A Multivariate Approach to the Simultaneous Spectrophotometric Determination of Perindopril Erbumine, Amlodipine Besylate and Indapamide in Fixed-Dose Combination

Spectrophotometry offers the advantage of low cost and less time consumption, making it still attractive as a method of analysis, especially when coupled with multivariate calibration models. This enhancement solves the majority of the drawbacks of UV–VIS spectrophotometry, which have to do with the entangled spectra of complex mixtures. In this study, a multivariate model was developed and validated for the determination of perindopril erbumine, amlodipine besylate and indapamide, addressing previously unresolved challenges by systematically covering three fixed-dose combinations with differing component ratios and by achieving accuracy suitable for the assay determination. The experimental plan involved a Taguchi orthogonal array design with three factors at five levels. In order to create multivariate calibration models, principal component regression, partial least squares and concentration residual augmented least squares regression algorithms were tested. Principal component regression combined with a genetic algorithm for feature selection was chosen as the optimal model based on prediction performance estimated by nested cross-validation with cluster-based sample splitting. The developed method was also evaluated for its environmentally friendly potential while the analytical method validation procedure confirmed its applicability for the assay testing of the fixed-dose drug combination.