Desai Urvish, Christian Jenee, Suhagia B N
Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Dharmsinh Desai University, Nadiad, Gujarat, India.
Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Dharmsinh Desai University, Nadiad, Gujarat, India.
Spectrochim Acta A Mol Biomol Spectrosc. 2025 Feb 15;327:125306. doi: 10.1016/j.saa.2024.125306. Epub 2024 Oct 22.
A UV-Vis spectrophotometric method enhanced by chemometric techniques, specifically Principal Component Regression (PCR) and Partial Least Squares (PLS) regression, was developed and validated for the simultaneous quantification of prasugrel (PRA) and aspirin (ASP) in bulk drugs and pharmaceutical formulations. The method demonstrated high accuracy, precision, and robustness, achieving mean recoveries of 100.63% for PRA and 100.08% for ASP with relative standard deviations (RSD) below 3%. Both PCR and PLS models showed excellent predictive capabilities, with RMSEP values of 0.45-0.48 for PRA and 0.78-1.13 for ASP, indicating the models' reliability. In line with green and white chemistry principles, the method minimizes environmental impact by reducing solvent consumption and waste generation compared to traditional chromatographic methods. The Analytical Eco-Scale score was 84, reflecting excellent compliance with green chemistry standards. The method's simplicity, low energy consumption, and reduced chemical waste further support its alignment with sustainability goals. However, acetonitrile, a hazardous solvent, was still used in small quantities, and solvent recycling was not implemented, slightly affecting the eco-score. To evaluate the method's greenness, the RGB12 algorithm was applied, achieving a high score of 94.4%, with the majority of parameters related to reagent consumption, waste production, energy efficiency, and safety scoring optimally. The method's safety, cost-effectiveness, and minimal environmental footprint make it suitable for routine pharmaceutical analysis, particularly in quality control environments where resource efficiency and sustainability are prioritized. Thus, the developed method offers a sustainable, efficient, and environmentally friendly solution for the simultaneous analysis of prasugrel and aspirin in pharmaceutical formulations, making it a valuable tool for routine analysis in the pharmaceutical industry.
开发了一种通过化学计量技术（特别是主成分回归（PCR）和偏最小二乘（PLS）回归）增强的紫外可见分光光度法，并对其进行了验证，用于同时定量原料药和药物制剂中的普拉格雷（PRA）和阿司匹林（ASP）。该方法具有高准确性、精密度和稳健性，PRA的平均回收率为100.63%，ASP的平均回收率为100.08%，相对标准偏差（RSD）低于3%。PCR和PLS模型均显示出优异的预测能力，PRA的RMSEP值为0.45 - 0.48，ASP的RMSEP值为0.78 - 1.13，表明模型的可靠性。与绿色和白色化学原则一致，与传统色谱方法相比，该方法通过减少溶剂消耗和废物产生，将对环境的影响降至最低。分析生态规模得分为84，反映出对绿色化学标准的优异符合性。该方法的简单性、低能耗和减少的化学废物进一步支持其与可持续发展目标的一致性。然而，仍少量使用了危险溶剂乙腈，且未实施溶剂回收，这对生态得分略有影响。为了评估该方法的绿色度，应用了RGB12算法，获得了94.4%的高分，大多数与试剂消耗、废物产生、能源效率和安全评分相关的参数均达到最佳。该方法的安全性、成本效益和最小的环境足迹使其适用于常规药物分析，特别是在优先考虑资源效率和可持续性的质量控制环境中。因此，所开发的方法为药物制剂中普拉格雷和阿司匹林的同时分析提供了一种可持续、高效且环保的解决方案，使其成为制药行业常规分析的有价值工具。
