Simultaneous quantitative determination of Amlodipine and Atorvastatin in tablets using artificial neural networks

Abstract

Simultaneous spectrophotometric estimation of Atorvastatin Calcium and Amlodipine Besylate in Amostatine^®  tablets were performed using UV–Vis spectroscopic and Artificial Neural Networks (ANN). Absorption spectra of two components were recorded in 200–350 (nm) wavelengths region with an interval of 4 nm. The calibration models were thoroughly evaluated at several concentration levels using the spectra of synthetic binary mixture (prepared using orthogonal design). Three layers feed-forward neural networks using the back-propagation algorithm (B.P) has been employed for building and testing models. Several parameters such as the number of neurons in the hidden layer, learning rate and the number of epochs were optimized. A general statistic function, Sum Square Error (SSE), was selected to evaluate the training process of ANN. The single Relative Standard Error (RSE) (%) of prediction for each component in real sample was calculated as 0.62 and 2.00 for Atorvastatin and Amlodipine, respectively. The results showed a very good agreement between true values and predicted concentration values. The proposed procedure is a simple, precise and convenient method for the determination of Atorvastatin and Amlodipine in commercial tablets.