Green Analytical Evaluation of Anticancer Drugs: A Multi-Tool Assessment of HPLC and LC-MS Methods

Green Analytical Evaluation of Anticancer Drugs: A Multi-Tool Assessment of HPLC and LC-MS Methods | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Green Analytical Evaluation of Anticancer Drugs: A Multi-Tool Assessment of HPLC and LC-MS Methods Huma Sulthana, Judy Jays, B Prakash Kumar, Prakash Goudanavar This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7860826/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 13 Jan, 2026 Read the published version in Scientific Reports → Version 1 posted 12 You are reading this latest preprint version Abstract Cancer continues to be a significant health challenge in the world. Anticancer treatments are developing rapidly, but the analytical techniques used to support these treatments in terms of drug development and monitoring often involve hazardous solvents and create much waste compared to other technologies. This study attempt to apply Green Analytical Chemistry principles in high-performance liquid chromatography and liquid chromatography–mass spectrometry methods for the analysis of anticancer drugs. Sixteen analytical methods were evaluated using five well-known greenness assessment tools: AGREE, GAPI, AGREEprep, Analytical Eco-Scale, and Blue Analytical Greenness Index. These tools provided a comprehensive evaluation of environmental sustainability in relation to reagent toxicity, waste production, energy consumption and preparation of samples. The most environmentally sustainable as well as practically implementable among the assessed methodologies are Methods HPLC-1, LC-MS-2, HPLC-7, LC-MS-3, and HPLC-8. Most methods incorporate toxic solvents acetonitrile and methanol even after great development; greener solvents such as ethanol and water-based systems should replace them more significantly in future strategies. Greenness assessment methods must be integrated into validation/development processes involving safer solvents for sustainability principles upheld while reducing environmental risk together with analytical performance maintenance toward global health success versus ecological preservation. Physical sciences/Chemistry Earth and environmental sciences/Environmental sciences Anticancer Greenness BAGI AGREE AGREE prep ESA GAPI 1. Introduction Cancer is one of the leading causes of death worldwide, second only to heart disease, with millions of lives lost each year. The number of cancer cases has been steadily rising over the years—from 12.7 million in 2008 to 14.1 million in 2012, and by 2018, there were 18.1 million new cases and 9.6 million deaths ( 1 , 2 ). In 2022, that number jumped to an estimated 20 million new cases and 9.7 million deaths. On a more hopeful note, around 53.5 million people were living five years after a cancer diagnosis, showing that more people are surviving cancer thanks to advances in treatment. But the statistics are still sobering—about 1 in 5 people will develop cancer in their lifetime, and roughly 1 in 9 men and 1 in 12 women will die from it. Looking ahead, it’s predicted that by 2050, there will be over 35 million new cancer cases each year 77% increase from 2022. This dramatic rise underscores the urgent need for better prevention, early detection, and treatment worldwide ( 3 ). cancer treatments vary, ranging from localized approaches like surgery and radiation, which target specific tumors, to systemic therapies such as chemotherapy, immunotherapy, and targeted therapy that affect the entire body. While chemotherapy broadly refers to cancer-fighting medications, anticancer agents encompass various groups—including natural products, alkylating agents, antimetabolites, and hormones—each with distinct mechanisms of action. Novel agents within these drug categories are in advanced stages of clinical development, driven by the growing demand for more effective treatments. To support this progress, highly sensitive analytical techniques such as electrophoresis, chromatography, spectroscopy, and electrochemical methods are essential for accurate quantitative analysis ( 4 – 6 ). Accurate analytical methods for the therapeutic drug monitoring (TDM) of anticancer medications are essential to maximize clinical outcomes. In therapeutic settings, pharmacokinetic (PK) investigations help determine the appropriate drug dosages and dosing intervals for cancer patients. These methods and studies are particularly crucial because many anticancer drugs have narrow therapeutic windows, exhibit high interpatient variability, and pose significant toxicity risks. accurate TDM &PK data enable safe, effective, and personalized treatment, ultimately improving therapeutic efficacy and minimizing adverse effects ( 7 , 8 ). Scientific research, ecological education, economic tools (such as revenues and subsidies), environmental monitoring, and legislative systems to control resource management and advance sustainable development are all part of the global implementation of pro-ecological policies. According to the World Commission on Environment and Development, sustainable eco-development was first proposed in 1987 ( 9 ). emphasizing the need to balance economic growth, environmental preservation, and public health. Sustainable development is particularly relevant to chemists, as reflected in green chemistry principles ( 10 ), which emerged after the US Congress passed the Pollution Prevention Act of 1990 ( 11 ). Paul Anastas introduced the term green chemistry in 1991 as part of an Environmental Protection Agency initiative ( 12 ), leading to the establishment of the US Green Chemistry Program in 1993, which promotes global collaboration and education in sustainable practices ( 13 ). Green chemistry is essential to address the environmental, health, and economic issues caused by traditional chemical practices. Conventional processes often generate hazardous waste and release pollutants, leading to climate change, biodiversity loss, and ecosystem damage. Exposure to toxic chemicals also increases risks of cancer, respiratory diseases, and neurological disorders. Additionally, traditional methods heavily rely on non-renewable resources such as fossil fuels, leading to resource depletion and inefficiencies like low atom economy and high material waste. Green chemistry focuses on renewable feedstocks, energy-efficient processes, and waste reduction, promoting long-term sustainability ( 14 ). Economically, green chemistry reduces costs by minimizing hazardous waste management and energy consumption. It also opens new markets for eco-friendly products as consumer demand shifts toward sustainability. Stricter regulations, including REACH (EU) and TSCA (USA), further necessitate the adoption of safer chemical processes to ensure compliance and competitiveness ( 15 ). Beyond regulation and economics, green chemistry embodies ethical scientific responsibility by designing safer products and processes that minimize harm. It supports several United Nations Sustainable Development Goals (SDGs), notably good health, clean water, responsible consumption, and climate action. Thus, green chemistry is not merely an innovation but a necessity for safeguarding health, protecting the environment, and advancing sustainable development ( 16 ). The current trend in analytical method development for HPLC and LC-MS is a shift towards greener and more sustainable solvent choices, driven by environmental and regulatory concerns. Water and ethanol are increasingly favoured as primary solvents. Techniques like miniaturization and UHPLC are being used to reduce solvent consumption. The integration of LC-MS often requires specific solvents compatible with mass spectrometry detection ( 17 ). Green Analytical Chemistry (GAC) principles are guiding the adoption of solvents like water, ethanol, and other bio-based options. Various green solvent types, including supercritical CO 2 , ionic liquids, and deep eutectic solvents, have potential applications in HPLC and LC-MS. Challenges remain in terms of solvent compatibility with analytes and LC-MS systems, method validation, and the need to replace traditional solvents like acetonitrile effectively. Regulatory frameworks like ICH guidelines also influence solvent use ( 15 ). Economically, green solvents are becoming more attractive, especially when considering reduced waste disposal costs. Solvent recycling programs are also gaining importance. Emerging solvent technologies like ionic liquids and deep eutetic solvents are being explored for HPLC and LC-MS applications. Automation and advancements in column technology are also contributing to more efficient solvent use in these techniques ( 18 ). Despite these advancements, no consensus exists on standardized criteria for evaluating analytical method greenness, risking GAC's practical application. However, the importance of sustainability in analytical chemistry is widely recognized, with efforts to extend its benefits to underserved regions through modified strategies and methods. No universal standard for greenness of an analytical method has been developed, which further continues to limit the practical adoption of GAC. Although total removal of solvents is the ideal approach, in reality, solutions are more aimed at reducing harmful solvents or substitutes with greener alternatives. In an ideal green solvent should exhibit low toxicity, biodegradability, reusability, sustainability and good analytical performance. GAPI, Analytical Eco-Scale and AGREE are examples of tools that provide structured and objective evaluations regarding environmental impacts due to factors like solvent usage waste energy consumption and operator safety. The systematic application of such tools allows researchers to point out the less sustainable elements in current methods and rectify them. This becomes especially important in the pharmaceutical industry as well as oncology research where accuracy has to go hand in hand with sustainable environment. Some criteria of greenness should be integrated into regulatory frameworks as a way forward; tool-based assessment shall pave ways towards sustainable transitions in analytical practices. This study presents a new evaluation framework for analytical techniques employed in the assessment of antineoplastic agents, which goes beyond traditional validation criteria and includes wider methodological as well as sustainability aspects. 2. Materials and Methods 2.1 Estimation techniques reported for anti-cancer drugs by HPLC and LC-MS HPLC and LC-MS are widely employed liquid chromatographic method due to their high separation capacity, making it suitable for analyzing anticancer drugs (19). In pharmaceutical drug research, there chromatography methods are often used, especially for the study of pharmaceuticals in biological matrices (20, 21). Organic solvents like ACN or MeOH combined with volatile buffers or acids (such acetic acid, ammonium acetate, or ammonium formate) in gradient or isocratic elution regimes make up common mobile phases. 2.1.1 Estimation technique by HPLC Barrawaz Aateka Yahya et al. (2021) developed a QbD-based RP-HPLC method for Abiraterone Acetate using a C 18 column with acetonitrile–ammonium acetate (69:31), showing good linearity (10–180 µg/mL, R² = 0.997), precision, and suitability for bulk, tablets, and nano-formulations (22). Sarwar Beg et al. (2021) also used a QbD approach with a Hypersil BDS C18 column and acetonitrile–water (15:85), achieving excellent recovery (99.8–100.2%) and identifying degradation products under stress conditions (23). Ravi Sankar et al. (2021) developed a precise method using methanol–acetonitrile (50:50) with a linearity of 2–10 µg/mL and high recovery (99.78%) (24). Tiphaine Belleville et al. (2015) introduced a sensitive HPLC-fluorescence method for abiraterone in plasma (1.75–50 ng/mL) using acetonitrile–glycine buffer and fluorescence detection (λex/em: 255/373 nm), enabling clinical monitoring (25). Vijay Kumar Sripuram et al. (2010) established a robust RP-HPLC method for doxorubicin in plasma with 99.8% recovery and excellent linearity over 0.2–10 µg/mL using a water–acetonitrile (75:25) mobile phase (26). Vanesa Escudero-Ortiz et al . (2013) quantified lapatinib in plasma using acetonitrile–ammonium acetate (53:47), showing > 86.7% recovery and good precision (27). Mistiran et al. (2010) reported a method for Ara-C and doxorubicin using acetonitrile–ammonium hydrogen phosphate (45:55), with strong precision and accuracy (28). Ebrahim Saadat et al. (2015) validated a rapid HPLC method for paclitaxel and lapatinib in micelles using acetonitrile–water (70:30), showing linearity (5–80 µg/mL) and precision (RSD < 5.83%) (29). Laura Zufía López et al . (2006) developed an HPLC-UV method for docetaxel and paclitaxel in plasma with high recovery (~ 88–91%) and a low LLOQ (0.015 mg/L), suitable for pharmacokinetics (30). Xinran Chen et al. (2022) established a UPLC-MS/MS method for simultaneous quantification of five drugs in plasma with high accuracy and stability, supporting clinical drug monitoring (31). Göknil Pelin Coşkun et al. (2022) developed a HPLC method for Imatinib using a C 18 column with acetonitrile and TEA/phosphate buffer (pH: 7.04; 0.1 M) (50:50, v/v) showing good linearity (10–90 µg/mL, R² = 0.999) (32). Silvia De Francia et al. (2022) introduced a sensitive HPLC method for imatinib, dasatinib, and nilotinib in human plasma, using acetonitrile and water + formic acid 0.05% (33). MD Nazmus Sakib et al. (2023) reported a method for rifampicin using 60% acetate buffer (pH 4.5) and 40% acetonitrile, with strong precision and accuracy (34). Panchumarthy Ravi Sankar et al. (2019) developed a RP-HPLC method for Dasatinib using a C 18 column with Methanol and Acetonitrile (50:50), showing good linearity (2–10 µg/mL, R² = 0.999) (35). as shown in Table 1. 2.1.2 Estimation technique by LC-MS Sandip Gurav et al. (2011) developed a sensitive LC-MS/MS method for abiraterone quantification in rat and human plasma using an Atlantis dC 18 column and acetonitrile–ammonium acetate (90:10), achieving a LLOQ of 0.20 ng/mL and linearity over 0.20–201 ng/mL, with validation conforming to FDA guidelines (38). Stefan Buck et al. (2023) simultaneously quantified abiraterone, enzalutamide, and darolutamide in plasma using LC-MS/MS with an Atlantis dC 18 column (4.6 × 50 mm), meeting FDA/EMA standards for therapeutic drug monitoring in prostate cancer patients (39). Lankheeta et al . (2012) established an HPLC-MS/MS method for eight tyrosine kinase inhibitors (TKIs) in human plasma using gradient elution and isotopically labeled standards on a Gemini C 18 column, demonstrating broad linearity and precise quantification for clinical TDM (40). Serena Mazzucchelli et al. (2016) validated an LC-MS/MS method for doxorubicin and its metabolite in mouse biological matrices using a Gemini C 18 column, confirming high accuracy and sensitivity, and applied it to evaluate nanoformulations and tissue distribution in tumor-bearing mice (41), as shown in Table 2. 2.2. Various Green Analytical Techniques 2.2.1 National Environmental Method NEMI was an early method for evaluating the environmental sustainability of analytical procedures. The greenness profile symbol used in this tool is represented by four quadrants. Hazardous materials, corrosive qualities, waste production, and compounds with persistent, bio accumulative, and toxic (PBT) characteristics are among the criteria that each quadrant relates to. The criteria for each quadrant are evaluated as either green or blank based on compliance with predefined standards. This graphic depiction makes it easier for analysts to compare the environmental impact of different analytical techniques and makes future greenness evaluations easier (42). 2.2.2 Eco-Scale Assessment Analytical Tool (ESA) Analytical methods' greenness is evaluated by the ESA tool using a numerical score system. (43). Environmental effects including the use of toxic solvents, excessive energy consumption, and waste generation are reduced (penalty points) in the best green analytical procedure, which receives a score of 100. Methods are classified as: Green: more than 75 points overall Reasonably green: 50–75 points overall Minimal green analysis: <50 points overall Non-hazardous (0 points), less severe (1 point), and severe (2 points) are the three penalty points indicate the extent of chemical danger. This tool offers a quantitative way to evaluate the environmental sustainability of analytical techniques (44, 45). 2.2.3 Green Analytical Procedure Index (GAPI) A systematic ecological assessment of analytical processes is provided by GAPI, including every phase from sample collection to final analysis (46). This tool employs a color-coded pictogram with sections marked green (eco-friendly), yellow, or red (non-eco-friendly), resembling traffic signals. The GAPI pictogram consists of five main sections subdivided into 15 detailed categories: sample preparation parameters: collection, preservation, transportation, storage, extraction scale, reagent consumption, technique type (direct/indirect), and further treatments Solvent and reagent parameters: Safety issues, health risks, and quantity utilized. Instrumentation factors include waste generation, waste treatment, energy consumption, and occupational risks Quantification mark: A central circle indicating quantitative analytical techniques This system provides both general and semi-quantitative insights into the greenness of analytical procedures. 2.2.4 Analytical GREEnness Metric (AGREE) A new tool for evaluating greenness, AGREE was unveiled by Pena-Pereira et al . in 2020 This software relies on the 12 principles of Green Analytical Chemistry (SIGNIFICANCE) as its foundation. The AGREE metric produces a pictogram divided into 12 sections, with adjustable widths to reflect the relative importance of each criterion. Every component is color-coded, with deep red (0 denoting poor greenness) and deep green (1 indicating outstanding greenness) being the extremes. The center of the circular pictogram displays a number between 0 and 1, which represents the total score. By emphasizing inclusivity, flexibility, simplicity, and clarity, AGREE empowers users to assess analytical approaches in a thorough manner. This tool has been applied to 16 analytical methods Anti-Cancer, generating full reports with colored pictograms for comparison with other greenness assessment tools (47). 2.2.5 BAGI The newly created Blue Analytical Greenness Index (BAGI), in contrast to instruments that just evaluate greenness, provides a quantitative assessment of an analytical method's "blueness," which is based on several important practical aspects. BAGI considers ten primary factors to provide a thorough evaluation of the blueness or overall suitability of an analytical method: the type of analysis, the number of analytes, the number of samples analysed in an hour, the reagents used, the necessary equipment, the number of samples processed simultaneously, the pre-concentration steps, the atomisation level, the sample quantity, and the preparation process. Pictograms having a centre numerical value are generated by the BAGI assessment. Dark blue denotes strong adherence, blue denotes moderate adherence, light blue denotes weak adherence, and white denotes non-compliance. In the center of the pictogram is the total blueness score of the analytical process, which ranges from 25 to 100. A score of 100 denotes exceptional achievement, while a score of 25 represents the least effective strategy (48). 3. Results The reported methods were evaluated using the AGREE, GAPI, AGREEprep, ESA, and BAGI tools. Scores were calculated for each method using these software tools, and the results are presented in the Tables 3 & 4. 4. Discussion In green analytical method development, the selection of environmentally benign solvents is critical to minimizing ecological and health risks. Solvents such as acetonitrile, methanol, and tetrahydrofuran (THF), as well as additives like orthophosphoric acid and sulfonic acid-based buffers, should be avoided due to their high toxicity, poor biodegradability, and significant environmental burden. Mobile phases with acetonitrile content exceeding 50%, methanol–acetonitrile mixtures, or phosphate/sulfonic acid buffers are particularly detrimental to method greenness. These components not only pose safety hazards but also complicate waste treatment and disposal. To improve sustainability, it is advisable to utilize water-rich solvent systems, bio-derived solvents such as ethanol, and greener buffers like ammonium formate or ammonium acetate, which offer lower toxicity and better environmental compatibility. Avoiding hazardous solvents is essential for aligning analytical methods with the principles of Green Analytical Chemistry, thereby promoting safer, more sustainable, and environmentally responsible laboratory practices. The collective results derived from five greenness assessment tools for various selective anticancer drugs are presented in the Table 3 , 4 . The critical findings from these evaluations are analyzed and summarized as follows. Various chromatographic techniques employed for the analysis of anticancer drugs in different dosage forms were systematically evaluated using five green analytical assessment tools: Analytical GREEnness metric (AGREE), Green Analytical Procedure Index (GAPI), AGREEprep, Analytical Eco-Scale (ESA), and Blue Applicability Grade Index (BAGI). These tools offer an extensive evaluation of the sustainability and environmental effect of the analytical approaches used. The AGREE tool quantifies the greenness of analytical methods by evaluating key parameters such as reagent consumption, waste generation, energy utilization, procedural complexity, and automation potential. These factors collectively determine an overall greenness score. The AGREE scores obtained for the investigated methods-HPLC-1, HPLC-2, LC-MS-3, and HPLC-8 were 0.60, 0.64, 0.61, and 0.56, respectively.. A moderate green tint indicated strong alignment with the other four evaluation tools. The GAPI tool offers a visual representation of the environmental impact and safety of analytical procedures. It is extensively utilized to evaluate the greenness of various stages within analytical methodologies. The pentagrams used in the GAPI index are divided into subsections and are categorized as green, yellow, or red according to the degree of environmental sustainability. With the largest percentage of green and yellow subsections among those evaluated were HPLC-1, LC-MS-2, LC-MS-3, and HPLC-8 demonstrated the best environmental performance in comparison to the other approaches examined. An analytical procedure's overall greenness is largely dependent on sample preparation, which is a critical part of the analytical process. AGREEprep is the first measure specifically created to evaluate how sample preparation techniques affect the environment. This tool integrates a ten-step evaluation aligned with the principles of green sample preparation and utilizes open-source software for data computation and visualization. AGREEprep employs a weighted scoring approach, generating a circular pictogram where a central circle displays the overall score, and ten trapezoidal bars correspond to individual criteria. The AGREEprep scores for obtained for the investigated methods HPLC-1, LC-MS-2, HPLC-7, LC-MS-3, and HPLC-8 were 0.56, 0.55, 0.61, 0.61, and 0.62, respectively, highlighting their minimal environmental footprint compared to the remaining methods. A novel tool called the Analytical Eco-Scale assigns penalty points to non-green characteristics to thoroughly assess the greenness of analytical procedures. The final eco-score is calculated by subtracting the assigned penalty points from a maximum score of 100; scores more than 75 signify an extraordinarily high degree of greenness. Sixteen techniques received Analytical Eco-Scale ratings more than 75. Comparing this tool against the more descriptive GAPI, AGREE, and BAGI tools, however, revealed that it was the least successful in evaluating greenness. A recently suggested metric for assessing the usefulness and applicability of analytical techniques is the Blue Applicability Grade Index (BAGI). BAGI is mainly concerned with the operational elements of White Analytical Chemistry and is used as a supplement to current greenness measures. Using an asteroid pictogram, the tool places characteristics 1–5 (which correspond to the processes of analytical determination and sample preparation) in the inner portion and attributes 6–10 (which relate to both stages) in the outside section. Using Matplotlib's 'Blues' sequential colormap, the BAGI scores for methods HPLC-1, LC-MS-2, HPLC-7, LC-MS-3, and HPLC-8 were 72.5, 70.0, 75.0, 70.0, and 75.0, respectively. These values indicate the superior practicality and applicability of these methods compared to the other assessed techniques. In conclusion, the integration of multiple greenness assessment tools provides a robust and multidimensional evaluation of the environmental sustainability of analytical methodologies for anticancer drugs. Among the investigated techniques, methods HPLC-1, LC-MS-2, HPLC-7, LC-MS-3, and HPLC-8 exhibited superior greenness and practicality based on AGREE, GAPI, AGREEprep, Analytical Eco-Scale, and BAGI assessments, establishing them as preferable choices for environmentally sustainable analytical practices. To further advance the sustainability of analytical method development, future efforts should focus on the systematic replacement of hazardous chemicals with safer, greener alternatives. This can be achieved by prioritizing solvent selection tools such as GAPI (Green Analytical Procedure Index), AGREE (Analytical GREEnness metric), and NEMI (National Environmental Methods Index) during the method design phase to assess environmental impact early in development. Emphasis should be placed on using water as a primary solvent wherever feasible and integrating bio-based solvents like ethanol or ethyl lactate instead of toxic organic solvents such as acetonitrile or THF. Additionally, miniaturization of analytical techniques, such as microscale sample preparation and lab-on-a-chip technologies, can significantly reduce chemical consumption and waste. Method optimization should also consider pH-adjustable, volatile, and biodegradable buffers, while computational approaches and machine learning may aid in predicting greener method conditions. Collectively, these strategies can guide the development of safer, eco-friendly analytical procedures. 5. Conclusion Over the last thirty years, various analytical techniques have been used, particularly High-Performance Liquid Chromatography (HPLC) and Liquid Chromatography–Mass Spectrometry (LC-MS), to determine anticancer pharmaceuticals in drug formulations and biological matrices. All these methods have supported pharmacokinetic and pharmacodynamic studies as well as the therapeutic drug monitoring of patients while emphasizing the importance of safe laboratory practice and environmental sustainability. Significantly, none of the analytical methods mentioned in the reviewed literature used green solvents, pointing to a significant void in eco-friendly analytical practices. The greenness metrics and additional figures of merit should be included in the ICH guidelines for the validation of analytical methods. This will improve safety for analysts and protect the environment more, which in turn will encourage a greater use of sustainable analytical approaches in pharmaceutical research and development. Declarations Ethics approval and consent to participate Not Applicable Conflicts of interest The authors declare no conflicts of interest. Consent for publication Not applicable. Funding No external funding was received. Author Contribution H.S. and J.J. conceptualized and designed the study, and conducted the data collection. H.S., J.J., P.K., and P.G. contributed to the data analysis. H.S. wrote the main manuscript text, and J.J. prepared all figures and tables. P.K. and P.G. reviewed and edited the manuscript. Acknowledgement The authors thank the management of the M.S. Ramaiah University of Applied Sciences, Bangalore, Karnataka, India, for providing all the required research facilities. Data Availability All the data are incorporated in the manuscript file. 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Tables Tables 1 to 4 are available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files Tables.docx Cite Share Download PDF Status: Published Journal Publication published 13 Jan, 2026 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 30 Nov, 2025 Reviews received at journal 06 Nov, 2025 Reviews received at journal 06 Nov, 2025 Reviews received at journal 04 Nov, 2025 Reviewers agreed at journal 01 Nov, 2025 Reviewers agreed at journal 30 Oct, 2025 Reviewers agreed at journal 28 Oct, 2025 Reviewers invited by journal 28 Oct, 2025 Editor invited by journal 23 Oct, 2025 Editor assigned by journal 15 Oct, 2025 Submission checks completed at journal 15 Oct, 2025 First submitted to journal 14 Oct, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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10:13:03","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":6803625,"visible":true,"origin":"","legend":"","description":"","filename":"Tables.docx","url":"https://assets-eu.researchsquare.com/files/rs-7860826/v1/e5469e7b8b85e0c7d66556f0.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Green Analytical Evaluation of Anticancer Drugs: A Multi-Tool Assessment of HPLC and LC-MS Methods","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eCancer is one of the leading causes of death worldwide, second only to heart disease, with millions of lives lost each year. The number of cancer cases has been steadily rising over the years\u0026mdash;from 12.7\u0026nbsp;million in 2008 to 14.1\u0026nbsp;million in 2012, and by 2018, there were 18.1\u0026nbsp;million new cases and 9.6\u0026nbsp;million deaths (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). In 2022, that number jumped to an estimated 20\u0026nbsp;million new cases and 9.7\u0026nbsp;million deaths. On a more hopeful note, around 53.5\u0026nbsp;million people were living five years after a cancer diagnosis, showing that more people are surviving cancer thanks to advances in treatment. But the statistics are still sobering\u0026mdash;about 1 in 5 people will develop cancer in their lifetime, and roughly 1 in 9 men and 1 in 12 women will die from it. Looking ahead, it\u0026rsquo;s predicted that by 2050, there will be over 35\u0026nbsp;million new cancer cases each year 77% increase from 2022. This dramatic rise underscores the urgent need for better prevention, early detection, and treatment worldwide (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003ecancer treatments vary, ranging from localized approaches like surgery and radiation, which target specific tumors, to systemic therapies such as chemotherapy, immunotherapy, and targeted therapy that affect the entire body. While chemotherapy broadly refers to cancer-fighting medications, anticancer agents encompass various groups\u0026mdash;including natural products, alkylating agents, antimetabolites, and hormones\u0026mdash;each with distinct mechanisms of action. Novel agents within these drug categories are in advanced stages of clinical development, driven by the growing demand for more effective treatments. To support this progress, highly sensitive analytical techniques such as electrophoresis, chromatography, spectroscopy, and electrochemical methods are essential for accurate quantitative analysis (\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAccurate analytical methods for the therapeutic drug monitoring (TDM) of anticancer medications are essential to maximize clinical outcomes. In therapeutic settings, pharmacokinetic (PK) investigations help determine the appropriate drug dosages and dosing intervals for cancer patients. These methods and studies are particularly crucial because many anticancer drugs have narrow therapeutic windows, exhibit high interpatient variability, and pose significant toxicity risks. accurate TDM \u0026amp;PK data enable safe, effective, and personalized treatment, ultimately improving therapeutic efficacy and minimizing adverse effects (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eScientific research, ecological education, economic tools (such as revenues and subsidies), environmental monitoring, and legislative systems to control resource management and advance sustainable development are all part of the global implementation of pro-ecological policies. According to the World Commission on Environment and Development, sustainable eco-development was first proposed in 1987 (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). emphasizing the need to balance economic growth, environmental preservation, and public health. Sustainable development is particularly relevant to chemists, as reflected in green chemistry principles (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e), which emerged after the US Congress passed the Pollution Prevention Act of 1990 (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Paul Anastas introduced the term green chemistry in 1991 as part of an Environmental Protection Agency initiative (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e), leading to the establishment of the US Green Chemistry Program in 1993, which promotes global collaboration and education in sustainable practices (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eGreen chemistry is essential to address the environmental, health, and economic issues caused by traditional chemical practices. Conventional processes often generate hazardous waste and release pollutants, leading to climate change, biodiversity loss, and ecosystem damage. Exposure to toxic chemicals also increases risks of cancer, respiratory diseases, and neurological disorders. Additionally, traditional methods heavily rely on non-renewable resources such as fossil fuels, leading to resource depletion and inefficiencies like low atom economy and high material waste. Green chemistry focuses on renewable feedstocks, energy-efficient processes, and waste reduction, promoting long-term sustainability (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eEconomically, green chemistry reduces costs by minimizing hazardous waste management and energy consumption. It also opens new markets for eco-friendly products as consumer demand shifts toward sustainability. Stricter regulations, including REACH (EU) and TSCA (USA), further necessitate the adoption of safer chemical processes to ensure compliance and competitiveness (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Beyond regulation and economics, green chemistry embodies ethical scientific responsibility by designing safer products and processes that minimize harm. It supports several United Nations Sustainable Development Goals (SDGs), notably good health, clean water, responsible consumption, and climate action. Thus, green chemistry is not merely an innovation but a necessity for safeguarding health, protecting the environment, and advancing sustainable development (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe current trend in analytical method development for HPLC and LC-MS is a shift towards greener and more sustainable solvent choices, driven by environmental and regulatory concerns. Water and ethanol are increasingly favoured as primary solvents. Techniques like miniaturization and UHPLC are being used to reduce solvent consumption. The integration of LC-MS often requires specific solvents compatible with mass spectrometry detection (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eGreen Analytical Chemistry (GAC) principles are guiding the adoption of solvents like water, ethanol, and other bio-based options. Various green solvent types, including supercritical CO\u003csub\u003e2\u003c/sub\u003e, ionic liquids, and deep eutectic solvents, have potential applications in HPLC and LC-MS. Challenges remain in terms of solvent compatibility with analytes and LC-MS systems, method validation, and the need to replace traditional solvents like acetonitrile effectively. Regulatory frameworks like ICH guidelines also influence solvent use (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Economically, green solvents are becoming more attractive, especially when considering reduced waste disposal costs. Solvent recycling programs are also gaining importance. Emerging solvent technologies like ionic liquids and deep eutetic solvents are being explored for HPLC and LC-MS applications. Automation and advancements in column technology are also contributing to more efficient solvent use in these techniques (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eDespite these advancements, no consensus exists on standardized criteria for evaluating analytical method greenness, risking GAC's practical application. However, the importance of sustainability in analytical chemistry is widely recognized, with efforts to extend its benefits to underserved regions through modified strategies and methods.\u003c/p\u003e\u003cp\u003eNo universal standard for greenness of an analytical method has been developed, which further continues to limit the practical adoption of GAC. Although total removal of solvents is the ideal approach, in reality, solutions are more aimed at reducing harmful solvents or substitutes with greener alternatives. In an ideal green solvent should exhibit low toxicity, biodegradability, reusability, sustainability and good analytical performance. GAPI, Analytical Eco-Scale and AGREE are examples of tools that provide structured and objective evaluations regarding environmental impacts due to factors like solvent usage waste energy consumption and operator safety. The systematic application of such tools allows researchers to point out the less sustainable elements in current methods and rectify them. This becomes especially important in the pharmaceutical industry as well as oncology research where accuracy has to go hand in hand with sustainable environment. Some criteria of greenness should be integrated into regulatory frameworks as a way forward; tool-based assessment shall pave ways towards sustainable transitions in analytical practices. This study presents a new evaluation framework for analytical techniques employed in the assessment of antineoplastic agents, which goes beyond traditional validation criteria and includes wider methodological as well as sustainability aspects.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\"\u003e\n \u003ch2\u003e2.1 Estimation techniques reported for anti-cancer drugs by HPLC and LC-MS\u003c/h2\u003e\n \u003cdiv\u003e\n \u003cp\u003eHPLC and LC-MS are widely employed liquid chromatographic method due to their high separation capacity, making it suitable for analyzing anticancer drugs (19). In pharmaceutical drug research, there chromatography methods are often used, especially for the study of pharmaceuticals in biological matrices (20, 21). Organic solvents like ACN or MeOH combined with volatile buffers or acids (such acetic acid, ammonium acetate, or ammonium formate) in gradient or isocratic elution regimes make up common mobile phases.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec4\"\u003e\n \u003ch2\u003e2.1.1 Estimation technique by HPLC\u003c/h2\u003e\n \u003cp\u003eBarrawaz Aateka Yahya \u003cem\u003eet al.\u003c/em\u003e (2021) developed a QbD-based RP-HPLC method for Abiraterone Acetate using a C\u003csub\u003e18\u003c/sub\u003e column with acetonitrile\u0026ndash;ammonium acetate (69:31), showing good linearity (10\u0026ndash;180 \u0026micro;g/mL, R\u0026sup2; = 0.997), precision, and suitability for bulk, tablets, and nano-formulations (22). Sarwar Beg \u003cem\u003eet al.\u003c/em\u003e (2021) also used a QbD approach with a Hypersil BDS C18 column and acetonitrile\u0026ndash;water (15:85), achieving excellent recovery (99.8\u0026ndash;100.2%) and identifying degradation products under stress conditions (23). Ravi Sankar \u003cem\u003eet al.\u003c/em\u003e (2021) developed a precise method using methanol\u0026ndash;acetonitrile (50:50) with a linearity of 2\u0026ndash;10 \u0026micro;g/mL and high recovery (99.78%) (24). Tiphaine Belleville \u003cem\u003eet al.\u003c/em\u003e (2015) introduced a sensitive HPLC-fluorescence method for abiraterone in plasma (1.75\u0026ndash;50 ng/mL) using acetonitrile\u0026ndash;glycine buffer and fluorescence detection (\u0026lambda;ex/em: 255/373 nm), enabling clinical monitoring (25). Vijay Kumar Sripuram \u003cem\u003eet al.\u003c/em\u003e (2010) established a robust RP-HPLC method for doxorubicin in plasma with 99.8% recovery and excellent linearity over 0.2\u0026ndash;10 \u0026micro;g/mL using a water\u0026ndash;acetonitrile (75:25) mobile phase (26). Vanesa Escudero-Ortiz \u003cem\u003eet al\u003c/em\u003e. (2013) quantified lapatinib in plasma using acetonitrile\u0026ndash;ammonium acetate (53:47), showing\u0026thinsp;\u0026gt;\u0026thinsp;86.7% recovery and good precision (27). Mistiran \u003cem\u003eet al.\u003c/em\u003e (2010) reported a method for Ara-C and doxorubicin using acetonitrile\u0026ndash;ammonium hydrogen phosphate (45:55), with strong precision and accuracy (28). Ebrahim Saadat \u003cem\u003eet al.\u003c/em\u003e (2015) validated a rapid HPLC method for paclitaxel and lapatinib in micelles using acetonitrile\u0026ndash;water (70:30), showing linearity (5\u0026ndash;80 \u0026micro;g/mL) and precision (RSD\u0026thinsp;\u0026lt;\u0026thinsp;5.83%) (29). Laura Zuf\u0026iacute;a L\u0026oacute;pez \u003cem\u003eet al\u003c/em\u003e. (2006) developed an HPLC-UV method for docetaxel and paclitaxel in plasma with high recovery (~\u0026thinsp;88\u0026ndash;91%) and a low LLOQ (0.015 mg/L), suitable for pharmacokinetics (30). Xinran Chen \u003cem\u003eet al.\u003c/em\u003e (2022) established a UPLC-MS/MS method for simultaneous quantification of five drugs in plasma with high accuracy and stability, supporting clinical drug monitoring (31). G\u0026ouml;knil Pelin Coşkun \u003cem\u003eet al.\u003c/em\u003e (2022) developed a HPLC method for Imatinib using a C\u003csub\u003e18\u003c/sub\u003e column with acetonitrile and TEA/phosphate buffer (pH: 7.04; 0.1 M) (50:50, v/v) showing good linearity (10\u0026ndash;90 \u0026micro;g/mL, R\u0026sup2; = 0.999) (32). Silvia De Francia \u003cem\u003eet al.\u003c/em\u003e (2022) introduced a sensitive HPLC method for imatinib, dasatinib, and nilotinib in human plasma, using acetonitrile and water\u0026thinsp;+\u0026thinsp;formic acid 0.05% (33). MD Nazmus Sakib \u003cem\u003eet al.\u003c/em\u003e (2023) reported a method for rifampicin using 60% acetate buffer (pH 4.5) and 40% acetonitrile, with strong precision and accuracy (34). Panchumarthy Ravi Sankar \u003cem\u003eet al.\u003c/em\u003e (2019) developed a RP-HPLC method for Dasatinib using a C\u003csub\u003e18\u003c/sub\u003e column with Methanol and Acetonitrile (50:50), showing good linearity (2\u0026ndash;10 \u0026micro;g/mL, R\u0026sup2; = 0.999) (35). as shown in Table\u0026nbsp;1.\u003c/p\u003e\n \u003cdiv\u003e\u003c/div\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec5\"\u003e\n \u003ch2\u003e2.1.2 Estimation technique by LC-MS\u003c/h2\u003e\n \u003cp\u003eSandip Gurav \u003cem\u003eet al.\u003c/em\u003e (2011) developed a sensitive LC-MS/MS method for abiraterone quantification in rat and human plasma using an Atlantis dC\u003csub\u003e18\u003c/sub\u003e column and acetonitrile\u0026ndash;ammonium acetate (90:10), achieving a LLOQ of 0.20 ng/mL and linearity over 0.20\u0026ndash;201 ng/mL, with validation conforming to FDA guidelines (38). Stefan Buck \u003cem\u003eet al.\u003c/em\u003e (2023) simultaneously quantified abiraterone, enzalutamide, and darolutamide in plasma using LC-MS/MS with an Atlantis dC\u003csub\u003e18\u003c/sub\u003e column (4.6 \u0026times; 50 mm), meeting FDA/EMA standards for therapeutic drug monitoring in prostate cancer patients (39). Lankheeta \u003cem\u003eet al\u003c/em\u003e. (2012) established an HPLC-MS/MS method for eight tyrosine kinase inhibitors (TKIs) in human plasma using gradient elution and isotopically labeled standards on a Gemini C\u003csub\u003e18\u003c/sub\u003e column, demonstrating broad linearity and precise quantification for clinical TDM (40). Serena Mazzucchelli \u003cem\u003eet al.\u003c/em\u003e (2016) validated an LC-MS/MS method for doxorubicin and its metabolite in mouse biological matrices using a Gemini C\u003csub\u003e18\u003c/sub\u003e column, confirming high accuracy and sensitivity, and applied it to evaluate nanoformulations and tissue distribution in tumor-bearing mice (41), as shown in Table\u0026nbsp;2.\u003c/p\u003e\n \u003cdiv\u003e\u003c/div\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec6\"\u003e\n \u003ch2\u003e2.2. Various Green Analytical Techniques\u003c/h2\u003e\n \u003cdiv id=\"Sec7\"\u003e\n \u003ch2\u003e2.2.1 National Environmental Method\u003c/h2\u003e\n \u003cp\u003eNEMI was an early method for evaluating the environmental sustainability of analytical procedures. The greenness profile symbol used in this tool is represented by four quadrants. Hazardous materials, corrosive qualities, waste production, and compounds with persistent, bio accumulative, and toxic (PBT) characteristics are among the criteria that each quadrant relates to. The criteria for each quadrant are evaluated as either green or blank based on compliance with predefined standards. This graphic depiction makes it easier for analysts to compare the environmental impact of different analytical techniques and makes future greenness evaluations easier (42).\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec8\"\u003e\n \u003ch2\u003e2.2.2 Eco-Scale Assessment Analytical Tool (ESA)\u003c/h2\u003e\n \u003cp\u003eAnalytical methods\u0026apos; greenness is evaluated by the ESA tool using a numerical score system. (43). Environmental effects including the use of toxic solvents, excessive energy consumption, and waste generation are reduced (penalty points) in the best green analytical procedure, which receives a score of 100.\u003c/p\u003e\n \u003cp\u003eMethods are classified as:\u003c/p\u003e\n \u003cul\u003e\n \u003cli\u003e\n \u003cp\u003eGreen: more than 75 points overall\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eReasonably green: 50\u0026ndash;75 points overall\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eMinimal green analysis: \u0026lt;50 points overall\u003c/p\u003e\n \u003c/li\u003e\n \u003c/ul\u003e\n \u003cp\u003eNon-hazardous (0 points), less severe (1 point), and severe (2 points) are the three penalty points indicate the extent of chemical danger. This tool offers a quantitative way to evaluate the environmental sustainability of analytical techniques (44, 45).\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec9\"\u003e\n \u003ch2\u003e2.2.3 Green Analytical Procedure Index (GAPI)\u003c/h2\u003e\n \u003cp\u003eA systematic ecological assessment of analytical processes is provided by GAPI, including every phase from sample collection to final analysis (46). This tool employs a color-coded pictogram with sections marked green (eco-friendly), yellow, or red (non-eco-friendly), resembling traffic signals.\u003c/p\u003e\n \u003cp\u003eThe GAPI pictogram consists of five main sections subdivided into 15 detailed categories:\u003c/p\u003e\n \u003cul\u003e\n \u003cli\u003e\n \u003cp\u003esample preparation parameters: collection, preservation, transportation, storage, extraction scale, reagent consumption, technique type (direct/indirect), and further treatments\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eSolvent and reagent parameters: Safety issues, health risks, and quantity utilized.\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eInstrumentation factors include waste generation, waste treatment, energy consumption, and occupational risks\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eQuantification mark: A central circle indicating quantitative analytical techniques\u003c/p\u003e\n \u003c/li\u003e\n \u003c/ul\u003e\n \u003cp\u003eThis system provides both general and semi-quantitative insights into the greenness of analytical procedures.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec10\"\u003e\n \u003ch2\u003e2.2.4 Analytical GREEnness Metric (AGREE)\u003c/h2\u003e\n \u003cp\u003eA new tool for evaluating greenness, AGREE was unveiled by Pena-Pereira \u003cem\u003eet al\u003c/em\u003e. in 2020 This software relies on the 12 principles of Green Analytical Chemistry (SIGNIFICANCE) as its foundation. The AGREE metric produces a pictogram divided into 12 sections, with adjustable widths to reflect the relative importance of each criterion. Every component is color-coded, with deep red (0 denoting poor greenness) and deep green (1 indicating outstanding greenness) being the extremes. The center of the circular pictogram displays a number between 0 and 1, which represents the total score. By emphasizing inclusivity, flexibility, simplicity, and clarity, AGREE empowers users to assess analytical approaches in a thorough manner. This tool has been applied to 16 analytical methods Anti-Cancer, generating full reports with colored pictograms for comparison with other greenness assessment tools (47).\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec11\"\u003e\n \u003ch2\u003e2.2.5 BAGI\u003c/h2\u003e\n \u003cp\u003eThe newly created Blue Analytical Greenness Index (BAGI), in contrast to instruments that just evaluate greenness, provides a quantitative assessment of an analytical method\u0026apos;s \u0026quot;blueness,\u0026quot; which is based on several important practical aspects. BAGI considers ten primary factors to provide a thorough evaluation of the blueness or overall suitability of an analytical method: the type of analysis, the number of analytes, the number of samples analysed in an hour, the reagents used, the necessary equipment, the number of samples processed simultaneously, the pre-concentration steps, the atomisation level, the sample quantity, and the preparation process.\u003c/p\u003e\n \u003cp\u003ePictograms having a centre numerical value are generated by the BAGI assessment. Dark blue denotes strong adherence, blue denotes moderate adherence, light blue denotes weak adherence, and white denotes non-compliance. In the center of the pictogram is the total blueness score of the analytical process, which ranges from 25 to 100. A score of 100 denotes exceptional achievement, while a score of 25 represents the least effective strategy (48).\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003eThe reported methods were evaluated using the AGREE, GAPI, AGREEprep, ESA, and BAGI tools. Scores were calculated for each method using these software tools, and the results are presented in the Tables\u0026nbsp;3 \u0026amp; 4.\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eIn green analytical method development, the selection of environmentally benign solvents is critical to minimizing ecological and health risks. Solvents such as acetonitrile, methanol, and tetrahydrofuran (THF), as well as additives like orthophosphoric acid and sulfonic acid-based buffers, should be avoided due to their high toxicity, poor biodegradability, and significant environmental burden. Mobile phases with acetonitrile content exceeding 50%, methanol\u0026ndash;acetonitrile mixtures, or phosphate/sulfonic acid buffers are particularly detrimental to method greenness. These components not only pose safety hazards but also complicate waste treatment and disposal. To improve sustainability, it is advisable to utilize water-rich solvent systems, bio-derived solvents such as ethanol, and greener buffers like ammonium formate or ammonium acetate, which offer lower toxicity and better environmental compatibility. Avoiding hazardous solvents is essential for aligning analytical methods with the principles of Green Analytical Chemistry, thereby promoting safer, more sustainable, and environmentally responsible laboratory practices.\u003c/p\u003e\u003cp\u003eThe collective results derived from five greenness assessment tools for various selective anticancer drugs are presented in the Table \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e,\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. The critical findings from these evaluations are analyzed and summarized as follows.\u003c/p\u003e\u003cp\u003eVarious chromatographic techniques employed for the analysis of anticancer drugs in different dosage forms were systematically evaluated using five green analytical assessment tools: Analytical GREEnness metric (AGREE), Green Analytical Procedure Index (GAPI), AGREEprep, Analytical Eco-Scale (ESA), and Blue Applicability Grade Index (BAGI). These tools offer an extensive evaluation of the sustainability and environmental effect of the analytical approaches used.\u003c/p\u003e\u003cp\u003eThe AGREE tool quantifies the greenness of analytical methods by evaluating key parameters such as reagent consumption, waste generation, energy utilization, procedural complexity, and automation potential. These factors collectively determine an overall greenness score. The AGREE scores obtained for the investigated methods-HPLC-1, HPLC-2, LC-MS-3, and HPLC-8 were 0.60, 0.64, 0.61, and 0.56, respectively.. A moderate green tint indicated strong alignment with the other four evaluation tools.\u003c/p\u003e\u003cp\u003eThe GAPI tool offers a visual representation of the environmental impact and safety of analytical procedures. It is extensively utilized to evaluate the greenness of various stages within analytical methodologies. The pentagrams used in the GAPI index are divided into subsections and are categorized as green, yellow, or red according to the degree of environmental sustainability. With the largest percentage of green and yellow subsections among those evaluated were HPLC-1, LC-MS-2, LC-MS-3, and HPLC-8 demonstrated the best environmental performance in comparison to the other approaches examined.\u003c/p\u003e\u003cp\u003eAn analytical procedure's overall greenness is largely dependent on sample preparation, which is a critical part of the analytical process. AGREEprep is the first measure specifically created to evaluate how sample preparation techniques affect the environment. This tool integrates a ten-step evaluation aligned with the principles of green sample preparation and utilizes open-source software for data computation and visualization. AGREEprep employs a weighted scoring approach, generating a circular pictogram where a central circle displays the overall score, and ten trapezoidal bars correspond to individual criteria. The AGREEprep scores for obtained for the investigated methods HPLC-1, LC-MS-2, HPLC-7, LC-MS-3, and HPLC-8 were 0.56, 0.55, 0.61, 0.61, and 0.62, respectively, highlighting their minimal environmental footprint compared to the remaining methods.\u003c/p\u003e\u003cp\u003eA novel tool called the Analytical Eco-Scale assigns penalty points to non-green characteristics to thoroughly assess the greenness of analytical procedures. The final eco-score is calculated by subtracting the assigned penalty points from a maximum score of 100; scores more than 75 signify an extraordinarily high degree of greenness.\u003c/p\u003e\u003cp\u003eSixteen techniques received Analytical Eco-Scale ratings more than 75. Comparing this tool against the more descriptive GAPI, AGREE, and BAGI tools, however, revealed that it was the least successful in evaluating greenness.\u003c/p\u003e\u003cp\u003eA recently suggested metric for assessing the usefulness and applicability of analytical techniques is the Blue Applicability Grade Index (BAGI). BAGI is mainly concerned with the operational elements of White Analytical Chemistry and is used as a supplement to current greenness measures. Using an asteroid pictogram, the tool places characteristics 1\u0026ndash;5 (which correspond to the processes of analytical determination and sample preparation) in the inner portion and attributes 6\u0026ndash;10 (which relate to both stages) in the outside section. Using Matplotlib's 'Blues' sequential colormap, the BAGI scores for methods HPLC-1, LC-MS-2, HPLC-7, LC-MS-3, and HPLC-8 were 72.5, 70.0, 75.0, 70.0, and 75.0, respectively. These values indicate the superior practicality and applicability of these methods compared to the other assessed techniques.\u003c/p\u003e\u003cp\u003eIn conclusion, the integration of multiple greenness assessment tools provides a robust and multidimensional evaluation of the environmental sustainability of analytical methodologies for anticancer drugs. Among the investigated techniques, methods HPLC-1, LC-MS-2, HPLC-7, LC-MS-3, and HPLC-8 exhibited superior greenness and practicality based on AGREE, GAPI, AGREEprep, Analytical Eco-Scale, and BAGI assessments, establishing them as preferable choices for environmentally sustainable analytical practices.\u003c/p\u003e\u003cp\u003eTo further advance the sustainability of analytical method development, future efforts should focus on the systematic replacement of hazardous chemicals with safer, greener alternatives. This can be achieved by prioritizing solvent selection tools such as GAPI (Green Analytical Procedure Index), AGREE (Analytical GREEnness metric), and NEMI (National Environmental Methods Index) during the method design phase to assess environmental impact early in development. Emphasis should be placed on using water as a primary solvent wherever feasible and integrating bio-based solvents like ethanol or ethyl lactate instead of toxic organic solvents such as acetonitrile or THF. Additionally, miniaturization of analytical techniques, such as microscale sample preparation and lab-on-a-chip technologies, can significantly reduce chemical consumption and waste. Method optimization should also consider pH-adjustable, volatile, and biodegradable buffers, while computational approaches and machine learning may aid in predicting greener method conditions. Collectively, these strategies can guide the development of safer, eco-friendly analytical procedures.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eOver the last thirty years, various analytical techniques have been used, particularly High-Performance Liquid Chromatography (HPLC) and Liquid Chromatography\u0026ndash;Mass Spectrometry (LC-MS), to determine anticancer pharmaceuticals in drug formulations and biological matrices. All these methods have supported pharmacokinetic and pharmacodynamic studies as well as the therapeutic drug monitoring of patients while emphasizing the importance of safe laboratory practice and environmental sustainability. Significantly, none of the analytical methods mentioned in the reviewed literature used green solvents, pointing to a significant void in eco-friendly analytical practices. The greenness metrics and additional figures of merit should be included in the ICH guidelines for the validation of analytical methods. This will improve safety for analysts and protect the environment more, which in turn will encourage a greater use of sustainable analytical approaches in pharmaceutical research and development.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eEthics approval and consent to participate\u003c/h2\u003e\u003cp\u003eNot Applicable\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConflicts of interest\u003c/strong\u003e\u003cp\u003eThe authors declare no conflicts of interest.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eConsent for publication\u003c/h2\u003e\u003cp\u003eNot applicable.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eNo external funding was received.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eH.S. and J.J. conceptualized and designed the study, and conducted the data collection. H.S., J.J., P.K., and P.G. contributed to the data analysis. H.S. wrote the main manuscript text, and J.J. prepared all figures and tables. P.K. and P.G. reviewed and edited the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe authors thank the management of the M.S. Ramaiah University of Applied Sciences, Bangalore, Karnataka, India, for providing all the required research facilities.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eAll the data are incorporated in the manuscript file.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eOtter, S., Chatterjee, J., Stewart, A. \u0026amp; Michael, A. The role of biomarkers for the prediction of response to checkpoint immunotherapy and the rationale for the use of checkpoint immunotherapy in cervical cancer. \u003cem\u003eClin. Oncol.\u003c/em\u003e \u003cb\u003e31\u003c/b\u003e (12), 834\u0026ndash;843 (2019).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBray, F. et al. 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Blue applicability grade index (BAGI) and software: a new tool for the evaluation of method practicality. \u003cem\u003eGreen Chem.\u003c/em\u003e \u003cb\u003e25\u003c/b\u003e (19), 7598\u0026ndash;7604 (2023).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 to 4 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Anticancer, Greenness, BAGI, AGREE, AGREE prep, ESA, GAPI","lastPublishedDoi":"10.21203/rs.3.rs-7860826/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7860826/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eCancer continues to be a significant health challenge in the world. Anticancer treatments are developing rapidly, but the analytical techniques used to support these treatments in terms of drug development and monitoring often involve hazardous solvents and create much waste compared to other technologies. This study attempt to apply Green Analytical Chemistry principles in high-performance liquid chromatography and liquid chromatography\u0026ndash;mass spectrometry methods for the analysis of anticancer drugs. Sixteen analytical methods were evaluated using five well-known greenness assessment tools: AGREE, GAPI, AGREEprep, Analytical Eco-Scale, and Blue Analytical Greenness Index. These tools provided a comprehensive evaluation of environmental sustainability in relation to reagent toxicity, waste production, energy consumption and preparation of samples. The most environmentally sustainable as well as practically implementable among the assessed methodologies are Methods HPLC-1, LC-MS-2, HPLC-7, LC-MS-3, and HPLC-8. Most methods incorporate toxic solvents acetonitrile and methanol even after great development; greener solvents such as ethanol and water-based systems should replace them more significantly in future strategies. Greenness assessment methods must be integrated into validation/development processes involving safer solvents for sustainability principles upheld while reducing environmental risk together with analytical performance maintenance toward global health success versus ecological preservation.\u003c/p\u003e","manuscriptTitle":"Green Analytical Evaluation of Anticancer Drugs: A Multi-Tool Assessment of HPLC and LC-MS Methods","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-07 19:59:01","doi":"10.21203/rs.3.rs-7860826/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-12-01T04:50:16+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-06T20:55:04+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-06T14:51:51+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-04T07:16:35+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"227059249578073141256832073286209372417","date":"2025-11-01T21:10:00+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"210255979795681949118712787220141037578","date":"2025-10-30T10:13:29+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"141945058471011741211463005573165119749","date":"2025-10-28T13:35:35+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-28T12:45:01+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-10-23T12:15:40+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-15T07:25:00+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-15T07:24:34+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-10-14T16:44:32+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f2d61f65-1017-4a88-b076-f6d0ac4dd533","owner":[],"postedDate":"November 7th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":57577838,"name":"Physical sciences/Chemistry"},{"id":57577839,"name":"Earth and environmental sciences/Environmental sciences"}],"tags":[],"updatedAt":"2026-01-19T17:09:28+00:00","versionOfRecord":{"articleIdentity":"rs-7860826","link":"https://doi.org/10.1038/s41598-025-33868-w","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2026-01-13 16:30:39","publishedOnDateReadable":"January 13th, 2026"},"versionCreatedAt":"2025-11-07 19:59:01","video":"","vorDoi":"10.1038/s41598-025-33868-w","vorDoiUrl":"https://doi.org/10.1038/s41598-025-33868-w","workflowStages":[]},"version":"v1","identity":"rs-7860826","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7860826","identity":"rs-7860826","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}