| Literature DB >> 20812297 |
Mohammad Reza Khoshayand1, Hamid Abdollahi, Ali Moeini, Ali Shamsaie, Alireza Ghaffari, Sepideh Abbasian.
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.Entities:
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Year: 2010 PMID: 20812297 DOI: 10.1002/dta.162
Source DB: PubMed Journal: Drug Test Anal ISSN: 1942-7603 Impact factor: 3.345