Simultaneous spectrophotometric determination of chlordiazepoxide and clidinium using multivariate calibration techniques.
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.
Khoshayand
Mohammad Reza
MR
Department of Drug and Food Control, Tehran University of Medical Sciences, Iran. khoshayand@tums.ac.ir
Abdollahi
Hamid
H
Moeini
Ali
A
Shamsaie
Ali
A
Ghaffari
Alireza
A
Abbasian
Sepideh
S
D002138:Calibration; D002707:Chlordiazepoxide / Q000032:analysis*; D016018:Least-Squares Analysis; D016571:Neural Networks, Computer; D025341:Principal Component Analysis; D011813:Quinuclidinyl Benzilate / Q000031:analogs & derivatives* / Q000032:analysis; D013053:Spectrophotometry / Q000379:methods; D013607:Tablets
D013607:Tablets; D011813:Quinuclidinyl Benzilate; D002707:Chlordiazepoxide; C054940:clidinium