Author(s): Khoshayand MR, Abdollahi H, Moeini A, Shamsaie A, Ghaffari A,
Abstract Share this page
Abstract Three multivariate modelling approaches including partial least squares regression (PLS), genetic algorithm-partial least squares regression (GA-PLS), and principal components-artificial neural network (PC-ANN) analysis were investigated for their application to the simultaneous determination of chlordiazepoxide and clidinium levels in pharmaceuticals. A set of synthetic mixtures of drugs in ethanol and 0.1 M HCL was made, and the prediction abilities of the aforementioned methods were examined using RSE\% (relative standard error of the prediction). The PLS and PC-ANN methods were found to be comparable, and GA-PLS produced slightly better results. The predictive models that we built were successfully applied to simultaneously determine the levels of chlordiazepoxide and clidinium in coated tablets. Copyright © 2010 John Wiley & Sons, Ltd.
This article was published in Drug Test Anal
and referenced in Pharmaceutica Analytica Acta