Sci Rep. 2025 Oct 31;15(1):38103. doi: 10.1038/s41598-025-22700-0.
ABSTRACT
Effective management of hypertension typically involves multiple medications. This underscores the pharmaceutical industry's demand for simple, cost-effective, and environmentally sustainable analytical methods capable of handling complex, multicomponent formulations. This study's primary goal was to compare and validate univariate and multivariate spectrophotometric techniques for analyzing fixed-dose antihypertensive formulations of Telmisartan (TEL), Chlorthalidone (CHT), and Amlodipine (AML). Successive Ratio Subtraction paired with Constant Multiplication (SRS-CM) and Successive Derivative Subtraction paired with Constant Multiplication (SDS-CM) were the developed univariate methods. The cited drugs were successfully quantified at their respective maxima: 295.7 nm for TEL, 275.0 nm for CHT, and 359.5 nm for AML. On the other hand, the SDS-CM method enabled their determination using first-derivative spectra, with TEL identified at P nm, CHT at 287.0 nm, and AML at P nm. Also, Interval-Partial Least Squares (iPLS) and Genetic Algorithm-Partial Least Squares (GA-PLS) were applied as multivariate techniques. In contrast to full-spectrum modeling alone, the results showed that adding variable selection techniques greatly improved the model's performance. Following ICH guidelines, the proposed techniques were used to quantify the cited medications in tablets. The validity of the results was confirmed by statistical comparison with the reported method. The study was further expanded to assess the content uniformity of the dosage units in compliance with USP. Three environmental complementary assessment tools were employed: the Analytical Greenness Metric (AGREE), the Blue Applicability Grade Index (BAGI) and White Analytical Chemistry (RGB12). This study also aligns with several UN Sustainable Development Goals (UN-SDGs), emphasizing commitment to green pharmaceutical research. Sustainability was verified using the NQS index, confirming the method's compliance with responsible analytical practices.
PMID:41174021 | PMC:PMC12578892 | DOI:10.1038/s41598-025-22700-0