Development of a chemometric-assisted spectrophotometric method for quantitative simultaneous determination of Amlodipine and Valsartan in commercial tablet

Abstract

In this study, two drugs named Amlodipine (AML) and Valsartan (VAL) related to the high blood pressure were simultaneously determined in synthetic mixtures and Valzomix tablet. For this purpose, the chemometric-assisted spectrophotometric method was developed without any pre-preparation. Artificial intelligence techniques, including artificial neural network (ANN) and least squares support vector machine (LS-SVM) as chemometrics procedures were proposed. Feed-forward back-propagation neural network (FFBP-NN) with two different algorithms, containing Levenberg–Marquardt (LM) and gradient descent with momentum and adaptive learning rate backpropagation (GDX) was applied. To select the best model, several layers and neurons were investigated. The results revealed that layer = 5 with 6 neurons and layer = 2 with 10 neurons had lower mean square error (MSE) (1.41 × 10−24, 1.16 × 10-23) for AML and VAL, respectively. In the LS-SVM method, gamma (γ) and sigma (σ) parameters were optimized. γ and σ were obtained 50, 30 and 40, 40 with the root mean square error (RMSE) of 0.4290 and 0.5598 for AML and VAL, respectively. Analysis of the pharmaceutical formulation was evaluated through the chemometrics methods and high-performance liquid chromatography (HPLC) as a reference technique. The obtained results were statistically compared with each other using the one-way analysis of variance (ANOVA) test. There were no significant differences between them and the proposed method was satisfactory for estimating the components of the Valzomix tablet.