The use of green spectroscopy with multivariate calibration models for simultaneous analysis of ternary drug mixture in combined oral antidiabetic pill.

Abstract

In this work, different chemometric calibration models were developed and validated for the purpose of determining of ternary mixture of oral antidiabetic drugs; vildagliptin (VDG), saxagliptin (SAX) and sitagliptin phosphate (STG). The used models were Partial least squares (PLS) and Artificial Neural Networks (ANN). However, on these various models the impact of genetic algorithm (GA) as a form of variable selection was also investigated. The UV spectral data was used as basis in the quantitative study of the drugs analyzed in bulk and product formulations. The concentration range of the calibration curves of VDG, SAX and STG were 10-22μgmL-1, 24-40μgmL-1 and 82-130μgmL-1, respectively. The calibration set included nineteen mixtures and the others six were used as a validation set to test the predictability of the developed multivariate models. The validation parameters of the evaluated methods were statistically determined. For the analysis of drugs studied in laboratory-prepared mixtures and their dosage forms, PLS-1, GA-PLS-1, ANN, and GA-ENN were successfully employed. The results obtained by the developed methods were compared to those given by a reported method and there were no statistically significant differences regarding accuracy and precision.