Full spectrum and genetic algorithm-selected spectrum-based chemometric methods for simultaneous determination of azilsartan medoxomil, chlorthalidone, and azilsartan: Development, validation, and application on commercial dosage form
Five various chemometric methods were established for the simultaneous determination of azilsartan medoxomil (AZM) and chlorthalidone in the presence of azilsartan which is the core impurity of AZM. The full spectrum-based chemometric techniques, namely partial least squares (PLS), principal compone...
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2021
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oai:doaj.org-article:0fe79ff55aea41b0a4be98c139d012242021-12-05T14:10:43ZFull spectrum and genetic algorithm-selected spectrum-based chemometric methods for simultaneous determination of azilsartan medoxomil, chlorthalidone, and azilsartan: Development, validation, and application on commercial dosage form2391-542010.1515/chem-2021-0022https://doaj.org/article/0fe79ff55aea41b0a4be98c139d012242021-03-01T00:00:00Zhttps://doi.org/10.1515/chem-2021-0022https://doaj.org/toc/2391-5420Five various chemometric methods were established for the simultaneous determination of azilsartan medoxomil (AZM) and chlorthalidone in the presence of azilsartan which is the core impurity of AZM. The full spectrum-based chemometric techniques, namely partial least squares (PLS), principal component regression, and artificial neural networks (ANN), were among the applied methods. Besides, the ANN and PLS were the other two methods that were extended by genetic algorithm procedure (GA-PLS and GA-ANN) as a wavelength selection procedure. The models were developed by applying a multilevel multifactor experimental design. The predictive power of the suggested models was evaluated through a validation set containing nine mixtures with different ratios of the three analytes. For the analysis of Edarbyclor® tablets, all the proposed procedures were applied and the best results were achieved in the case of ANN, GA-ANN, and GA-PLS methods. The findings of the three methods were revealed as the quantitative tool for the analysis of the three components without any intrusion from the co-formulated excipient and without prior separation procedures. Moreover, the GA impact on strengthening the predictive power of ANN- and PLS-based models was also highlighted.Darwish Hany W.Al Majed Abdulrahman A.Al-Suwaidan Ibrahim A.Darwish Ibrahim A.Bakheit Ahmed H.Al-Shehri Hassan H.De Gruyterarticlechlorthalidoneazilsartan medoxomilazilsartangaannChemistryQD1-999ENOpen Chemistry, Vol 19, Iss 1, Pp 205-213 (2021) |
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chlorthalidone azilsartan medoxomil azilsartan ga ann Chemistry QD1-999 |
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chlorthalidone azilsartan medoxomil azilsartan ga ann Chemistry QD1-999 Darwish Hany W. Al Majed Abdulrahman A. Al-Suwaidan Ibrahim A. Darwish Ibrahim A. Bakheit Ahmed H. Al-Shehri Hassan H. Full spectrum and genetic algorithm-selected spectrum-based chemometric methods for simultaneous determination of azilsartan medoxomil, chlorthalidone, and azilsartan: Development, validation, and application on commercial dosage form |
description |
Five various chemometric methods were established for the simultaneous determination of azilsartan medoxomil (AZM) and chlorthalidone in the presence of azilsartan which is the core impurity of AZM. The full spectrum-based chemometric techniques, namely partial least squares (PLS), principal component regression, and artificial neural networks (ANN), were among the applied methods. Besides, the ANN and PLS were the other two methods that were extended by genetic algorithm procedure (GA-PLS and GA-ANN) as a wavelength selection procedure. The models were developed by applying a multilevel multifactor experimental design. The predictive power of the suggested models was evaluated through a validation set containing nine mixtures with different ratios of the three analytes. For the analysis of Edarbyclor® tablets, all the proposed procedures were applied and the best results were achieved in the case of ANN, GA-ANN, and GA-PLS methods. The findings of the three methods were revealed as the quantitative tool for the analysis of the three components without any intrusion from the co-formulated excipient and without prior separation procedures. Moreover, the GA impact on strengthening the predictive power of ANN- and PLS-based models was also highlighted. |
format |
article |
author |
Darwish Hany W. Al Majed Abdulrahman A. Al-Suwaidan Ibrahim A. Darwish Ibrahim A. Bakheit Ahmed H. Al-Shehri Hassan H. |
author_facet |
Darwish Hany W. Al Majed Abdulrahman A. Al-Suwaidan Ibrahim A. Darwish Ibrahim A. Bakheit Ahmed H. Al-Shehri Hassan H. |
author_sort |
Darwish Hany W. |
title |
Full spectrum and genetic algorithm-selected spectrum-based chemometric methods for simultaneous determination of azilsartan medoxomil, chlorthalidone, and azilsartan: Development, validation, and application on commercial dosage form |
title_short |
Full spectrum and genetic algorithm-selected spectrum-based chemometric methods for simultaneous determination of azilsartan medoxomil, chlorthalidone, and azilsartan: Development, validation, and application on commercial dosage form |
title_full |
Full spectrum and genetic algorithm-selected spectrum-based chemometric methods for simultaneous determination of azilsartan medoxomil, chlorthalidone, and azilsartan: Development, validation, and application on commercial dosage form |
title_fullStr |
Full spectrum and genetic algorithm-selected spectrum-based chemometric methods for simultaneous determination of azilsartan medoxomil, chlorthalidone, and azilsartan: Development, validation, and application on commercial dosage form |
title_full_unstemmed |
Full spectrum and genetic algorithm-selected spectrum-based chemometric methods for simultaneous determination of azilsartan medoxomil, chlorthalidone, and azilsartan: Development, validation, and application on commercial dosage form |
title_sort |
full spectrum and genetic algorithm-selected spectrum-based chemometric methods for simultaneous determination of azilsartan medoxomil, chlorthalidone, and azilsartan: development, validation, and application on commercial dosage form |
publisher |
De Gruyter |
publishDate |
2021 |
url |
https://doaj.org/article/0fe79ff55aea41b0a4be98c139d01224 |
work_keys_str_mv |
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