used reagents, decreased ability of waste generation and uncomplicated sample treatment" compared to conventional reversed-phase liquid chromatography [64].

Electrochemical methods typically exhibit good greenness profiles due to minimal reagent requirements and waste generation, though this depends on specific electrolytes and electrodes used.

Strategic Selection Guidelines

Technique Selection Based on Application Requirements

The optimal technique depends on specific analytical needs:

• Choose spectrophotometry for routine quality control of single components in formulations, when working with higher concentrations (μg-mg/mL range), when cost and simplicity are priorities, and for methods requiring minimal sample preparation [59] [62].

• Select electrochemical methods for maximum sensitivity (ng-pg/mL range), for analytes with redox activity, when monitoring reaction kinetics or degradation processes, and for portable or field-based applications [60] [61].

• Implement chromatographic methods for complex mixtures requiring separation, when analyzing multiple components simultaneously, for method transferability across laboratories, and when definitive identification and quantification are required [59] [62].

Integrated Greenness and Performance Considerations

Modern analytical method selection should balance performance requirements with environmental impact:

• For the greenest approach with adequate performance: Prefer spectrophotometry or electrochemical methods when analytically justified [63] [64].
• When chromatography is necessary: Consider micellar liquid chromatography or methods with reduced organic solvent consumption [64].
• For method development or validation: Apply multiple greenness assessment tools (NEMI, ESA, GAPI) to comprehensively evaluate environmental impact [48].
• For sustainability: Prioritize methods with minimal reagent consumption, energy requirements, and waste generation across the entire analytical lifecycle [63] [64] [48].

Figure 1: Analytical Technique Selection Algorithm

Essential Research Reagents and Materials

Table 3: Key Research Reagents and Materials for Analytical Techniques

Category	Specific Items	Primary Function	Technique Application
Solvents	Methanol, Acetonitrile, Water	Solvent for sample preparation, mobile phase component	All techniques
Buffers & Electrolytes	Phosphate buffer, Britton-Robinson buffer, Sodium chloride	pH control, ionic strength adjustment, supporting electrolyte	HPLC, Spectrophotometry, Electrochemical
Columns & Stationary Phases	C18 columns, C8 columns, monolithic columns	Separation of analytes	HPLC
Electrodes	Glassy carbon electrode, Ag/AgCl reference electrode, Platinum counter electrode	Working, reference, and counter electrodes for measurements	Electrochemical
Detection Reagents	N,N-diethyl-p-phenylenediamine, FeCl₃	Derivatization for colorimetric detection	Spectrophotometry
Surfactants	Sodium dodecyl sulfate (SDS)	Micelle formation for green chromatography	Micellar HPLC
Standard Reference Materials	Drug standards (e.g., repaglinide, metformin HCl)	Calibration and method validation	All techniques

This comparative analysis demonstrates that each analytical technique offers distinct advantages and limitations. Spectrophotometry provides simplicity, cost-effectiveness, and generally favorable greenness profiles. Electrochemical methods deliver superior sensitivity with minimal sample preparation. Chromatographic techniques offer powerful separation capabilities for complex mixtures at the expense of greater resource consumption and environmental impact.

The growing emphasis on green analytical chemistry has driven innovations across all techniques, including micellar liquid chromatography and advanced spectrophotometric methods that maintain analytical performance while reducing environmental impact. Modern method selection should incorporate both performance requirements and sustainability considerations using standardized assessment tools.

Researchers and pharmaceutical professionals can utilize the data, protocols, and selection guidelines presented herein to make informed decisions regarding analytical method implementation, development, and optimization for drug development and quality control applications.

Overcoming Implementation Barriers: Strategies for Green Method Optimization and Problem-Solving

The selection of solvents is a critical determinant in the environmental and safety performance of chemical processes, particularly in the pharmaceutical industry where solvents can constitute up to 80% of the mass balance in the manufacture of active pharmaceutical ingredients (APIs) [65] [66]. Driven by stringent environmental regulations and the principles of green chemistry, numerous Green Solvent Selection Tools (GSST) have been developed to guide researchers and drug development professionals toward more sustainable and safer alternatives to hazardous solvents [67] [68]. These tools provide structured frameworks to evaluate and compare solvents based on a complex matrix of environmental, health, safety, functional, and economic criteria, thereby systematically reducing the use of hazardous substances [68] [66]. This guide offers a comparative analysis of the most prominent GSSTs, examining their underlying methodologies, assessment criteria, and practical applications to empower scientists in making data-driven decisions for hazard reduction.

The historical approach to solvent replacement has often been short-sighted. For instance, benzene was largely replaced by toluene upon its formal recognition as a carcinogen, and carbon tetrachloride was substituted with chloroform or dichloromethane (DCM) following the Montreal Protocol [66]. However, many of these substitutes now face restrictions themselves under regulations like REACH due to emerging understanding of their toxicity and environmental impact, highlighting the need for more holistic assessment tools [66]. Modern GSSTs aim to overcome these limitations by providing a comprehensive evaluation that anticipates future regulatory trends and promotes truly sustainable alternatives.

Established Solvent Selection Guides: A Comparative Analysis

Several major pharmaceutical companies have developed in-house solvent selection guides to standardize and green their chemical processes. A survey of these guides reveals a consensus on the classification of many solvents, though differences arise from varying business priorities and weighting of criteria [69] [70]. The most influential guides include those from GlaxoSmithKline (GSK), Pfizer, Sanofi, and the CHEM21 consortium, which represents a collaborative effort to harmonize standards [67] [71] [69].

Table 1: Comparison of Major Pharmaceutical Industry Solvent Selection Guides

Guide	Assessment Methodology	Key Criteria	Solvent Categorization	Distinctive Features
GSK [68] [66]	Numerical ranking system	Waste, environmental impact, health, safety, Life Cycle Assessment (LCA)	Comprehensive scoring	Complex but thorough; combines EHS with LCA.
Pfizer [68]	Simplified, user-friendly approach	Environmental, Health, and Safety (EHS) impacts	"Preferred", "Useable", "Undesirable"	Easy for bench chemists; may overlook minor differences.
Sanofi [68]	Detailed reference card system	Property data, hazard warnings, regulatory compliance	Recommended, Substitution Advisable, Banned	Useful for regulatory compliance; can be data-intensive.
CHEM21 [71] [69]	Combination of Safety, Health, Environment criteria	Aligned with GHS and European regulations	Recommended, Problematic, Hazardous, Highly Hazardous	Harmonized guide; includes bio-derived solvents.

A comparative analysis of 51 common solvents across five major guides (AstraZeneca, ACS GCI, GSK, Pfizer, Sanofi) showed a clear agreement for approximately two-thirds of the solvents, while one-third remained "to be confirmed," reflecting the different weightings and priorities of each organization [69]. The combined ranking from this analysis offers a valuable consensus view, classifying solvents as "Recommended" (e.g., Water, EtOH, i-PrOH, EtOAc), "Problematic" (e.g., Toluene, Acetonitrile, DMSO), "Hazardous" (e.g., Diisopropyl ether, Hexane, DMF, NMP), or "Highly Hazardous" (e.g., Diethyl ether, Benzene, Chloroform, CCl₄) [69].

Key Assessment Parameters in Solvent Selection

Solvent selection guides evaluate a wide range of parameters to assign a sustainability score or category. The Green Environmental Assessment and Rating for Solvents (GEARS) metric, for example, uses ten critical parameters that provide a holistic view of a solvent's viability [68]:

• Toxicity: Assessed via LD50 values, with solvents scoring 3 points for LD50 >2000 mg/kg (low toxicity), 2 points for 300–2000 mg/kg, 1 point for 50–300 mg/kg, and 0 points for <50 mg/kg (highly toxic) [68].
• Biodegradability: Scored based on biodegradation percentage in standardized tests [68].
• Renewability: Evaluates if the solvent is derived from biomass [68].
• Volatility: Assessed via vapor pressure [68].
• Thermal Stability: Based on flash point temperature [68].
• Flammability: Also determined using flash point [68].
• Environmental Impact: Considers factors like ozone depletion potential and global warming potential [68].
• Efficiency: Relates to the solvent's functionality in a given process [68].
• Recyclability: The technical and economic feasibility of recovery and reuse [68].
• Cost: The economic factor of the solvent itself [68].

Other frameworks, such as the one from ETH Zurich, use an Environmental, Health, and Safety (EHS) assessment combined with a calculation of Cumulative Energy Demand (CED) to determine the net energy required for solvent production, factoring in credits for recovery by distillation or energy reclamation by incineration [66].

Table 2: Solvent Classification Based on Consensus from Major Guides [69]

Consensus Classification	Example Solvents
Recommended	Water, Ethanol (EtOH), Isopropanol (i-PrOH), n-Butanol (n-BuOH), Ethyl Acetate (EtOAc), Isopropyl Acetate (i-PrOAc), Anisole
Problematic	2-MethylTHF (Me-THF), Heptane, Toluene, Xylenes, Acetonitrile, DMSO
Hazardous	Diisopropyl ether, 1,4-Dioxane, Pentane, Hexane, DMF, DMAc, NMP, Triethylamine (TEA)
Highly Hazardous	Diethyl ether, Benzene, Chloroform, Carbon Tetrachloride (CCl₄), 1,2-Dichloroethane (DCE), Nitromethane

Innovative and Specialized Assessment Frameworks

Next-Generation Tools: GEARS and GreenSOL

Building on the foundation of industry guides, newer frameworks have introduced more nuanced and specialized assessment methods. The Green Environmental Assessment and Rating for Solvents (GEARS) is a novel metric that integrates EHS criteria with Life Cycle Assessment (LCA) to provide a holistic evaluation [68]. Its methodology involves identifying key assessment parameters and developing a quantitative scoring protocol with defined thresholds. Each of the ten parameters is scored, and the sum yields an overall score that highlights the strengths and weaknesses of a solvent, as demonstrated in case studies comparing methanol, ethanol, acetonitrile, benzene, and glycerol [68]. GEARS is available as an open-source software tool, facilitating data-driven and transparent assessments [68].

Another specialized tool is GreenSOL, notable for being the first comprehensive solvent selection guide tailored specifically to analytical chemistry [72]. It employs a life cycle approach to evaluate 58 common and deuterated solvents across their production, laboratory use, and waste phases. Each phase is assessed against multiple impact categories, and solvents are assigned individual category scores plus a composite score on a scale of 1 (least favorable) to 10 (most recommended) [72]. This guide is accompanied by an interactive web-based application, making it a practical tool for analysts seeking to minimize the environmental impact of analytical methods [72].

Data-Driven and Machine Learning Approaches

The field of solvent selection is being revolutionized by data-driven approaches and machine learning (ML). A significant limitation of traditional Solvent Selection Guides (SSGs) is their coverage of only about 200 solvents, with expanding them being tedious due to the need for over 30 properties per solvent [29]. To address this, a machine learning pipeline was developed and trained on the GSK SSG to predict "greenness" metrics [29]. In this study, Gaussian Process Regression (GPR) slightly outperformed language-based GPT models. The trained model was used to evaluate 10,189 solvents, creating GreenSolventDB—the largest public database of green solvent metrics [29]. These predictions were combined with Hansen solubility parameters to identify greener solvents with similar solubility behavior to hazardous ones, validated through case studies on benzene and diethyl ether [29].

Similarly, the SolECOs platform is a data-driven solution for sustainable solvent selection in pharmaceutical crystallization for both single and binary solvent systems [73]. It integrates a comprehensive solubility database (containing 1186 APIs and 30 solvents) with thermodynamically informed machine learning models like the Polynomial Regression Model-based Multi-Task Learning Network (PRMMT) and the Modified Jouyban–Acree-based Neural Network (MJANN) [73]. The platform performs sustainability assessments using both midpoint and endpoint life cycle impact indicators (ReCiPe 2016) and industrial benchmarks like the GSK framework, enabling a multidimensional ranking of solvent candidates [73]. Its effectiveness has been experimentally validated for APIs such as paracetamol and meloxicam [73].

Experimental Protocols and Case Studies in Hazard Reduction

Methodology for Comparative Greenness Assessment

Implementing a robust experimental protocol for comparing solvents using GSSTs is crucial for validating their effectiveness in hazard reduction. The following workflow, derived from the methodologies of the tools discussed, provides a generalizable approach:

• Problem Definition: Identify the hazardous solvent to be replaced and define the key functional requirements for the alternative (e.g., solubility power for a specific API, boiling point for separation, polarity for reaction kinetics) [68] [73].
• Tool-Based Screening: Use one or more GSSTs (e.g., CHEM21 guide, GEARS, or SolECOs) to generate a shortlist of potential alternative solvents. The screening should be based on the pre-defined assessment parameters (EHS, LCA, cost, etc.) [68] [71] [73].
• Performance Verification: For the shortlisted solvents, verify their technical performance. This involves:
  • Solubility Prediction/Measurement: Use machine learning models (as in SolECOs) or experimental methods to determine the solubility of the target compound in the alternative solvents [73].
  • Process Compatibility: Assess the solvent's compatibility with other process parameters, such as temperature stability and miscibility with other streams [68].
• Holistic Scoring and Ranking: Calculate a final score for each alternative. For instance, using the GEARS framework, scores for toxicity, biodegradability, renewability, etc., are summed. In SolECOs, LCA indicators and the GSK framework are used for multidimensional ranking [68] [73].
• Experimental Validation: Conduct lab-scale experiments to validate the performance of the top-ranked solvent(s). This includes crystallization yield and purity assessment, reaction efficiency testing, or other relevant performance metrics [73].
• Lifecycle and Economic Impact Analysis: Perform a final review of the selected solvent's full lifecycle impact and cost implications for the process to ensure overall sustainability and economic viability [68] [66].

Case Study: Substitution of Benzene and Diethyl Ether

Case studies demonstrate the practical application of these frameworks. The machine learning assessment of 10,189 solvents successfully identified greener alternatives for benzene and diethyl ether, with predictions aligning well with known substitutes [29]. For instance, benzene (a highly hazardous and known carcinogen) can be replaced by toluene or anisole in certain applications. However, advanced tools like GEARS provide a more nuanced evaluation, revealing that while toluene is an improvement, it is still "problematic" due to suspicions of developmental toxicity and organ damage, whereas anisole is often "recommended" [69] [66].

Another case study applying the GEARS metric evaluated methanol, ethanol, acetonitrile, benzene, and glycerol [68]. The results highlighted ethanol's strong performance due to its combination of low toxicity, excellent biodegradability, high renewability (from biomass), and good recyclability. In contrast, benzene scored poorly across nearly all parameters, particularly toxicity and environmental impact, confirming its status as a solvent to be avoided [68]. This quantitative, multi-parameter comparison provides a compelling, data-driven argument for solvent substitution.

The Scientist's Toolkit: Essential Research Reagents and Materials

The following table details key solvents and their functions in research and development, along with their typical greenness classification based on the consensus from the solvent selection guides. This serves as a quick reference for scientists seeking safer alternatives.

Table 3: Key Solvents and Their Functions in Research and Development

Solvent/Reagent	Primary Function	Greenness Consensus	Notes and Common Alternatives
Water [69]	Universal polar solvent; reaction medium	Recommended	The greenest solvent where applicable.
Ethanol (EtOH) [68] [69]	Polar protic solvent; extraction, crystallization	Recommended	Renewable, low toxicity. Often used in place of methanol.
Isopropanol (i-PrOH) [69]	Polar protic solvent; cleaning, crystallization	Recommended	Similar profile to ethanol.
Ethyl Acetate (EtOAc) [69]	Medium polarity solvent; extraction, chromatography	Recommended	Biodegradable ester. Alternative to chlorinated solvents.
2-Methyltetrahydrofuran (2-MeTHF) [69]	Ether solvent; water-immiscible reaction medium	Problematic	Bio-derived; less hazardous than THF but has controversies.
Toluene [69]	Non-polar solvent; organic synthesis	Problematic	Replacement for benzene; but still suspected reprotoxin.
Acetonitrile [69]	Polar aprotic solvent; chromatography, synthesis	Problematic	High performance in HPLC; but toxic and high environmental impact.
N,N-Dimethylformamide (DMF) [69]	Polar aprotic solvent; powerful solubilizer	Hazardous	Reprotoxic; alternatives include Cyrene (dihydrolevoglucosenone) [66].
N-Methyl-2-pyrrolidone (NMP) [69]	Polar aprotic solvent; powerful solubilizer	Hazardous	Reprotoxic; subject to REACH restrictions [66].
Dichloromethane (DCM) [69] [66]	Volatile polar solvent; extraction, reaction medium	Hazardous	Likely carcinogen; ozone-depleting. Alternatives: EtOAc, 2-MeTHF.
Hexane [69]	Non-polar solvent; extraction	Hazardous	Neurotoxic; heptane is a slightly safer hydrocarbon.
Diethyl Ether [69]	Ether solvent; extraction, reaction medium	Highly Hazardous	Highly flammable, peroxide former.
Benzene [69]	Non-polar solvent; historical use in synthesis	Highly Hazardous	Known human carcinogen; avoid entirely.

The landscape of Green Solvent Selection Tools is rich and varied, offering frameworks suitable for different needs, from the simple, user-friendly categorizations of Pfizer's guide to the comprehensive, data-driven assessments of GEARS and SolECOs [68] [73]. A clear trend is the move towards integrating Life Cycle Assessment and machine learning to provide more holistic and predictive evaluations that go beyond simple EHS profiling [68] [29] [73]. For researchers and drug development professionals, the key to successful hazard reduction lies in leveraging these tools not in isolation but as a complementary suite. Starting with a consensus guide like CHEM21 can provide quick guidance, while employing advanced platforms like SolECOs can optimize solvent choice for specific, critical applications like API crystallization. The consistent message across all frameworks is that universal solvents do not exist, and the "greenness" of a solvent is inherently tied to the specific process context. However, by systematically applying these GSSTs, the scientific community can significantly accelerate the adoption of safer, more sustainable solvents, thereby minimizing environmental impact and enhancing workplace safety.

The growing process of industrialization has underscored the need for more sustainable practices across all scientific fields [74]. In the life sciences, particularly in drug development and clinical diagnostics, miniaturization and automation have emerged as powerful strategies to reduce environmental impact. These approaches align directly with the principles of Green Chemistry, which aim to minimize or eliminate the use of hazardous substances and reduce waste generation [75] [74]. Modern laboratories are increasingly adopting these technologies not only to enhance efficiency and reproducibility but also to address pressing environmental concerns, including the massive plastic waste problem—with the average biology lab producing approximately 4000 kg of plastic waste annually [76]. This guide provides a comparative assessment of miniaturization and automation technologies, evaluating their performance in reducing reagent consumption and waste generation while maintaining experimental integrity.

Core Technologies and Their Characteristics

The following table summarizes the primary technologies enabling greener laboratory practices through miniaturization and automation:

Technology	Key Mechanism	Volume Range	Primary Sustainability Benefits
Acoustic Liquid Handling [76] [77]	Uses sound waves to transfer droplets without physical contact.	Nanoliter (nL) range	Tip-free operation reduces plastic waste; minimal dead volume reduces reagent consumption.
Microfluidics / Lab-on-a-Chip [78]	Manipulates fluids in microfabricated channels.	Microliter (μL) to picoliter (pL)	Extreme miniaturization of reaction volumes; high-throughput with minimal sample.
Automated Liquid Handling Robots [79] [80]	Employs robotic arms and pipettors for liquid transfer.	Microliter (μL) to milliliter (mL)	High precision reduces errors and reagent waste; suitable for a wide range of applications.
Contactless Dispensing (e.g., Air Pressure) [76]	Uses pressure pulses to eject liquid without a tip.	Nanoliter (nL) to microliter (μL)	Eliminates pipette tips, reducing plastic waste; avoids cross-contamination.

The Scientist's Toolkit: Key Research Reagent Solutions

When implementing miniaturized and automated workflows, the choice of reagents and materials is crucial. The table below details essential components and their functions in sustainable experimental design.

Item	Function in Miniaturized/Automated Workflows
Low-Volume Plates (384-, 1536-well) [81]	Enables dramatic reagent reduction by hosting reactions in much smaller volumes than standard 96-well plates.
Acoustic-Compatible Source Plates [77]	Specially designed plates that facilitate the efficient and precise transfer of nanoliter droplets via acoustic energy.
Miniaturized Assay Kits [81]	Reagents optimized and validated for use at significantly reduced reaction volumes, ensuring performance is not compromised.
Concentrated Reagents/Stocks [81]	High-concentration solutions are essential for accurately dispensing minute, nanoliter-scale volumes of reagents.

Quantitative Performance Comparison

Adopting miniaturization and automation technologies leads to significant, quantifiable improvements in sustainability and cost-effectiveness. The data below, drawn from case studies and market analyses, highlights these benefits.

Sustainability and Cost Impact Table

Experiment / Workflow	Traditional Volume	Miniaturized Volume	Reduction in Reagent Use / Cost	Key Waste Reduction
Golden Gate DNA Assembly [77]	10-25 μL	1 μL	~90-96% reduction in reaction volume	Tip-free acoustic dispensing eliminates plastic waste
RNA Sequencing (NGS) [76] [81]	Standard manufacturer volume	1/10th scale	86% cost savings reported	Reduced consumption of plastic tips and plates
High-Throughput Screening [81]	50-100 μL per well	4-10 μL per well	Use of expensive reagents reduced by up to 10x	Less plastic waste and hazardous chemical waste
Genomics Lab (NGS Library Prep) [80]	Manual methods	Automated liquid handling	18% lower per-sample cost	Reduced tip consumption and failed runs (error drop from 4.5% to 1%)

Detailed Experimental Protocols

Protocol 1: Miniaturized Golden Gate DNA Assembly via Acoustic Dispensing

This protocol demonstrates how a common molecular biology technique can be scaled down for significant reagent savings and waste reduction [77].

Methodology:

• Plate Setup: In an acoustic-compatible source plate, prepare all reaction components, including the DNA fragments (insert and vector), Golden Gate enzyme mix (e.g., Type IIS restriction enzyme and ligase), and reaction buffer.
• Reaction Miniaturization: Using an acoustic liquid handler, transfer nanoliter volumes of each component from the source plate to a 384-well target plate. The total reaction volume is scaled down to 1 μL.
• Reaction Assembly: The acoustic dispenser combines the reagents in the target well without physical contact, ensuring no carryover or cross-contamination.
• Incubation: Seal the target plate and incubate in a thermal cycler using the standard cycling conditions for Golden Gate assembly (e.g., a cycle of digestion and ligation, followed by a final enzyme inactivation step).
• Transformation: Use the entire 1 μL reaction volume to transform competent E. coli cells.

The workflow for this miniaturized, tip-free protocol is illustrated below.

Protocol 2: Miniaturized High-Throughput Screening (HTS) Cell-Based Assay

This protocol leverages non-contact dispensing to enable ultra-miniaturized screening of compound libraries [76] [81].

Methodology:

• Cell and Reagent Preparation: Prepare cell suspension and compound libraries in source plates compatible with a non-contact dispenser.
• Miniaturized Cell Seeding: Using a contactless liquid handler (e.g., acoustic or air pressure-based), dispense a 4 nL droplet of cell suspension directly into a 1536-well assay plate. The system's integrated volume verification ensures precision.
• Compound Addition: Following cell adhesion, use the same dispenser to transfer nanoliter volumes of compounds from the library source plate to the assay plate. The tip-free technology eliminates the need for hundreds of disposable pipette tips.
• Incubation and Assay Readout: Incubate the plate under standard conditions and proceed with the assay steps (e.g., addition of a detection reagent, if needed, via the same dispenser). Finally, read the assay using a compatible plate reader.
• Data Analysis: Analyze the results. The miniaturized format allows for a dramatic increase in throughput while using a fraction of the cells and compounds required in a 96- or 384-well format.

The logical flow of this miniaturized screening process is as follows.

Comparative Greenness Assessment

The "greenness" of a laboratory technology can be assessed by its performance across multiple environmental and operational metrics. The following diagram synthesizes the decision-making process for evaluating these technologies based on key criteria such as waste generation, reagent consumption, and energy use. This framework allows for a holistic comparative assessment, which is central to the thesis context of this guide.

Application in Drug Development

The push for sustainability is actively reshaping drug development. At recent industry conferences like ELRIG 2025, sustainability has become a strategic priority, with speakers highlighting practical changes such as adopting acoustic dispensing to reduce solvent volumes and using higher plate formats to minimize plastic waste [82]. These shifts are not merely procedural but represent a fundamental integration of green principles into scientific decision-making. The use of Design of Experiment (DoE) is also being emphasized as a process-driven technology to embed sustainability into assay design from the outset, allowing researchers to systematically reduce waste and eliminate harmful reagents [82]. This industry-wide movement demonstrates that the comparative greenness of different technologies is now a key factor in protocol selection and laboratory instrumentation purchases.

In the pursuit of industrial sustainability, optimizing operational parameters and process duration presents a significant opportunity for enhancing energy efficiency. Fine grinding processes and the operation of heating, ventilation, and air conditioning (HVAC) systems in critical infrastructure are notably energy-intensive. This guide objectively compares the performance of various optimization strategies and control algorithms applied to these systems, drawing on direct experimental evidence. The analysis is framed within the broader context of comparative greenness assessment case studies, providing researchers and drug development professionals with actionable data for improving the environmental footprint of laboratory and industrial processes.

Comparative Analysis of Energy Efficiency Optimization Strategies

The table below summarizes quantitative performance data from experimental studies on optimizing stirred ball mills and base station cooling systems.

Table 1: Comparative Energy Efficiency Performance of Optimization Strategies

System Optimized	Key Parameters Adjusted	Optimization Algorithm/Method	Experimental Outcome	Energy Efficiency Improvement
Stirred Ball Mill (Copper Ore) [83]	Grinding Time, Stirrer Speed, Solid Concentration	Parameter Sweep & Model Fitting	Achieved 100% ~1 μm particles	~22% energy savings via parameter optimization [83]
Stirred Ball Mill (Calcite) [83]	Stirrer Speed, Solid Concentration	Parameter Optimization	Achieved P50 of 0.3 μm	High energy input of 1340 kWh/t [83]
5G Base Station Cooling [84]	Evaporator/Condenser Fan Speed, Compressor Frequency	Genetic Algorithm (GA) & Linear Fitting	Validated across five climate zones in China	Annual Cooling Load Factor (CLF) as low as 0.061 [84]
Parallel Pumping System [85]	Pump Speeds, Valve Settings (Throttling, Bypass)	Gravitational Search Algorithm (GSA)	Optimization under five given loads	Minimizing power consumption was the most stable and energy-saving strategy [85]

Detailed Experimental Protocols and Methodologies

Protocol for Stirred Ball Mill Optimization

This protocol is adapted from the fine grinding experiments performed on Egyptian copper ore [83].

• Apparatus: A laboratory-scale Stirred Mill (Attritor) from Union Process with a 9.5 L tank and a working capacity of 4.2 L was used. The mill features a stainless-steel shaft with five adjustable arms, a variable speed drive, and instrumentation to display impeller speed (rpm), motor frequency (Hz), and power draw (kW) [83].
• Materials: The mill feed was copper ore with a density of 2.9 g/cm³. The grinding media consisted of 3 mm diameter alumina balls. The process was conducted under wet conditions [83].
• Experimental Procedure & Parameters:
  • Slurry Preparation: The solid ore is mixed with water to achieve the target solid concentration (e.g., 33.3%).
  • Parameter Variation: For each experimental run, key parameters are systematically varied:
    • Grinding Time: Tested over a range, up to 17 hours.
    • Stirrer Speed: Adjusted as revolutions per minute (rpm), with a maximum of 500 rpm.
    • Solid Concentration: Varied as a mass percentage (e.g., 33.3%).
  • Operation: The mill chamber is charged with the slurry and grinding media. The mill is operated at the set parameters for the designated duration.
  • Data Collection: The power draw is monitored throughout the process. After the run, the product is discharged and sampled for particle size analysis to determine the Particle Size Distribution (PSD) [83].
• Optimization Method: The effects of the variable parameters on the specific energy input (kWh/t) and the resulting PSD are analyzed. The PSD of the ground products is simulated using models like the Gates-Gaudin-Schuhmann (GGS) model and the Rosin-Rammler-Benne (RRB) function to identify the parameter set that achieves the target particle size with minimal energy consumption [83].

Protocol for Integrated Heat Pipe Cooling System Optimization

This protocol is derived from the experimental validation of a cabinet-level cooling solution for 5G base stations [84].

• Apparatus: An integrated heat pipe cooling system is installed, comprising an indoor unit (with a fan and evaporator/heat-exchange backplane) and an outdoor unit (with a condenser and fan), connected by copper pipes. The experiment is conducted in an enthalpy difference laboratory, which uses two sealed insulating spaces to simulate indoor and outdoor environments [84].
• Experimental Procedure & Parameters:
  • System Commissioning: The cooling system is installed, and its pressure and refrigerant charge are checked.
  • Load and Environment Simulation: The indoor space is subjected to a thermal load (e.g., 6000 W partial load, 10000 W full load). The outdoor space temperature is controlled to simulate various ambient conditions [84].
  • Parameter Adjustment: The key control parameters are dynamically adjusted:
    • Evaporator fan speed
    • Condenser fan speed
    • Compressor frequency
  • Data Collection: The total energy consumption of the cooling system and the indoor temperature are recorded for each parameter set.
• Optimization Method: A Genetic Algorithm (GA) framework is first used to find the parameter combinations that minimize total energy consumption while maintaining the indoor temperature within constraints. Due to the unattended nature of base stations, the complex GA results are then simplified into a linear fitting approach. This simplified control strategy is embedded into a single-chip microcomputer controller for real-time, on-site energy efficiency optimization [84].

Visualization of Optimization Workflows

The following diagrams illustrate the logical workflows for the two primary optimization methodologies discussed.

Stirred Mill Parameter Optimization

Genetic Algorithm Control Optimization

The Scientist's Toolkit: Key Research Reagent Solutions

The table below details essential materials and components used in the featured energy optimization experiments.

Table 2: Essential Materials and Components for Featured Experiments

Item Name	Function / Relevance	Application Context
Alumina Grinding Balls	Media for attrition and abrasion-based particle breakage.	Stirred ball mill grinding of ores like copper and calcite [83].
Refrigerant (in Heat Pipes)	Working fluid that transports heat via phase change.	Integrated heat pipe cooling systems for 5G base stations and data centers [84].
Variable Speed Drive (VSD)	Electronically controls motor speed and torque.	Enables optimization of pump, fan, and stirrer speeds for energy savings [85].
IoT Sensors & Smart Meters	Collects real-time data on energy consumption, temperature, and equipment status.	Foundational for data acquisition in modern energy management systems [86].
Digital Twin Model	A virtual replica of a physical system used for simulation and optimization.	Allows for testing optimization strategies without disrupting real-world operations [87].

In modern analytical chemistry, sample preparation is a critical step that significantly influences the environmental footprint of an entire analytical procedure. The principles of Green Analytical Chemistry (GAC) and Green Sample Preparation (GSP) have driven the development of more sustainable laboratory practices [88] [89]. To quantitatively evaluate and measure the environmental impact of sample preparation methods, several metric tools have been established, with the Analytical Greenness Metric for Sample Preparation (AGREEprep) emerging as a particularly significant and user-friendly tool since its introduction in 2022 [90] [27].

AGREEprep is specifically designed to assess the sample preparation stage based on the 10 principles of green sample preparation [88] [90]. This metric tool uses a weighted scoring system across these ten criteria, generating a final score between 0 and 1 (where 1 represents ideal greenness) accompanied by an intuitive pictogram [91] [27]. The assessment covers crucial aspects such as waste generation, energy consumption, operator safety, use of safer solvents and reagents, and integration of operational steps [88]. This article provides a comprehensive comparison of various microextraction techniques through the lens of AGREEprep scores, offering researchers objective data to select environmentally sustainable sample preparation methods.

Microextraction techniques represent a paradigm shift from conventional sample preparation methods by dramatically reducing solvent consumption, minimizing waste generation, and integrating procedures to save time and energy. These techniques can be broadly classified into two main categories: solid-phase microextraction (SPME) and liquid-phase microextraction (LPME) [88].

Solid-phase microextraction encompasses several approaches where analytes are extracted onto a solid sorbent phase. These include fiber SPME, in-tube SPME, pipette-tip SPE, μ-SPE, microextraction by packed sorbent (MEPS), stir bar sorptive extraction (SBSE), fabric-phase sorptive extraction (FPSE), thin-film microextraction (TFME), and magnetic SPE (MSPE) [88]. SPME techniques are particularly valued for their sensitivity, efficiency, speed, versatility, and economy, making them preferred over traditional extraction methods like Simultaneous Distillation Extraction (SDE) and Solvent-Assisted Flavor Evaporation (SAFE) [91].

Liquid-phase microextraction techniques utilize minimal volumes of liquid solvents for extraction and include methods such as single-drop microextraction (SDME), hollow fiber LPME, and dispersive liquid-liquid microextraction (DLLME) [88]. A key advancement in this area involves replacing traditional organic solvents with greener alternatives like deep eutectic solvents (DESs) and ionic liquids (ILs), which offer improved biodegradability and reduced toxicity profiles [92] [93].

The fundamental advantage shared by all microextraction techniques is their miniaturized nature, which aligns perfectly with the principles of green analytical chemistry by reducing consumption of samples, solvents, and materials while minimizing waste generation [88] [89].

AGREEprep Metric Tool: Principles and Operation

The AGREEprep metric tool operates on a standardized framework for evaluating sample preparation methods. The assessment is based on ten core principles that correspond to the ten criteria used for scoring [88] [90]:

• Favoring in situ sample preparation
• Using safer solvents and reagents
• Targeting sustainable, reusable, and renewable materials
• Minimizing waste generation
• Minimizing sample, chemical, and material amounts
• Maximizing sample throughput
• Integrating steps and promoting automation
• Minimizing energy consumption
• Choosing the greenest possible post-sample preparation configuration for analysis
• Ensuring safe procedures for the operator

Each criterion receives a sub-score between 0 and 1, with the final overall score calculated as a weighted sum of these subscores [90]. The software allows users to adjust the weight of each criterion based on their specific analytical goals, though default weights are typically used for standardized assessments [88]. The output is an easily interpretable pictogram that displays both the numerical score and a color code (ranging from red for poor performance to green for excellent performance), providing an at-a-glance assessment of the method's environmental impact [91] [27].

For researchers performing assessments, the free AGREEprep software is accessible online at https://mostwiedzy.pl/AGREE, offering a user-friendly platform for inputting method parameters and generating comprehensive greenness evaluations [27].

Comparative AGREEprep Scores of Microextraction Techniques

Comprehensive Comparison Table

The following table summarizes AGREEprep scores for various microextraction techniques as reported in recent literature, providing a quantitative basis for comparing their environmental performance.

Table 1: AGREEprep Scores of Microextraction Techniques Across Different Applications

Microextraction Technique	Analytical Context	AGREEprep Score	Key Greenness Strengths	Reference
Dynamic HF-LPME-HPLC-UV	UV filter analysis in cosmetics	0.82	High score attributed to miniaturization and reduced solvent consumption	[27]
US-VA-DLLME	UV filter analysis in cosmetics	0.80	Ultrasound and vortex assistance reducing energy consumption	[27]
Dispersive Solid-Phase Microextraction (DSPME)	UV filter analysis in cosmetics	0.78	Minimal reagent requirements and simplified procedures	[27]
Micro-MSPD	UV filter analysis in cosmetics	0.75	Combined microextraction with dispersive solid-phase extraction	[27]
MEPS	UV filter analysis in cosmetics	0.72	Miniaturized packed sorbent with reusability	[27]
SPME (Method 34)	Flavor compound analysis in foods	0.66	Safe solvents, minimized waste, high throughput, low energy	[91]
SPME (Method 7)	Flavor compound analysis in foods	0.64	Miniaturization, fewer steps, low energy consumption	[91]
Single-Drop Microextraction (SDME)	Nitro compounds in water samples	0.61	Minimal solvent volume (single microdrop)	[93]

Analysis of Score Trends

The data reveals that liquid-phase microextraction techniques generally achieve high AGREEprep scores, with methods like dynamic HF-LPME and US-VA-DLLME scoring above 0.80 in cosmetic analysis [27]. These high scores reflect advantages in multiple greenness criteria, particularly minimal solvent consumption, reduced waste generation, and operational integration.

Solid-phase microextraction methods also demonstrate strong environmental profiles, with scores typically ranging from 0.64 to 0.75 [91] [27]. The specific design and implementation of each SPME method significantly influences its score, with factors such as sorbent reusability, automation potential, and energy requirements playing crucial roles in the final assessment.

It is important to note that AGREEprep scores are context-dependent, and the same technique may yield different scores when applied in different analytical scenarios due to variations in solvents, sample types, or operational parameters [88] [27]. Nevertheless, the consistent theme across all high-scoring methods is their adherence to the core principles of green sample preparation through miniaturization, waste reduction, and integration of analytical steps [88].

Detailed Experimental Protocols for High-Scoring Techniques

Dynamic Hollow-Fiber Liquid-Phase Microextraction (HF-LPME)

Dynamic HF-LPME achieved one of the highest AGREEprep scores (0.82) for UV filter analysis in cosmetics [27]. The experimental protocol typically involves these critical stages:

• Device Setup: A porous hollow fiber membrane (usually polypropylene) is used as a support for the organic solvent. The fiber pores are impregnated with an appropriate water-immiscible solvent, creating a protected liquid membrane.
• Sample Preparation: Cosmetic samples (approximately 0.5 g) are diluted with ultrapure water and placed into the donor compartment. The pH may be adjusted to ensure analytes are in their uncharged form.
• Extraction Process: The hollow fiber is immersed in the sample solution, and the acceptor phase (typically an aqueous solution with different pH) is filled inside the fiber lumen. Using a syringe pump, the acceptor phase is repeatedly withdrawn and pushed back through the fiber, creating dynamic movement that enhances extraction efficiency.
• Analysis: After a prescribed extraction time (usually 15-30 minutes), the acceptor phase is collected and directly injected into an HPLC system for analysis [27].

The greenness advantages of this method include minimal solvent consumption (only a few microliters for membrane impregnation), no solvent evaporation step required, reduced exposure to hazardous solvents for operators, and compatibility with green analytical techniques [27].

Ultrasound-Vortex-Assisted Dispersive Liquid-Liquid Microextraction (US-VA-DLLME)

US-VA-DLLME, with an AGREEprep score of 0.80, employs energy-assisted dispersion to improve extraction efficiency while maintaining green characteristics [27]:

• Solvent Selection: A green extraction solvent with higher density than water (such as certain deep eutectic solvents) is selected, along with a minimal volume of dispersive solvent if needed.
• Extraction Procedure: In a conical test tube, the cosmetic sample (approximately 1.0 g) is dissolved in ultrapure water. The extraction solvent (typically 50-100 μL) is rapidly injected into the sample solution.
• Assisted Dispersion: The mixture is subjected to vortex mixing (1-2 minutes) combined with ultrasound assistance (30-60 seconds) to form a fine dispersion of the extraction solvent.
• Phase Separation: Centrifugation at 4000-5000 rpm for 5 minutes separates the phases, with the sedimented extraction phase collected at the bottom of the tube.
• Analysis: A small aliquot of the extracted phase is collected using a microsyringe and transferred for chromatographic analysis [27].

This method's greenness derives from its very low solvent consumption, reduced extraction time due to energy assistance, minimal waste generation, and high enrichment factors that improve detection limits [27].

Solid-Phase Microextraction (SPME) for Flavor Analysis

The high-scoring SPME method (0.66) for flavor analysis employs the following protocol [91]:

• Fiber Selection: A SPME fiber with an appropriate stationary phase coating (e.g., polydimethylsiloxane/divinylbenzene for volatiles) is selected based on the target flavor compounds.
• Sample Preparation: Food samples (1-2 g) are placed in headspace vials, possibly with the addition of internal standards and salt to modify ionic strength.
• Extraction: The SPME fiber is exposed to the sample headspace (or directly immersed) for a specified time (10-30 minutes) at a controlled temperature with constant agitation.
• Desorption: After extraction, the fiber is retracted and transferred to the GC injector port, where thermal desorption (typically 250-280°C for 2-5 minutes) releases the analytes into the chromatographic system [91].

The green advantages include solventless operation, reusability of SPME fibers (50-100 extractions typically), minimal sample requirements, and easy automation potential [91].

The AGREEprep Assessment Framework

The following diagram illustrates the ten fundamental principles of the AGREEprep metric tool and their interrelationships in evaluating the greenness of sample preparation methods.

AGREEprep Assessment Principles Framework

This framework visually represents how each of the ten green sample preparation principles contributes collectively to the final AGREEprep score, highlighting the comprehensive nature of this assessment tool.

Advanced Green Solvents in Microextraction

The incorporation of green solvents represents a significant advancement in improving the AGREEprep scores of microextraction techniques. These solvents directly enhance performance in multiple AGREEprep criteria, particularly principle #2 (using safer solvents and reagents) and principle #4 (minimizing waste) [92].

Table 2: Green Solvents in Microextraction Techniques

Green Solvent Category	Key Characteristics	Compatible Microextraction Techniques	Environmental Advantages
Deep Eutectic Solvents (DESs)	Biodegradable, low toxicity, tunable properties	LPME, DLLME, SDME	Higher biodegradability, reduced ecotoxicity, from natural sources	[92] [93]
Ionic Liquids (ILs)	Negligible vapor pressure, high thermal stability, designable structures	SPME, HF-LPME	Reduced solvent evaporation, reusable, high extraction efficiency	[92]
Switchable Solvents (SSs)	Reversible physicochemical properties in response to stimuli	DLLME, LPME	Facilitate recovery and reuse, minimizing waste generation	[94]
Supramolecular Solvents (SUPRASs)	Nano-structured liquids with multiple binding sites	DLLME, LPME	Self-assembled from natural ingredients, biodegradable	[93] [94]
Bio-Based Solvents	Derived from renewable biomass resources	LPME, SDME, DSPME	Reduced fossil fuel dependence, often lower toxicity	[94]

Research indicates that DES-based LPME techniques often provide stronger enrichment factors coupled with lower environmental impacts, while IL-based SPME approaches demonstrate high selectivity and tunable sorbent-analyte interactions [92]. The strategic implementation of these green solvents directly contributes to higher AGREEprep scores by addressing multiple green chemistry principles simultaneously.

Research Reagent Solutions for Green Microextraction

Table 3: Essential Reagents and Materials for Green Microextraction

Reagent/Material	Function in Microextraction	Green Attributes	Application Examples
Deep Eutectic Solvents	Extraction phase in LPME	Low toxicity, biodegradable, renewable sources	Pharmaceutical analysis in biological samples	[92]
Ionic Liquids	Sorbent coatings in SPME	Tunable selectivity, negligible vapor pressure	Selective extraction of pharmaceuticals	[92]
Polymeric Sorbents	Extraction phase in SPME	Reusability, chemical stability	Fiber SPME, in-tube SPME	[88] [95]
Hollow Fiber Membranes	Support for solvent in HF-LPME	Disposable, minimal solvent requirement	Sample cleanup and pre-concentration	[88] [27]
Magnetic Nanoparticles	Sorbent in magnetic SPE	Rapid separation, reusability	Dispersive microextraction approaches	[88]
Switchable Solvents	Extraction phase in DLLME	Stimuli-responsive recovery	Environmentally tunable separations	[94]

This comprehensive comparison of microextraction techniques through the standardized assessment of AGREEprep scores provides clear, quantitative evidence of their environmental performance. The data demonstrates that microextraction techniques consistently achieve favorable AGREEprep scores (typically ranging from 0.61 to 0.82), confirming their significant advantages over traditional sample preparation methods in terms of environmental sustainability [88] [91] [27].

Among the various techniques evaluated, liquid-phase microextraction methods such as dynamic HF-LPME and US-VA-DLLME achieve the highest scores, benefiting from their minimal solvent consumption, reduced waste generation, and operational efficiency [27]. The integration of green solvents, particularly deep eutectic solvents and ionic liquids, further enhances the environmental profile of these methods while maintaining or even improving analytical performance [92] [93].

For researchers and analytical method developers, the AGREEprep metric tool offers a scientifically rigorous approach to quantify and compare the environmental impact of sample preparation methods, enabling more informed decisions that align with the principles of green analytical chemistry. The continued development and optimization of microextraction techniques, coupled with their validation through standardized greenness assessment tools, represents a crucial pathway toward more sustainable analytical practices in research and industrial applications.

The field of analytical chemistry is undergoing a fundamental paradigm shift to align with sustainability science. This transformation requires carefully balancing traditional analytical performance with environmental considerations. While analytical chemistry plays a crucial role in determining the composition and quantity of matter, its reliance on energy-intensive processes, non-renewable resources, and waste generation raises significant environmental concerns [21]. For researchers and drug development professionals, this creates a complex challenge: maintaining the rigorous analytical performance required for pharmaceutical applications while minimizing environmental impact.

The contemporary understanding of sustainability in analytical science extends beyond simple "greenness" to incorporate a triple bottom line approach that balances economic, social, and environmental pillars [21]. This framework recognizes that sustainability is not just about efficiently using resources and reducing waste, but also about ensuring economic stability and fostering social well-being. Within this context, a new comprehensive assessment framework has emerged—White Analytical Chemistry (WAC)—which strengthens traditional Green Analytical Chemistry (GAC) by adding criteria that evaluate both performance and practical usability [6].

This comparison guide examines the tools, methodologies, and practical strategies that enable scientists to navigate the critical trade-offs between greenness and analytical performance in pharmaceutical research and development.

Assessment Frameworks: From Green to White Analytical Chemistry

The White Analytical Chemistry (WAC) Framework

White Analytical Chemistry represents a significant evolution beyond traditional green assessment approaches. WAC employs a color-coded RGB model that integrates three equally important dimensions [6]:

• Green component: Incorporates traditional Green Analytical Chemistry metrics focused on environmental impact
• Red component: Represents analytical performance criteria including accuracy, sensitivity, and precision
• Blue component: Addresses economic and practical aspects such as cost, time, and usability

According to this framework, a "whiter" method achieves an optimal balance between all three attributes, making it better suited for practical application while maintaining environmental responsibility [17]. This holistic approach acknowledges that an environmentally friendly method is useless if it lacks the analytical performance required for reliable results, just as a high-performing method is unsustainable if its environmental impact is excessive.

Specialized Assessment Tools and Metrics

Several specialized tools have been developed to quantify and visualize the different dimensions of analytical method sustainability:

Table 1: Analytical Method Assessment Tools

Tool Name	Focus Area	Assessment Output	Key Criteria Evaluated
Red Analytical Performance Index (RAPI) [17]	Analytical Performance (Red)	Score (0-100) and star pictogram	Repeatability, intermediate precision, selectivity, calibration, sensitivity, accuracy, recovery, robustness, linearity, productivity
Blue Applicability Grade Index (BAGI) [17]	Practicality & Economics (Blue)	Score (25-100) and star pictogram	Cost, time, operational simplicity, health & safety, sample throughput, energy consumption, analytical potential, hyphenation, automation, waste management
AGREEprep [21]	Green Sample Preparation	Score (0-1) and pictogram	Sample preparation environmental impact metrics
ComplexGAPI [6]	Comprehensive Greenness	Pictogram	Holistic environmental impact assessment

The Red Analytical Performance Index (RAPI) software provides user-friendly assessment of analytical methods against ten validation parameters guided by ICH recommendations, generating a visual star-like pictogram where higher scores (darker red colors) indicate superior analytical performance [17]. This tool complements the Blue Applicability Grade Index (BAGI), which focuses on practical and economic factors [17].

Together, these tools enable researchers to systematically evaluate methods across all three WAC dimensions, facilitating informed decisions that balance environmental concerns with analytical requirements.

Experimental Protocols for Comparative Assessment

Greenness Assessment Protocol Using AGREEprep

The AGREEprep metric provides a standardized approach for evaluating the environmental impact of sample preparation methods [21]. The experimental protocol involves:

• Method Characterization: Document all components of the sample preparation process, including solvents, reagents, equipment, energy consumption, and waste generation.

• Data Input: Enter the characterized parameters into the AGREEprep software tool, which calculates scores across multiple environmental impact categories.

• Pictogram Generation: The tool generates a visual output with an overall score between 0 and 1, where 1 represents the highest possible greenness.

• Comparative Analysis: Compare scores across different methods to identify opportunities for improving environmental performance.

A recent study applying AGREEprep to 174 standard methods from CEN, ISO, and Pharmacopoeias revealed that 67% of methods scored below 0.2 on the 0-1 scale, demonstrating that many official methods still rely on resource-intensive and outdated techniques [21].

Analytical Performance Assessment Using RAPI

The Red Analytical Performance Index protocol provides systematic evaluation of analytical method robustness [17]:

• Method Validation: Conduct full validation of the analytical method according to ICH guidelines, documenting results for all relevant performance parameters.

• Parameter Scoring: For each of the ten RAPI criteria, assign scores (0, 2.5, 5.0, 7.5, or 10 points) based on predefined benchmarks:

  • Repeatability: Variation when measurements are performed by a single analyst using the same equipment
  • Intermediate precision: Variation across different days, analysts, or equipment
  • Selectivity/Specificity: Ability to measure analyte accurately in presence of interferences
  • Calibration and sensitivity: Detection limit, quantification limit, and sensitivity
  • Accuracy and Recovery: Agreement between measured and true values
  • Robustness: Capacity to remain unaffected by small methodological variations
  • Linearity: Ability to obtain results proportional to analyte concentration
  • Throughput: Number of samples processed per unit time

• Software Input: Enter scores into the open-source RAPI software, which automatically generates a color-coded star pictogram and overall performance score.

• Interpretation: Higher scores (darker red colors in the pictogram) indicate superior analytical performance across the evaluated criteria.

Integrated WAC Assessment Workflow

The relationship between different assessment frameworks and the complete evaluation workflow can be visualized as follows:

Integrated Method Assessment Workflow demonstrates the comprehensive evaluation process balancing green, red, and blue components.

Comparative Case Studies in Pharmaceutical Analysis

Stability-Indicating HPTLC Methods

Research applying WAC principles to stability-indicating High-Performance Thin-Layer Chromatography (HPTLC) methods for thiocolchicoside and aceclofenac demonstrates the framework's practical utility [6]. The study revealed that:

• Methods with excellent analytical performance (high red scores) sometimes utilized larger volumes of organic solvents, compromising greenness
• Greener alternatives with reduced solvent consumption occasionally showed minor compromises in precision or sensitivity
• The WAC-assisted Analytical Quality by Design (AQbD) approach enabled identification of method parameters that balanced all three dimensions

HPLC Method for Combination Drugs

A green RP-HPLC method developed for simultaneous determination of azilsartan, medoxomil, chlorthalidone, and cilnidipine in human plasma achieved an excellent white WAC score through systematic optimization [6]. Key success factors included:

• Solvent selection prioritizing less hazardous alternatives
• Method parameters optimized for minimal energy consumption
• Sample preparation designed to reduce waste generation
• Validation parameters meeting all ICH precision, accuracy, and sensitivity requirements

This case demonstrates that carefully designed methods can achieve both environmental goals and rigorous analytical performance required for pharmaceutical applications.

Quantitative Comparison of Analytical Approaches

Table 2: Performance Comparison of Analytical Method Categories

Method Category	Greenness Score (AGREEprep)	Performance Score (RAPI)	Practicality Score (BAGI)	Key Strengths	Common Limitations
Traditional HPLC Methods	0.15-0.30 [21]	85-95 [17]	70-85	Excellent sensitivity and precision; Well-established protocols	High solvent consumption; Energy intensive; Significant waste generation
Green HPLC Methods	0.50-0.75	80-90	75-85	Reduced solvent and energy use; Maintained performance	May require method development; Limited validation data
Automated Sample Preparation	0.60-0.80 [21]	75-90	85-95	High throughput; Reduced human error; Lower exposure risk	High initial investment; Complex maintenance
Miniaturized Systems	0.70-0.90	70-85	65-80	Minimal sample/solvent consumption; High greenness	Potential precision issues; Limited application scope

Implementation Strategies for Balancing Trade-offs

Green Sample Preparation Techniques

Adapting traditional sample preparation techniques to align with Green Sample Preparation principles involves several key strategies [21]:

• Accelerate sample preparation by applying vortex mixing or assisting fields (ultrasound, microwaves) to enhance extraction efficiency with significantly less energy
• Parallel processing of multiple samples using miniaturized systems to increase throughput and reduce energy consumed per sample
• Automate sample preparation to save time, lower reagent consumption, reduce waste, and minimize human intervention
• Integrate multiple preparation steps into single, continuous workflows to simplify operations while cutting resource use

These approaches demonstrate how thoughtful methodological design can simultaneously improve both greenness and practical efficiency (blue criteria) while maintaining analytical performance.

Addressing the "Rebound Effect"

A critical consideration in implementing greener analytical methods is the rebound effect, where efficiency gains lead to unintended consequences that offset environmental benefits [21]. For example:

• A novel, low-cost microextraction method using minimal solvents might lead laboratories to perform significantly more extractions, increasing total chemical usage
• Automation that saves time and enhances efficiency may result in over-testing, where analyses are performed more frequently than necessary

Mitigation strategies include [21]:

• Implementing testing protocols optimized to avoid redundant analyses
• Using predictive analytics to identify when tests are truly necessary
• Training laboratory personnel on rebound effect implications
• Establishing sustainability checkpoints in standard operating procedures

Research Reagent Solutions for Sustainable Analytics

Table 3: Essential Research Reagents and Solutions for Sustainable Analytical Chemistry

Reagent/Solution	Function	Green Alternatives	Performance Considerations
Acetonitrile (HPLC)	Mobile phase component	Ethanol, methanol, or water-based mobile phases	May affect separation efficiency; Require method redevelopment
Chlorinated Solvents	Extraction and cleaning	Bio-based solvents, ionic liquids, or surfactant solutions	Potential differences in extraction efficiency and selectivity
Derivatization Agents	Analyte detection enhancement	Miniaturized derivatization; Reduced reagent volumes	May impact method sensitivity and detection limits
Traditional Buffers	pH control and stability	Biodegradable buffers; Reduced concentration options	Potential effects on system compatibility and peak shape

Balancing greenness with analytical performance requires a fundamental shift from the traditional linear "take-make-dispose" model to a Circular Analytical Chemistry framework [21]. This transition faces two main challenges: the lack of clear direction toward greener practices, and coordination failures within the analytical chemistry community [21].

The implementation of White Analytical Chemistry, supported by tools like RAPI, BAGI, and AGREEprep, provides a structured approach to navigate these complex trade-offs. As the field evolves, key priorities include:

• Regulatory modernization to phase out outdated, resource-intensive standard methods
• Enhanced collaboration between industry, academia, and manufacturers to drive innovation
• Green financing models specifically dedicated to sustainable analytical chemistry innovations [6]
• Educational initiatives to train researchers in both traditional and sustainable analytical approaches

For drug development professionals and researchers, adopting these frameworks enables method selection and optimization that meets rigorous analytical requirements while advancing sustainability goals—a critical balance for the future of pharmaceutical science.

Benchmarking and Verification: Establishing Credibility in Greenness Claims

The adoption of Green Analytical Chemistry (GAC) principles has driven the development of numerous metric tools to evaluate the environmental impact of analytical methods. Among these, the National Environmental Methods Index (NEMI), Analytical Eco-Scale (AES), Analytical GREEnness (AGREE), and ChlorTox represent widely used assessment approaches with distinct structures and scoring mechanisms [96] [97]. This guide provides an objective comparison of these four tools, supported by experimental data from pharmaceutical analysis case studies, to help researchers understand their correlations, strengths, and limitations for comprehensive greenness assessment.

Tool Fundamentals: Principles and Mechanisms

Fundamental Characteristics of Assessment Tools

Tool	Assessment Basis	Scoring System	Output Format	Primary Focus
NEMI [96] [1]	4 binary criteria (PBT, hazardous, corrosive, waste)	Qualitative (pass/fail per criterion)	Pictogram with 4 colored quadrants	Reagent toxicity & waste quantity
AES [96] [97]	Penalty points for hazardous reagents, energy, waste	Semi-quantitative (base score 100 minus penalties)	Numerical score (higher = greener)	Operational hazards & energy use
AGREE [1] [98]	12 principles of GAC	Quantitative (0-1 scale)	Circular pictogram with numerical score	Comprehensive GAC principles
ChlorTox [97] [99]	Toxicity relative to chloroform	Quantitative (chloroform equivalents)	Numerical score (lower = greener)	Reagent toxicity profile

Theoretical Workflow for Multi-Metric Assessment

The following diagram illustrates the logical relationship and workflow when applying these four metrics in a comprehensive assessment.

Experimental Correlation: Pharmaceutical Case Studies

Case Study 1: HPTLC Analysis of Ertugliflozin

A direct comparison of normal-phase (NP) versus reversed-phase (RP) HPTLC methods for ertugliflozin quantification provides empirical correlation data across all four metrics [100].

Experimental Protocol:

• NP-HPTLC: Silica gel 60 NP-18F254S plates with chloroform/methanol (85:15 v/v) mobile phase
• RP-HPTLC: Silica gel 60 RP-18F254S plates with ethanol-water (80:20 v/v) mobile phase
• Detection: UV at 199 nm
• Linear Range: 50-600 ng/band (NP) and 25-1200 ng/band (RP)
• Greenness Assessment: Applied NEMI, AES, ChlorTox, and AGREE to both methods

Results Correlation:

Method	NEMI Profile	AES Score	ChlorTox (g)	AGREE Score	Overall Greenness
NP-HPTLC	2/4 green quadrants	67	1.42	0.61	Less green
RP-HPTLC	4/4 green quadrants	89	0.78	0.84	More green

Case Study 2: HPTLC Analysis of Lemborexant

A similar comparative study evaluating NP versus RP-HPTLC for lemborexant analysis demonstrates consistent correlation patterns across metrics [99].

Experimental Protocol:

• NP-HPTLC: Acetone-petroleum ether (40:60 v/v) developing system
• RP-HPTLC: Ethanol-water (85:15 v/v) developing system
• Detection: UV at 199 nm
• Linear Range: 50-500 ng/band (NP) and 20-1000 ng/band (RP)
• Greenness Assessment: Parallel application of all four metric tools

Results Correlation:

Method	NEMI Profile	AES Score	ChlorTox (g)	AGREE Score	Overall Greenness
NP-HPTLC	2/4 green quadrants	72	1.26	0.65	Less green
RP-HPTLC	4/4 green quadrants	93	0.88	0.89	More green

Metric Correlations: Comparative Analysis

Inter-Metric Correlation Patterns

The correlation between metric outcomes follows predictable patterns based on their underlying assessment focus:

• NEMI & ChlorTox: Strong correlation as both prioritize reagent toxicity, though NEMI uses binary assessment while ChlorTox provides quantitative toxicity measurement [99]
• AES & AGREE: Moderate correlation as both consider multiple GAC principles, though AES emphasizes operational factors while AGREE provides more comprehensive principle coverage [100]
• NEMI & AGREE: Weaker correlation as AGREE evaluates broader principles beyond reagent toxicity, including energy consumption and operator safety [1]

Scoring Pattern Visualization

The following diagram visualizes the consistent scoring patterns observed across the four metrics in the case studies, showing their relative assessment of method greenness.

Key Reagents and Materials for Greenness Assessment

Category	Specific Items	Function in Assessment	Green Preference
Chromatographic Plates [100] [99]	Silica gel 60 NP-18F254S, 60 RP-18F254S	Stationary phase for HPTLC analysis	RP generally greener than NP
Solvents [100] [99]	Chloroform, methanol, petroleum ether, ethanol, water	Mobile phase components	Ethanol-water > chloroform-methanol
Reference Standards [100] [99]	Ertugliflozin, lemborexant pure standards	Method validation & calibration	Minimal quantities required
Software Tools [1] [4]	AGREE calculator, BAGI software	Automated greenness scoring	Open access availability

Assessment Implementation Protocol

• Method Documentation: Record all reagents, quantities, energy consumption, and waste generation
• Sequential Application:
  • Apply NEMI based on safety data sheets and waste volume
  • Calculate AES penalty points (100 - Σ penalties)
  • Compute ChlorTox using chloroform equivalence
  • Generate AGREE score using 12 GAC principles
• Results Correlation: Identify consistent patterns and outliers across metrics
• Improvement Strategy: Target lowest-scoring areas for method optimization

The correlation of results across NEMI, AES, AGREE, and ChlorTox provides a robust framework for comprehensive greenness assessment. Experimental data from pharmaceutical analysis demonstrates consistent patterns where ethanol-water based RP-HPTLC methods consistently outperform chloroform-methanol based NP-HPTLC approaches across all metrics [100] [99]. While these tools show strong correlation in identifying greener methods, their complementary nature provides multidimensional assessment coverage—from specific toxicity profiling (ChlorTox) to comprehensive GAC principle evaluation (AGREE). Researchers should employ this multi-metric approach to validate greenness claims and drive sustainable method development in pharmaceutical analysis.

The International Council for Harmonisation (ICH) provides the essential framework for validating analytical procedures, ensuring that methods used in pharmaceutical development are reliable, sensitive, and precise. Performance verification is a critical regulatory requirement to guarantee that analytical data supporting drug identity, strength, quality, and purity is trustworthy. Within the modern laboratory, this verification process now extends beyond traditional performance parameters to include sustainability assessments, aligning with the growing emphasis on Green Analytical Chemistry (GAC). The ICH guidelines establish harmonized standards for method validation, requiring rigorous testing of key performance characteristics including accuracy, precision, specificity, detection limit, quantitation limit, linearity, and range.

The integration of greenness assessment into method verification represents an evolution in pharmaceutical analysis, where environmental impact and method efficiency join the traditional validation criteria. This dual focus ensures that methods are not only scientifically sound but also environmentally sustainable, reducing the use of hazardous chemicals and energy consumption while maintaining regulatory compliance. This guide explores how different analytical methods compare across these critical dimensions, providing a framework for scientists to select optimal methods that meet both technical and sustainability requirements.

Greenness Assessment Metrics for Analytical Methods

Evolution and Principles of Greenness Assessment

Green Analytical Chemistry has emerged as a critical discipline focused on minimizing the environmental footprint of analytical methods, evolving from basic to comprehensive assessment metrics [1]. This progression began with foundational tools like the National Environmental Methods Index (NEMI), which introduced a simple pictogram indicating whether a method complied with four basic environmental criteria, though its binary structure limited its ability to distinguish degrees of greenness [1]. The field advanced with more sophisticated tools including the Analytical Eco-Scale, which assigns a score out of 100 based on penalty points for non-green attributes, and the Green Analytical Procedure Index (GAPI), which assesses the entire analytical process using a five-part, color-coded pictogram [101] [1].

The most recent advancements include the Analytical Greenness (AGREE) metric, which provides both a circular pictogram and a numerical score based on the 12 principles of GAC, and the Modified GAPI (MoGAPI), which retains the GAPI pictographic approach while adding a cumulative scoring system to improve comparability [101] [1]. Further specialized tools have emerged such as AGREEprep for evaluating sample preparation impact, Carbon Footprint Reduction Index (CaFRI) for estimating carbon emissions, and Analytical Green Star Analysis (AGSA) that uses a star-shaped diagram for multidimensional assessment [1]. This evolution reflects the growing importance of integrating environmental responsibility into analytical science, enabling chemists to design and select methods that are both scientifically robust and ecologically sustainable.

Key Greenness Assessment Tools Comparison

Table 1: Comparison of Major Greenness Assessment Metrics

Metric Tool	Assessment Focus	Scoring System	Visual Output	Key Advantages	Key Limitations
NEMI	Basic environmental criteria	Binary (pass/fail 4 criteria)	Simple pictogram	User-friendly, accessible	Lacks granularity, doesn't assess full workflow
Analytical Eco-Scale	Overall environmental impact	Numerical (0-100, penalty-based)	None	Facilitates direct comparison	Lacks visual component, subjective penalties
GAPI	Entire analytical process	Qualitative (green/yellow/red)	Five pentagrams	Comprehensive, visual identification of impact areas	No overall score, somewhat subjective
MoGAPI	Entire analytical process	Numerical score + qualitative	Five pentagrams with total score	Enables method comparison, classification	Retains some subjectivity from GAPI
AGREE	12 GAC principles	Numerical (0-1) + qualitative	Circular pictogram	Comprehensive, user-friendly, facilitates comparison	Doesn't fully account for pre-analytical processes
AGREEprep	Sample preparation	Numerical (0-1) + qualitative	Circular pictogram	Focuses on often high-impact stage	Must be used with broader tools for full assessment
AGSA	Multiple green criteria	Numerical + qualitative	Star-shaped diagram	Intuitive visualization, integrated scoring	Newer tool with less established track record
CaFRI	Carbon emissions	Numerical assessment	Specific output	Addresses climate impact specifically	Narrow focus on carbon footprint

Experimental Protocols for Greenness Assessment

MoGAPI Assessment Methodology

The Modified GAPI (MoGAPI) tool and software were developed to address the key limitation of the traditional GAPI metric—the lack of a total score for method comparison [101]. The assessment follows a detailed protocol where different stages of the analytical process are evaluated against specific criteria, with points assigned based on environmental impact. The scoring system allocates credits based on the number of options available in each item; for sample collection, in-line collection receives the maximum score (3 credits), online collection receives intermediate, while offline collection receives minimum credits (1) [101].

The calculation involves summing all earned credits and dividing by the maximum possible credits to generate a percentage score. If any aspect is not applicable, it is excluded from the calculation to avoid unfairly affecting the percentage. This approach enables the classification of methods into categories: excellent green (≥75), acceptable green (50-74), and inadequately green (<50) [101]. The software for this assessment is freely available as open source, making it accessible to researchers. The output includes both the characteristic red/green/yellow pictograms of traditional GAPI and the overall numerical score, providing both detailed and summary assessments of method greenness.

AGREE Assessment Methodology

The AGREE metric evaluates analytical methods against the 12 principles of Green Analytical Chemistry, offering a comprehensive assessment framework [1]. Each principle is scored individually, and the results are integrated into both a numerical score between 0 and 1 and a circular pictogram that provides immediate visual feedback on the method's environmental performance. The assessment covers the entire analytical process from sample preparation to final detection and waste management.

The AGREE software requires input parameters related to these 12 principles, including the use of hazardous chemicals, energy consumption, waste generation, and operator safety, among others. The tool then calculates the overall score, with higher values indicating superior greenness. The circular pictogram uses a color-coded system (typically green to red) to quickly communicate which principles are well-addressed and which need improvement. This dual output facilitates both quick comparison between methods and detailed analysis of specific environmental strengths and weaknesses, supporting continuous improvement in method sustainability.

Case Study: Greenness Assessment of Baricitinib Analytical Methods

Experimental Background and Methodologies

A recent study conducted a comprehensive greenness assessment of multiple analytical methods for baricitinib, a Janus kinase inhibitor, providing valuable insights into how performance verification intersects with sustainability goals [102]. The research compared several established methods against a newly developed Diffuse Reflectance Infrared Fourier Transform Spectroscopy (DRIFTS) approach, applying multiple greenness metrics to evaluate their environmental performance. The experimental design included both conventional chromatographic methods and the innovative DRIFTS method, which was developed using designed experiments to optimize robustness and reliability while minimizing resource demand and method failure.

The DRIFTS method development followed a systematic approach that ensured acceptable linearity, accuracy, and precision while eliminating the need for sophisticated sample preparation [102]. This methodology represents a significant advancement in green analysis, as it reduces solvent consumption and waste generation while maintaining analytical performance. The case study highlights the importance of retrospective greenness assessment of existing methods as a cost-effective strategy for achieving sustainable method performance within regulatory frameworks, demonstrating how older methods can be reevaluated and improved to meet modern environmental standards without compromising ICH validation requirements.

Comparative Greenness Assessment Results

Table 2: Greenness Scores for Baricitinib Analytical Methods Across Different Metrics

Analytical Method	MoGAPI Score	AGREE Score	AGSA Score	Key Greenness Strengths	Key Greenness Limitations
DRIFTS (New)	Not specified	Not specified	Not specified	Minimal solvent use, no complex sample preparation	Specific scores not provided in study
Reported HPLC/UV Methods	Not specified	Not specified	Not specified	Established validation parameters	High solvent consumption, waste generation
SULLME-HPLC (Antiviral Compounds)	60	56	58.33	Green solvents, microextraction (<10 mL), no derivatization	Toxic solvents, >10 mL waste, no waste treatment
DLLME-HPLC (Gliflozins)	80	~80	Not specified	Green solvents, minimal toxic solvents, microextraction	Moderate waste generation (1-10 mL)
Modified Column HPLC (Carboxylic Acids)	79	80	Not specified	Low-toxicity solvents, minimal energy consumption	Moderate waste generation (1-10 mL)

The case study revealed that the newly developed DRIFTS method for baricitinib analysis offered superior greenness characteristics compared to traditional methods, though specific numerical scores were not provided in the available data [102]. The assessment demonstrated that greenness optimization could be achieved without compromising method performance, as the DRIFTS method maintained acceptable linearity, accuracy, and precision while reducing environmental impact. The researchers employed multiple assessment tools including AGREE, ChlorTox, GAPI, NEMI, and Analytical Eco-Scale, establishing a comprehensive evaluation framework that can be applied across different analytical techniques.

The findings from this case study emphasize that method greenness and performance verification are not mutually exclusive but can be synergistically optimized through thoughtful method design and development. The DRIFTS approach successfully addressed the 12 principles of Green Analytical Chemistry by minimizing solvent use, reducing waste generation, and eliminating energy-intensive procedures while still meeting ICH guidelines for analytical method validation, providing a model for how pharmaceutical analysis can evolve toward greater sustainability.

Implementation Framework for Green Analytical Methods

Strategic Integration with ICH Compliance

Implementing green analytical methods while maintaining ICH compliance requires a systematic approach that aligns sustainability goals with regulatory requirements. The foundation of this integration is establishing a greenness assessment protocol that operates alongside traditional method validation procedures. This begins with evaluating existing methods using tools like MoGAPI or AGREE to establish baseline environmental performance, then identifying opportunities for improvement without compromising analytical reliability, sensitivity, or precision. Method transfer and verification protocols should be expanded to include greenness criteria, ensuring that sustainability becomes an integral component of method lifecycle management.

A critical success factor is the early incorporation of green principles during method development rather than attempting to retrofit sustainability into existing procedures. This proactive approach includes selecting less hazardous solvents, implementing miniaturized techniques, exploring alternative detection methods, and optimizing energy consumption. Method validation protocols under ICH guidelines should document both the standard performance characteristics (specificity, linearity, accuracy, precision, etc.) and environmental metrics, creating a comprehensive method profile that addresses both technical and sustainability requirements. This integrated documentation facilitates regulatory review and demonstrates commitment to both quality and environmental responsibility.

Green Method Optimization Strategies

• Solvent Selection and Management: Replace hazardous solvents with safer alternatives based on solvent selection guides, implement solvent recovery systems, and minimize solvent volumes through method miniaturization. This strategy directly addresses ICH Q3C guidelines on residual solvents while improving greenness scores in metrics like AGREE and MoGAPI [102] [1].

• Energy Reduction: Utilize ambient temperature processes where possible, optimize instrument methods to reduce run times, implement energy-efficient equipment, and schedule analyses to maximize instrument utilization. This approach reduces the energy penalty in greenness assessments while maintaining method precision and reliability [101] [1].

• Waste Minimization: Employ microextraction techniques, implement flow-based or on-line analysis systems, explore solvent-free extraction methods, and establish proper waste segregation and treatment protocols. These measures address the waste generation criteria in greenness metrics while often improving method efficiency and reducing costs [101] [1].

• Sample Preparation Innovation: Develop direct analysis techniques to eliminate extraction and purification steps, implement automated and miniaturized sample preparation systems, and explore alternative preparation methods that use less reagents and generate less waste. Simplified sample preparation improves overall method greenness while potentially enhancing reproducibility and precision [102] [1].

Research Reagent Solutions for Green Analytical Chemistry

Table 3: Essential Reagents and Materials for Green Analytical Methods

Reagent/Material	Function in Analysis	Green Alternatives	Environmental Considerations
Acetonitrile (ACN)	HPLC mobile phase	Ethanol, methanol, water-based mobile phases	Highly toxic, environmental pollutant
Methanol (MeOH)	HPLC mobile phase, extraction solvent	Ethanol, supercritical fluids	Toxic, flammable, hazardous waste
Chloroform	Extraction solvent	Ethyl acetate, cyclopentyl methyl ether	Carcinogenic, environmental persistent
Dichloromethane (DCM)	Extraction solvent	2-Methyltetrahydrofuran, ethyl acetate	Toxic, ozone-depleting, hazardous
Phosphate Buffers	HPLC mobile phase modifier	Ammonium acetate, ammonium formate	Eutrophication potential
Hydrochloric Acid (HCl)	Acidification, digestion	Alternative acids (citric, tartaric)	Corrosive, hazardous disposal
Sodium Hydroxide (NaOH)	Alkalization, hydrolysis	Alternative bases (ammonia)	Corrosive, hazardous disposal
Derivatization Agents	Analyte modification for detection	Direct analysis methods	Highly reactive, toxic, hazardous waste

Greenness Assessment Workflow Diagram

The integration of greenness assessment with traditional performance verification represents the future of analytical method development in the pharmaceutical industry. As demonstrated through the case studies and metrics comparisons, it is both feasible and beneficial to develop analytical methods that meet rigorous ICH guidelines for reliability, sensitivity, and precision while simultaneously minimizing environmental impact. The evolving landscape of greenness assessment tools, from GAPI and MoGAPI to AGREE and AGSA, provides researchers with comprehensive frameworks to evaluate and improve their methods' sustainability profiles.

The baricitinib case study illustrates how innovative analytical approaches like DRIFTS can offer superior greenness characteristics while maintaining methodological robustness [102]. As regulatory expectations continue to evolve, proactively adopting these green assessment principles will position pharmaceutical companies and researchers at the forefront of sustainable analytical science. By embracing the integrated verification framework outlined in this guide, scientists can ensure their methods not only generate reliable data but also contribute to broader environmental sustainability goals within the pharmaceutical industry.

In the face of pressing global environmental challenges, the scientific community has developed systematic approaches to evaluate and minimize the ecological footprint of chemical processes and analytical methods. Greenness scoring systems provide standardized, reproducible frameworks for quantifying environmental impact, enabling researchers and industry professionals to make informed decisions that align with sustainability goals. These assessment tools have evolved from basic checklists to sophisticated multi-dimensional metrics that integrate environmental, social, and economic considerations [1].

The pharmaceutical industry and analytical laboratories present particular challenges for sustainability implementation due to their reliance on complex chemical processes and stringent regulatory requirements. Within these fields, green analytical chemistry (GAC) has emerged as a critical discipline focused on minimizing the environmental footprint of analytical methods through reduced waste generation, lower energy consumption, and the elimination of hazardous substances [28] [1]. The evolution of assessment methodologies has progressed from foundational tools like the National Environmental Methods Index (NEMI) to comprehensive frameworks such as the Analytical Greenness (AGREE) metric and Analytical Method Greenness Score (AMGS) calculator, which offer both visual and quantitative evaluations of analytical procedures [1] [103].

Comprehensive Comparison of Greenness Scoring Systems

Foundational Metrics and Tools

Assessment Tool	Type	Scoring System	Key Parameters Assessed	Primary Applications
Analytical Method Greenness Score (AMGS) [103]	Quantitative	Numerical score (lower = greener)	Instrument energy, solvent energy, solvent EHS (Environment, Health, Safety)	HPLC/UHPLC method sustainability comparison
AGREE (Analytical Greenness) [1]	Semi-quantitative	Score 0-1 + pictorial representation	All 12 principles of GAC, including waste, toxicity, energy	Comprehensive analytical method evaluation
GAPI (Green Analytical Procedure Index) [1]	Qualitative	Color-coded pictogram (5-part)	Sample collection, preparation, transportation, derivation, detection	Visual identification of high-impact analytical stages
NEMI (National Environmental Methods Index) [1]	Qualitative	Binary pictogram (pass/fail 4 criteria)	Toxicity, persistence, waste generation, corrosive reagents	Basic environmental compliance screening
Analytical Eco-Scale [1]	Quantitative	Penalty points subtracted from 100	Hazardous reagents, energy demand, waste generation	Direct method comparison with transparent scoring
SUSTAIN [104]	Quantitative	Percentage score (0-100) + SDG alignment	UN Sustainable Development Goals (SDGs) mapping	Broad sustainability assessment of methods, processes, initiatives
Green Index (GI) [105]	Quantitative	Numerical index	Leaf greenness as proxy for chlorophyll content, plant health	Plant phenotyping, agricultural research

Advanced and Specialized Assessment Systems

Assessment Tool	Type	Scoring System	Key Parameters Assessed	Primary Applications
AGREEprep [1]	Semi-quantitative	Score 0-1 + pictorial representation	Sample preparation-specific parameters	Environmental impact of sample preparation steps
Modified GAPI (MoGAPI) [1]	Semi-quantitative	Cumulative scoring system + pictogram	Entire analytical process with improved comparability	Enhanced method comparison with visual elements
AGSA (Analytical Green Star Analysis) [1]	Semi-quantitative	Star-shaped diagram + integrated score	Reagent toxicity, waste generation, energy use, solvent consumption	Multidimensional visual method comparison
CaFRI (Carbon Footprint Reduction Index) [1]	Quantitative	Carbon emission estimates	Energy sources, equipment, transportation, solvent volumes	Climate impact assessment of analytical procedures

Experimental Protocols and Methodologies

Analytical Method Greenness Score (AMGS) Application Protocol

The AMGS calculator, developed by Hicks et al. and available through the ACS Green Chemistry Institute Pharmaceutical Roundtable, provides a standardized methodology for quantifying the environmental impact of chromatographic methods [103]. The experimental protocol involves:

• System Characterization: Document the analytical platform (HPLC, UHPLC, or UPLC), flow rate (mL/min), and run time (minutes).

• Mobile Phase Composition: Quantify the exact proportions of all solvents and reagents in the mobile phase, including water.

• Sample Analysis Requirements: Specify the number of analytes of interest and the total number of injections required for a complete analysis, including system suitability tests and sample replicates.

• Sample Preparation Details: Account for volumes of all solvents and reagents used in sample preparation, including diluents and stock solutions.

• Data Input and Calculation: Enter all parameters into the AMGS calculator, which computes three subscores:

  • Instrument Energy Score: Based on system type and total run time
  • Solvent Energy Score: Reflects energy embedded in solvent production
  • Solvent EHS Score: Accounts for environmental, health, and safety impacts of solvents

• Interpretation: Lower final AMGS values indicate greener methods, enabling direct comparison between different methodological approaches [103].

AGREE Assessment Methodology

The AGREE metric evaluates analytical methods against all 12 principles of green analytical chemistry through a standardized protocol:

• Principle-Based Evaluation: Assess the method against each of the 12 GAC principles using a 0-1 scoring scale for each principle.

• Data Collection: Gather comprehensive data on:

  • Sample preparation techniques
  • Sample size and collection methods
  • Derivatization requirements
  • Throughput and analysis time
  • Automation level
  • Energy consumption per sample
  • Reagent toxicity and quantities
  • Waste generation and treatment
  • Operator safety considerations

• Software-Assisted Calculation: Input data into the freely available AGREE software, which generates:

  • A unified numerical score between 0-1
  • A circular pictogram with 12 sections corresponding to GAC principles
  • Color-coded visualization (red to green) indicating performance per principle

• Comparative Analysis: Use the output to identify environmental hotspots and compare methods holistically [1].

Case Study: Sustainability Assessment of Naproxen Monograph Methods

A recent application of greenness scoring demonstrates the practical implementation of these assessment protocols. Researchers evaluated the United States Pharmacopeia (USP) monograph method for naproxen sodium tablets across three chromatographic platforms:

• Traditional HPLC: 5 µm particle column, 1.2 mL/min flow rate, 8-minute run time
• UHPLC System: Smaller particle column, reduced flow rate and run time
• UPLC System: Sub-2 µm particle column, minimal flow rate and run time

The experimental workflow included:

• Method Validation: Ensuring all three platforms met USP system suitability requirements
• Parameter Quantification: Documenting solvent consumption, energy use, and waste generation for each platform
• AMGS Calculation: Applying the calculator to all three methods using identical sample preparation and injection parameters
• Result Interpretation: The UPLC method achieved an AMGS of <30, compared to 110 for the traditional HPLC method, demonstrating significantly improved sustainability while maintaining analytical validity [103].

Visualizing Assessment Workflows and Relationships

Greenness Assessment Selection Algorithm

Analytical Greenness Assessment Ecosystem

Essential Research Reagent Solutions and Tools

Greenness Assessment Software and Calculators

Tool/Resource	Type	Access	Key Function	Application Context
AMGS Calculator [103]	Web-based calculator	Free online access	Quantifies environmental impact of LC methods	Pharmaceutical analysis, method modernization
AGREE Software [1]	Downloadable software	Free access	Evaluates methods against 12 GAC principles	Comprehensive analytical method development
SUSTAIN Tool [104]	Assessment framework	Freely available	Maps processes to UN SDGs	Broad sustainability assessment beyond analytics
Green Index Calculator [105]	Online calculator & software	Open-source	Quantifies plant greenness from RGB images	Plant phenotyping, agricultural research

Analytical Methodology Modernization Tools

Tool/Resource	Type	Key Function	Sustainability Benefit
UPLC Systems [103]	Instrumentation	Sub-2µm particle chromatography	Reduces solvent consumption by 85-90% vs. HPLC
PHREEPro Database	Software	Solvent substitution guidance	Identifies greener alternative solvents
Method Translation Software	Software	HPLC to UHPLC/UPLC method conversion	Enables modernization without revalidation
Suspended Solvent Modules	Hardware	Microscale extraction & preparation	Reduces reagent volumes to µL scale

The evolving landscape of greenness scoring systems provides researchers and pharmaceutical professionals with increasingly sophisticated tools to quantify and minimize environmental impacts. From specialized metrics like AMGS for chromatographic methods to comprehensive frameworks like SUSTAIN that align with United Nations Sustainable Development Goals, these assessment approaches enable data-driven decisions that balance analytical performance with ecological responsibility [104] [103].

The experimental protocols and case studies demonstrate that significant sustainability improvements can be achieved through method modernization and optimization, often with co-benefits of reduced operational costs and increased throughput. As regulatory pressure and environmental awareness continue to grow, the implementation of standardized greenness assessment will become increasingly integral to analytical method development, validation, and routine application in drug development and beyond [1] [103].

Future developments in greenness scoring will likely focus on harmonizing assessment methodologies, addressing social sustainability dimensions, and integrating circular economy principles to create a more comprehensive and standardized approach to sustainability evaluation in scientific practice [106].

In the pharmaceutical industry, the environmental impact of analytical methods used for drug quality control is a growing concern. The principles of Green Analytical Chemistry (GAC) aim to make analytical procedures more ecologically friendly and safer, leading to the development of various greenness assessment tools [107]. This guide provides a structured framework for the statistical comparison of these greenness profiles, enabling researchers, scientists, and drug development professionals to objectively identify significant differences between analytical methods and select the most sustainable options. This work is situated within a broader thesis on comparative greenness assessment case studies research, providing a standardized approach for evaluating method sustainability.

Greenness Assessment Tools and Metrics

A variety of metrics have been developed to quantify the environmental impact of analytical methods. These tools evaluate factors such as reagent toxicity, energy consumption, and waste generation [107]. The table below summarizes the key greenness, blueness, and whiteness assessment tools used in comparative pharmaceutical analysis.

Table 1: Greenness, Blueness, and Whiteness Assessment Metrics

Metric Name	Category	Primary Evaluation Focus	Scoring System
Analytical Eco-Scale [107]	Greenness	Reagent quantity/quality, energy, waste, occupational risk	Penalty points subtracted from 100; >75 = excellent green analysis
AGREE (Analytical GREEnness) [107] [108]	Greenness	12 principles of GAC (sample treatment, amount, waste, energy, toxicity)	Pictogram with 0-1 scale for each principle; 1 = ideal
GAPI (Green Analytical Procedure Index) [107] [108]	Greenness	15 aspects across sampling, preparation, instrumentation, reagents	Color-coded pentagrams (green, yellow, red)
BAGI (Blue Applicability Grade Index) [107] [108]	Blueness	Usefulness and practicality of the analytical method	Quantitative assessment of practical aspects
RGB 12 (Red-Green-Blue 12) [108]	Whiteness	Holistic integration of analytical (red), ecological (green), and practical (blue) quality	12 principles encompassing all three pillars

Experimental Protocols for Greenness Comparison

A robust protocol for comparing greenness profiles involves method application, data extraction, statistical analysis, and interpretation. The following workflow details the steps for a typical comparative assessment.

Application of Assessment Tools

The first experimental phase involves the systematic application of selected greenness tools to each analytical method under review. For instance, a study evaluating spectrophotometric methods for analyzing chloramphenicol and dexamethasone sodium phosphate applied the Analytical Eco-Scale, AGREE, and GAPI to five different techniques [107]. Similarly, a review of chromatographic methods for cilnidipine utilized six different metrics, including AGREE, GAPI, and BAGI [108]. This multi-tool approach provides a comprehensive view of each method's environmental and practical performance. The output from these tools—whether a numerical score, a pictogram, or a color-coded diagram—serves as the raw data for subsequent statistical analysis.

Data Extraction and Preparation

Quantitative data must be extracted from the assessment results to enable statistical testing. For tools like the Analytical Eco-Scale, the final numerical score is used directly [107]. For AGREE, the overall score (a number between 0 and 1) from the central pictogram is recorded. When using GAPI, a semi-quantitative approach can be adopted, such as counting the number of green, yellow, and red fields. These extracted scores should be organized in a structured table to facilitate comparison.

Table 2: Example Data Structure for Extracted Greenness Scores

Analytical Method	Analytical Eco-Scale Score	AGREE Score	GAPI (Green Fields)	BAGI Score
Method A	85	0.82	12/15	75
Method B	72	0.65	9/15	82
Method C	90	0.88	14/15	70

Statistical Analysis Framework

Choosing the correct statistical test is paramount for validating the significance of observed differences in greenness scores. The flowchart below guides the selection process based on the number of methods being compared and the distribution of the data.

Hypothesis Testing and P-Values

The core of statistical comparison lies in hypothesis testing. The null hypothesis (H₀) states that there is no significant difference in the greenness profiles between the analytical methods. A p-value is calculated, representing the probability of observing the measured difference if the null hypothesis were true [109]. A result is considered statistically significant if the p-value falls below a pre-defined significance threshold (alpha, α), typically set at 0.05 (5%) [109]. In a comparative study of spectrophotometric methods, researchers used Student's t-test and F-test to validate that their newly developed green methods showed no significant difference from published methods in terms of analytical performance, thereby establishing their validity before greenness comparison [107].

Interpreting Significance and Effect Size

A statistically significant result (p ≤ 0.05) allows the researcher to reject the null hypothesis and conclude that a genuine difference exists between the greenness profiles [109]. However, it is crucial to also consider the effect size, which quantifies the magnitude of the difference [109]. A large effect size with statistical significance indicates a substantial and reliable environmental advantage of one method over another. This combination provides a complete picture, ensuring that the difference is not just statistically significant but also practically meaningful for making sustainable choices in drug development.

Essential Research Reagent Solutions

The following reagents and instruments are fundamental for conducting the analytical methods and greenness assessments described in this guide.

Table 3: Key Research Reagents and Instruments for Greenness Analysis

Item Name	Function/Application	Example from Literature
Ethanol	Used as a greener solvent alternative to more hazardous organic solvents in sample preparation and analysis [107].	Used in spectrophotometric analysis of CHL and DSP to enhance method greenness [107].
UV-Visible Spectrophotometer	Instrument for quantifying drug components in formulations; generally has a lower environmental footprint than chromatographic systems.	A JASCO V-630 model was used for green spectrophotometric methods [107].
Chloramphenicol (CHL) & Dexamethasone Sodium Phosphate (DSP)	Model drug compounds used in development and validation of green analytical methods.	Used as analytes in a comparative greenness study of five spectrophotometric techniques [107].
Standard Reference Materials	High-purity chemicals with certified concentrations used to create calibration curves and validate method accuracy.	CHL and DSP with purities of 99.07% and 99.36%, respectively, were used to establish regression equations [107].

In the evolving landscape of analytical chemistry, the principles of Green Analytical Chemistry (GAC) have gained significant prominence, driven by a growing awareness of the environmental impact of analytical procedures [110]. GAC aims to minimize the ecological footprint of analytical methods by reducing waste, energy consumption, and the use of hazardous reagents [28]. This paradigm shift has necessitated the development of reliable metrics to evaluate and quantify the environmental sustainability of analytical processes. Modern assessment tools have evolved to provide a more comprehensive evaluation by including previously overlooked aspects such as sample preparation, which is often essential for accurate analysis but can significantly contribute to environmental impact [28]. The contemporary landscape of assessment tools now includes various metrics for evaluating greenness, alongside emerging concepts of whiteness and blueness assessments that provide a more balanced view of method practicality and sustainability [110].

The implementation of these tools is particularly crucial for drug development professionals and researchers who must balance methodological rigor with environmental responsibility. This comparative guide examines the strengths, limitations, and appropriate applications of major green assessment tools through the lens of comparative case studies, providing a structured framework for selecting the most appropriate evaluation methodology for specific research contexts.

Tool Descriptions and Methodological Approaches

Several established tools are currently available for evaluating the greenness of analytical methods, each with unique approaches and evaluation criteria. The National Environmental Methods Index (NEMI), Eco-scale Assessment (ESA), Green Analytical Procedure Index (GAPI), and Analytical GREEnness (AGREE) represent the most widely adopted metrics in contemporary analytical chemistry [110]. These tools provide either numerical scores or visual representations to facilitate the environmental impact assessment of analytical procedures.

Recent comparative studies have expanded evaluations to include newer metrics such as the blue applicability grade index (BAGI), which works alongside greenness metrics to provide a more comprehensive sustainability profile [111]. The progression of these tools demonstrates a shift from simple binary evaluations to nuanced, multi-factor assessments that consider the complete analytical workflow. The Whiteness Assessment Criteria (WAC) represents a particularly significant advancement, as it seeks to balance environmental impact with functionality, avoiding an unconditional increase in greenness at the expense of methodological performance [110].

Comparative Analysis of Tool Characteristics

Table 1: Key Characteristics of Major Green Assessment Tools

Assessment Tool	Evaluation Approach	Output Format	Parameters Evaluated	Scope of Assessment
NEMI	Qualitative	Pictogram (4 quadrants)	PBT, hazardous, corrosive, waste quantity	Basic environmental impact
Eco-Scale Assessment (ESA)	Quantitative	Numerical score (100-point scale)	Reagents, instruments, energy, waste	Penalty-based system
GAPI	Semi-quantitative	Pictogram (5 pentagrams)	Sample collection, preparation, transportation, reagent use, waste	Comprehensive lifecycle approach
AGREE	Quantitative	Numerical score (0-1) & circular pictogram	12 principles of GAC	Most comprehensive GAC principles
BAGI	Quantitative	Numerical score	Method performance, practicality	Applicability & practicality

Experimental Protocols for Tool Application

Standardized Evaluation Methodology

To ensure consistent comparison across different green assessment tools, researchers should implement a standardized evaluation protocol. A recent comparative study analyzing 16 analytical methods based on solid-phase microextraction techniques established a robust methodological framework [111]. The protocol begins with the extraction of required parameters from analytical procedures, including energy consumption, reagent types and volumes, waste generation, and analysis throughput.

The subsequent calculation phase applies the unique evaluation algorithm of each tool while maintaining a uniform approach to data interpretation. For tools employing pictograms, such as NEMI and GAPI, researchers should standardize the color-coding schemes and symbolic representations to maintain consistency across evaluations. For quantitative tools like AGREE and ESA, establishing threshold values for different sustainability levels is essential for comparative analysis. The comparative phase identifies factors most significantly affecting greenness scores, enabling researchers to pinpoint specific areas for methodological improvement [111].

Case Study Implementation Framework

Implementing a valid case study requires careful experimental design that controls for methodological variability. A representative study should select analytical methods from similar domains to ensure meaningful comparisons—for instance, focusing exclusively on chromatographic methods or spectroscopy-based techniques. The case study should include diverse methodological approaches within the domain, such as comparing traditional solvent-intensive methods with more modern micro-extraction techniques [111].

Each method must be evaluated using multiple assessment tools to obtain synergistic results and increase the understanding of the greenness profile. The experimental protocol should specifically document how each tool handles critical parameters such as energy consumption, organic solvent use, waste generation, analysis throughput, and the number of determined analytes, as these factors have been identified as crucial parameters requiring improvement in analytical methods [111]. This multi-tool approach provides a more nuanced understanding of environmental impact and helps identify consistent trends across different evaluation methodologies.

Visualizing Assessment Tool Workflows

Greenness Assessment Tool Selection Algorithm

Comprehensive Greenness Assessment Workflow

Critical Analysis of Tool Strengths and Limitations

Advantages of Modern Assessment Tools

Contemporary green assessment tools offer several significant advantages over earlier evaluation methods. The most notable strength is their comprehensive scope, with modern tools like AGREE evaluating methods against all 12 principles of Green Analytical Chemistry, providing a more holistic sustainability assessment [110]. The inclusion of sample preparation in evaluations addresses a critical gap in earlier metrics, acknowledging that this often resource-intensive step substantially contributes to the overall environmental impact of analytical methods [28].

The development of whiteness assessments represents a particular advancement, as these tools balance environmental concerns with practical methodological requirements. Unlike earlier approaches that prioritized greenness unconditionally, whiteness assessment recognizes that analytical methods must remain functionally effective while reducing environmental impact [110]. The visual output formats employed by many tools, including pictograms and colored scales, enhance communication of complex sustainability data to diverse stakeholders, facilitating more informed decision-making in method selection and optimization.

Limitations and Challenges

Despite their utility, current assessment tools face several limitations that researchers must consider. A significant challenge is the variability in evaluation criteria across different tools, which can produce conflicting results for the same analytical method [111]. This inconsistency complicates direct comparisons and may lead to confusion in method selection. Many tools also suffer from subjectivity in scoring, particularly for parameters that lack standardized quantitative metrics, potentially introducing bias into sustainability assessments.

Another notable limitation is the inadequate addressing of sample throughput, which significantly influences the overall environmental impact of analytical methods when considered on a per-analysis basis [111]. Furthermore, most tools exhibit limited accommodation of emerging technologies, such as automated systems and miniaturized techniques, which may offer substantial sustainability advantages not fully captured by current evaluation frameworks. This technological gap can undervalue innovative approaches that align with green chemistry principles but deviate from traditional methodological paradigms.

Research Reagent Solutions for Green Analytical Chemistry

Essential Materials and Their Functions

Table 2: Key Research Reagents and Their Functions in Green Analytical Chemistry

Reagent/Material	Function in Analytical Methods	Green Alternatives	Environmental Considerations
Organic Solvents	Sample preparation, extraction, mobile phases	Green solvents (water, ethanol, bio-based solvents)	Toxicity, biodegradability, waste generation
Derivatization Agents	Analyte modification for detection	Microwave-assisted, ultrasound-assisted techniques	Reduction of reaction time and energy
Sorbents	Extraction and concentration of analytes	Biopolymer-based sorbents, molecularly imprinted polymers	Renewable sources, recyclability
Catalysts	Acceleration of analytical reactions	Heterogeneous catalysts, biocatalysts	Reusability, reduced metal content
Energy Sources	Method execution	Renewable energy, optimized power settings	Consumption reduction, sustainable sources

The movement toward green solvents represents a particularly significant development, with machine learning approaches now being employed to assess and identify sustainable alternatives to hazardous solvents without compromising performance [29]. These data-driven pipelines can predict greenness metrics and identify safer substitutes for traditionally problematic solvents like benzene and diethyl ether, accelerating the adoption of environmentally friendly alternatives in analytical chemistry [29].

Appropriate Applications and Case Study Findings

Context-Specific Tool Selection

The effective application of green assessment tools requires careful matching of tool capabilities to specific research contexts. For preliminary screening of analytical methods, pictogram-based tools like NEMI and GAPI offer rapid visual assessments that efficiently identify potential environmental concerns. For comprehensive method optimization and development, quantitative tools such as AGREE and ESA provide detailed scoring systems that facilitate precise comparisons between methodological variations and establish clear improvement targets.

In regulatory and compliance contexts, the whiteness assessment approach offers particular value by balancing environmental sustainability with methodological practicality, acknowledging that analytical methods must satisfy multiple performance criteria beyond simply minimizing environmental impact [110]. The integration of multiple tools has been demonstrated to yield synergistic benefits, providing more nuanced insights into method greenness than any single-metric approach [111]. This multi-tool strategy helps mitigate individual tool limitations while capitalizing on their respective strengths.

Comparative Case Study Insights

Recent comparative studies applying multiple assessment tools to solid-phase microextraction techniques have revealed several consistent findings. The research demonstrated that microextraction techniques generally outperform traditional approaches in greenness metrics due to their reduced solvent consumption and minimal waste generation [111]. However, the studies also identified high energy consumption and organic solvent use as persistent challenges even in advanced microextraction methods, highlighting priority areas for further technological innovation.

The case studies further revealed that method throughput and the number of determined analytes significantly influence overall greenness assessments, emphasizing the importance of considering analytical efficiency alongside environmental impact metrics [111]. These findings underscore the value of whiteness assessment approaches that balance environmental concerns with practical analytical performance, ensuring that sustainability improvements do not compromise methodological effectiveness.

The critical evaluation of green assessment tools reveals a rapidly evolving landscape of metrics designed to quantify and improve the environmental sustainability of analytical methods. While significant advancements have been made in developing comprehensive, multi-parameter tools that provide nuanced sustainability assessments, important limitations remain in terms of standardization, technological currency, and methodological scope. The integration of multiple assessment tools, particularly those incorporating whiteness concepts that balance environmental and practical considerations, offers the most promising approach for comprehensive sustainability evaluation.

For researchers and drug development professionals, selecting appropriate assessment tools requires careful consideration of methodological context, assessment goals, and decision-making criteria. The continued refinement of these tools, coupled with emerging technologies like machine learning for solvent assessment and substitution, promises to further enhance their utility and accuracy. As green chemistry principles become increasingly embedded in analytical method development, these assessment tools will play a crucial role in guiding the field toward more sustainable practices without compromising analytical performance.

Conclusion

Comparative greenness assessment represents a transformative approach to pharmaceutical analysis, moving sustainability from an abstract concept to a measurable, optimizable parameter. The consistent evidence from case studies demonstrates that techniques like capillary electrophoresis, reversed-phase HPTLC, and microextraction methods consistently achieve superior greenness profiles while maintaining analytical validity. The successful implementation of multi-metric tools provides a robust framework for objective environmental impact assessment, though method selection must balance ecological benefits with practical applicability and performance requirements. Future directions should focus on developing standardized greenness validation protocols, integrating artificial intelligence for method optimization, and expanding assessment frameworks to encompass economic and social dimensions of sustainability. As regulatory pressures and environmental consciousness grow, embracing these evidence-based green assessment strategies will be crucial for advancing both ecological stewardship and analytical excellence in pharmaceutical research and development.

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