Simultanuous Quantitation of Amlodipine and Rosuvastatin by Artificial Neural Network

Abstract

Artificial neural network (ANN) is a useful tool in chemometrics to model the complex relationship in spectral data resulting in overlapping spectra, spectral interferences, non-linearity, and deviations from Lambert-Beer law. In this work, a new application of ANN was proposed for the simultaneous spectrophotometric quantification of amlodipine (AML) and rosuvastatin (ROS) in tablets despite their overlapping spectra. The relationship between the actual concentrations and absorption data of binary calibration samples was modeled by ANN. The validity of the method was proved by analyzing AML and ROS in their laboratory-made mixtures, intra and, inter-day samples, as well as standard addition samples. The developed method was then applied to the simultaneous quantitation of AML and ROS in commercial tablets and a good agreement was reported between label claim assay results.

Keywords

• Chemometrics
• Artificial neural network
• Amlodipine
• Rosuvastatin
• Tablet analysis

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