Multi-spectroscopic assay methods for concurrent determination of recent anti-gout combination, a comparative study

Abstract

Recently, Chemometric calibration methods in spectrophotometric analysis are achieving significant attention in the quality control of resolving drug mixtures and pharmaceutical formulations containing two or more drugs with overlapping spectra. The simple univariate methods have been used over the last few decades and has proven to be highly efficient and easy to apply. In this study, a comparative study was performed between some univariate and multivariate methods to determine if chemometric methods can substitute univariate methods in pharmaceutical analysis. In this study, three chemometric techniques were compared to seven univariate techniques to resolve a mixture of mefenamic acid and febuxostat in their raw materials, dosage forms and spiked human plasma. Mefenamic acid and febuxostat were used together for treatment of gout. The applied chemometric methods are partial least squares (PLS), artificial neural network (ANN) and genetic algorithm partial least squares (GA-PLS), while the used univariate methods include first derivative, second derivative, ratio spectra, derivative ratio spectra, ratio subtraction, Q-Absorbance ratio and mean centering spectrophotometric methods. The ten proposed methods were found to be green, sensitive, and rapid. They are simple and did not require any pre-separation steps. The results of both univariate and multivariate approaches were statistically compared with the reported spectrophotometric methods using student’s t test and ratio variance F-test. They were also compared with each other, using one-way analysis of variance (ANOVA). These methods were assessed and validated according to ICH guidelines. The studied drugs were analyzed in their pharmaceutical dosage forms and spiked human plasma with good recoveries using the developed methods, which qualify them for routine quality control of the studied drugs.