Department of Pharmaceutical Chemistry, College of Pharmacy, Taif University, Al-Hawiah, 21974 Taif, Saudi Arabia; Pharmaceutical Analytical Chemistry Department, Faculty of Pharmacy, Beni-Suef University, Alshaheed Shehata Ahmad Hegazy St., 62514 Beni-Suef, Egypt.
Pharmaceutical Analytical Chemistry Department, Faculty of Pharmacy, Beni-Suef University, Alshaheed Shehata Ahmad Hegazy St., 62514 Beni-Suef, Egypt.
Spectrochim Acta A Mol Biomol Spectrosc. 2020 Apr 15;231:118116. doi: 10.1016/j.saa.2020.118116. Epub 2020 Jan 27.
UV cutoff area (COA) is known to be the wavelength band where solvents used for analysis can absorb radiation and accordingly affect the absorption spectra of drugs of interest being analyzed, even if blank experiments are done to eliminate solvent interference. However, this area may show peaks of significance for some drugs, and accordingly some researchers tend to include it in analysis. This study is presenting the importance of avoiding using COA, where it may represent significant negative effect on predictive ability of some linear chemometric methods like partial least squares regression PLSR. The presented study is using previously analyzed pharmaceutical mixtures of Dapoxetine Hydrochloride (DAP) and Tadalafil (TAD) as a case study, whether in pure forms or in dosage form, where the study uses two datasets for analysis, the first aims to include COA and the second dataset avoids it, then a statistical comparison is conducted for training sets, test sets and dosage form datasets to see how far COA may interfere with analysis results. Generally, the results show significant difference in datasets for t and F statistics for analysis of dosage form sets; which reflects changes in predictive ability of used chemometric method upon inclusion of COA in absorbance datasets, and accordingly unsuitability of using COA especially for routine quality control analysis of pharmaceutical mixtures.
紫外截止区（COA）是指用于分析的溶剂可以吸收辐射的波长带，因此即使进行空白实验以消除溶剂干扰，也会影响所分析的感兴趣药物的吸收光谱。然而，对于某些药物，该区域可能会出现显著的峰，因此一些研究人员倾向于将其包含在分析中。本研究强调了避免使用 COA 的重要性，因为它可能对某些线性化学计量方法（如偏最小二乘回归 PLSR）的预测能力产生重大负面影响。本研究以前分析的盐酸达泊西汀（DAP）和他达拉非（TAD）的药物混合物为例，无论是纯形式还是剂型，研究使用两个数据集进行分析，第一个数据集旨在包含 COA，第二个数据集则避免使用 COA，然后对训练集、测试集和剂型数据集进行统计比较，以了解 COA 可能会在多大程度上干扰分析结果。一般来说，结果表明，剂型数据集的 t 和 F 统计数据在分析中存在显著差异；这反映了在吸收数据集包含 COA 时所用化学计量方法的预测能力发生了变化，因此不适合特别是在药物混合物的常规质量控制分析中使用 COA。
