Eco-friendly chemometric analysis: Sustainable quantification of five pharmaceutical compounds in bulk, tablets, and spiked human plasma

Abstract

The development of sustainable chemometric methodologies is crucial in pharmaceutical analysis to ensure accurate chemical quantification with little environmental effect. This study introduces novel chemometric techniques for the simultaneous measurement of Rabeprazole (RAB), Lansoprazole (LAN), Levofloxacin (LEV), Amoxicillin (AMO), and Paracetamol (PAR) in various samples, including lab-prepared mixtures, tablets, and spiked human plasma. Taguchi L25 (5^5) orthogonal array design to construct the calibration and validation sets was employed, the techniques used named Principal Component Regression (PCR), Partial Least Squares (PLS-2), Artificial Neural Networks (ANNs), and Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS). The models were validated for their effectiveness in resolving complex spectra from overlapping components, the models achieving high correlation coefficients (R≥0.9997) and the relative error of prediction (REP) and root mean square error of prediction (RMSEP), were (0.2221 to 0.8022) and (0.0352 to 0.1767), respectively. The bias-corrected mean square error of prediction (BCMSEP) was (−0.00065 to 0.00166). The application of various assessment tools for evaluating greenness, blueness, and whiteness offered valuable insights into the environmental impact and sustainability of the developed methods compared to the reported ones. According to the Need Quality Sustainability (NQS) index, the developed methods align with sustainable analytical practices and support the United Nations Sustainable Development Goals (UN-SDGs).