Application of Genetic Algorithm as a Variable Selection in Partial Least Square and Artificial Neural Network for the Simultaneous Analysis of Sacubitril and Valsartan in their Recently Approved Pharmaceutical Preparation. Issue 3 (4th May 2018)

• Record Type: Journal Article
• Authors: Attia, Khalid A.M.; Nassar, Mohammed W.I.; El-Olemy, Ahmed; Ramzy, Sherif
• Is Part Of: Analytical chemistry letters. Volume 8:Issue 3(2018)
• Page Start: 287
• Page End: 296
• Publication Date: 2018-05-04
• Subjects: Entresto® -- sacubitril -- valsartan -- chemometric models -- genetic algorithm; Chemistry, Analytic -- Periodicals; 543.05
• DOI: 10.1080/22297928.2018.1438312
• Languages: English
• ISSNs: 2229-7928

Abstract

Abstract: Two smart chemometric models have been applied for quantitative spectral analysis of recently approved binary mixture of sacubitril and valsartan namely; partial least squares and artificial neural networks. Moreover, effect of genetic algorithm as a powerful variable selection technique on the two models has been studied. Genetic algorithm has improved the predictive ability of the models and reduces its complexity by elimination of irrelevant variables. The proposed methods have been successfully applied for the determination of the two drugs in Entresto® tablets. Statistical comparisons between the obtained results and those obtained by the reported method have been performed showing no significant differences by applying t-test and F-test.