Multivariate chemometric assisted analysis of metformin hydrochloride, gliclazide and pioglitazone hydrochloride in bulk drug and dosage forms.

Abstract

In this work a numerical method, based on the use of spectrophotometric data coupled to partial least squares (PLS) regression and net analyte preprocessing combined with classical least square (NAP/CLS) multivariate calibration, is reported for the simultaneous determination of metformin hydrochloride (MET), gliclazide (GLZ) and pioglitazone hydrochloride (PIO) in synthetic samples and combined commercial tablets. Spectra of MET, GLZ and PIO were recorded at concentrations within their linear ranges (5-25 µg/ml, 0.5-8 µg/ml and 0.5-3 µg/ml respectively) and were used to compute a total of 25 synthetic mixtures involving 15 calibration and 10 validation sets between wavelength range of 200 and 400 nm in 0.1N HCl. The suitability of the models was decided on the basis of root mean square error (RMSE) values of calibration and validation data. The analytical performances of these chemometric methods were characterized by relative prediction errors and recovery studies (%) and were compared with each other. These two methods were successfully applied to pharmaceutical formulation, tablet, with no interference with excipients as indicated by the recovery study results. Mean recoveries of the commercial formulation set together with the figures of merit (calibration sensitivity, selectivity, limit of detection, limit of quantification etc.) were estimated. The proposed methods are simple, rapid and can be easily used as an alternative analysis tool in the quality control of drugs and formulation.