Background Noising is an undesirable phenomenon accompanying the development of widely used chemometric models such as partial least square regression (PLSR) and support vector regression (SVR). Objective Optimizations of these chemometric models by applying orthogonal projection to latent structures (OPLS) as a preprocessing step which is characterized by canceling noise is the purpose of this research study. Additionally, a comprehensive comparative study between the developed methods was undertaken highlighting pros and cons. Methods OPLS was conducted with PLSR and SVR for quantitative determination of pyridoxine HCl, cyclizine HCl, and meclizine HCl in the presence of their related impurities. The training set was formed from 25 mixtures as there were five mixtures for each compound at each concentration level. Additionally, to check the validity and predictive ability of the developed chemometric models, independent test set mixtures were prepared by repeating the preparation of four mixtures of the training set plus preparation of another four independent mixtures. Results Upon application of the OPLS processing method, an upswing of the predictive abilities of PLSR and SVR was found. The root-mean-square error of prediction of the test set was the basic benchmark for comparison. Conclusion The major finding from the conducted research is that processing with OPLS reinforces the ability of models to anticipate the future samples. Highlights Novel optimizations of the widely used chemometric models; application of a comparative study between the suggested methods; application of OPLS preprocessing methods; quantitative determination of pyridoxine HCl, cyclizine HCl and meclizine HCl; checking the predictive power of developed chemometric models; analysis of active ingredients in their pharmaceutical dosage forms.

中文翻译：

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在存在相关杂质的情况下采用先进的化学计量方法测定盐酸吡哆醇、盐酸环利嗪和盐酸美克利嗪：一项比较研究

背景噪声是伴随广泛使用的化学计量模型（例如偏最小二乘回归（PLSR）和支持向量回归（SVR））的发展而出现的不良现象。目的通过将正交投影应用于潜在结构 (OPLS) 作为以消除噪声为特征的预处理步骤来优化这些化学计量模型是本研究的目的。此外，还对所开发的方法进行了全面的比较研究，突出了优缺点。方法 采用PLSR和SVR进行OPLS定量测定盐酸吡哆醇、盐酸环利嗪和盐酸美克利嗪相关杂质的含量。训练集由 25 种混合物组成，因为每种浓度水平的每种化合物有 5 种混合物。此外，为了检查开发的化学计量模型的有效性和预测能力，通过重复准备训练集的四种混合物加上另外四种独立混合物的制备来制备独立的测试集混合物。结果 应用 OPLS 处理方法后，发现 PLSR 和 SVR 的预测能力上升。测试集预测的均方根误差是比较的基本基准。结论 所进行研究的主要发现是，使用 OPLS 进行处理增强了模型预测未来样本的能力。突出广泛使用的化学计量模型的新优化；在建议的方法之间应用比较研究；OPLS预处理方法的应用；盐酸吡哆醇的定量测定，cyclizine HCl和meclizine HCl；检查已开发的化学计量模型的预测能力；分析其药物剂型中的活性成分。