Simultaneous spectrophotometric determination of diclofenac sodium, paracetamol, and chlorzoxazone in ternary mixture using chemometric and artificial neural networks techniques

Abstract

Objective: The aim of this study is to develop and validate simple, accurate, and precise spectrophotometric methods for the simultaneous determination of diclofenac sodium (DIC), paracetamol (PAR), and chlorzoxazone (CHZ) in ternary mixture using chemometric and artificial neural networks (ANN) techniques. Methods: Three chemometric techniques include classical least squares (CLS), principal component regression (PCR), and partial least squares (PLS) in addition to cascade-forward backpropagation ANN (CFBP-ANN) were prepared using the synthetic mixtures containing the three drugs in methanol. In CLS, PCR, and PLS, the absorbances of the synthetic mixtures in the range 267-295 nm with the intervals Δλ=0.2 nm in their zero-order spectra were selected. Then, calibration or regression was obtained using the absorbance data matrix and concentration data matrix for the prediction of the unknown concentrations of DIC, PAR, and CHZ in their mixtures. In CFBP-ANN, two layers, sigmoid layer with 10 neurons and linear layer were found appropriate for the simultaneous determination of the three drugs in their ternary mixture. Results: The four proposed methods were successfully applied to the analysis of the three drugs in laboratory prepared mixtures and tablets with good percentage recoveries in the range of 98-102%. Relative standard deviation for the precision study was found <1%. Conclusion: The four proposed methods showed simplicity, accuracy, precision, and rapidity making them suitable for quality control and routine analysis of the cited drugs in ternary mixtures and pharmaceutical formulation containing them.