首页> 外文期刊>Open Chemistry >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
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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

机译:全谱和遗传算法的基于谱的化学计量测量方法,用于同时测定阿桑沙坦麦克斯莫洛尼尔,Chlorthaldone和Azilsartan:开发,验证和商业用量形式的应用

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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.
机译:建立了各种各种化学计量方法,用于同时测定含氮藻的亚辛甘氨氧诺莫罗(AZM)和ChlorthalidOne,其是AZM的核心杂质。基于全谱形的化学计量技术,即偏最小二乘(PLS),主要成分回归和人工神经网络(ANN)在应用的方法中。基础,ANN和PLS是通过遗传算法(GA-PLS和GA-ANN)作为波长选择过程延伸的另外两种方法。模型是通过应用多级多级多方面的实验设计而开发的。通过含有九种混合物的验证组评估所建议模型的预测力,该分析的不同比例不同。对埃达比克朗的分析?平板电脑,所有提出的程序都适用,在ANN,GA-ANN和GA-PLS方法的情况下实现了最佳结果。这三种方法的发现被揭示为分析三种组件的定量工具还强调了来自共同配制赋形剂和没有先前分离程序的任何侵入.Oore,还强调了对加强基于ANN和PLS的模型的预测力的GA影响。

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