A simple and rapid spectrophotometric method coupled with intelligent approaches for the simultaneous determination of antiepileptic drugs in pharmaceutical formulations, biological, serological, and breast milk samples

Abstract

In this study, simultaneous measurement of Phenytoin (PHT), Levetiracetam (LEV), and Pregabalin (PRG) was assessed by chemometrics methods, including feedforward artificial neural network (FF-ANN) with Levenberg-Marquardt (LM) and Conjugate Gradient with Fletcher Reeves updates (CGF), as well as least squares support vector machine (LS-SVM) along with the spectrophotometric method in the formulation of antiepileptic drugs, biological, serological, as well as breast milk samples were examined. According to better results of the LM algorithm than the other one, layers 2 with 8, 10, and 8 neurons with the least error (mean square error (MSE)) as the best layer and neurons were selected for PHT (MSE = 3 × 10−28), LEV (MSE = 7.67 × 10−27), and PRG (MSE = 4.43 × 10−28), respectively in LM algorithm. The mean recovery values were achieved in the range of 97.39%–102.57% and 85.01%–112.40% for LM and CGF, respectively. The regularization parameter (γ) values of the LS-SVM model were found to be 240, 70, and 80 for PHT, LEV, and PRG, respectively. Also, the width of the function (σ2) were 270,350, 230 for PHT, LEV, and PRG, respectively. The mean recovery of this method was found to be 99.50%, 99.44%, and 99.26% for PHT, LEV, PRG, respectively. The results of the proposed methods on the samples of tablets and capsules were compared with high-performance liquid chromatography (HPLC) as a reference method with one-way analysis of variance (ANOVA) test at 95% confidence level, which did not show a significant difference between the approaches. The proposed methods are fast, simple, inexpensive, accurate, and without the need for the separation steps that can be used to improve the quality of pharmaceutical products.