首页> 外文期刊>Spectrochimica acta, Part A. Molecular and biomolecular spectroscopy >Advanced chemometrics manipulation of UV-spectroscopic data for determination of three co-formulated drugs along with their impurities in different formulations using variable selection and regression model updating
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Advanced chemometrics manipulation of UV-spectroscopic data for determination of three co-formulated drugs along with their impurities in different formulations using variable selection and regression model updating

机译:先进的化学计量器操纵UV光谱数据,用于测定三种共同配制的药物以及使用可变选择和回归模型更新的不同配方中的杂质

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摘要

Multivariate calibration models manipulating UV-spectroscopic data of three anti-productive cough drugs namely ambroxol, guaifenesin and theophylline were constructed for the intent of simultaneous determination in presence of their impurities; guaiacol and caffeine. Both interval partial least squares (iPLS) and synergy interval partial least square (siPLS) algorithms were adopted for variables selection to extract useful information and improve the models' performance. The optimal spectral range and their combinations were assigned according to the lowest value of Root Mean Square Error of Prediction (RMSEP), Standard Error of Prediction (SEP) and Correlation Coefficient (R-2). The results obtained from full spectrum PLS were compared with those obtained by iPLS and siPLS. The siPLS method exhibited better performance. The combination of four subintervals, 2, 9,13, and 16, showed the best effect, with RMSEP of 0.1039, 03548 and 0.207 mu g/mL, for ambroxol, guaifenesin and theophylline, respectively and correlation coefficient of 0.9999, 0.9975 and 0.9994 for ambroxol, guaifenesin and theophylline, respectively. The proposed methods were used for the simultaneous determination of the three drugs in presence of their impurities in bulk powder and in pharmaceutical formulation. (C) 2018 Elsevier B.V. All rights reserved.
机译:为三种抗高效咳嗽药物的UV光谱数据进行多变量校准模型,即Ambroxol,Guaifenesin和Theophylline,用于同时测定它们的杂质的目的;桂醇和咖啡因。采用间隔部分最小二乘(IPL)和协同间隔部分最小二乘(SIPLS)算法用于变量选择以提取有用的信息并提高模型的性能。根据预测(RMSEP)的根均线误差,预测标准误差(SEP)和相关系数(R-2),根据最低值和它们的组合来分配最佳光谱范围及其组合。将从全谱PLS获得的结果与IPLS和SIPLS获得的结果进行了比较。 SIPLS方法表现出更好的性能。四个子宫内离心物,2,9,13和16的组合显示出最佳效果,RMSEP为0.1039,03548和0.207μg/ ml,用于氨溴苯,胍蛋白和茶碱,相关系数为0.9999,0.9975和0.9994对于氨溴苯,胍蛋白和茶碱。所提出的方法用于同时测定散装粉末和药物制剂中的杂质存在的三种药物。 (c)2018年elestvier b.v.保留所有权利。

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