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The botanical drug substance crofelemer as a model system for comparative characterization of complex mixture drugs

机译:植物药Crofelemer作为复杂混合物药物比较表征的模型系统

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摘要

Crofelemer is a botanical polymeric proanthocyanidin that inhibits chloride channel activity and is used clinically for treating HIV-associated secretory diarrhea. Crofelemer lots may exhibit significant physicochemical variation due to the natural source of the raw material. A variety of physical, chemical, and biological assays were utilized to identify potential critical quality attributes (CQAs) of crofelemer, which may be useful in characterizing differently sourced and/or processed drug products. Crofelemer drug substance was extracted from tablets of one commerical drug product lot, fractionated, and subjected to accelerated thermal degradation studies to produce derivative lots with variations in chemical and physical composition potentially representative of manufacturing and raw material variation. Liquid chromatography, UV absorbance spectroscopy, mass spectrometry, and NMR analysis revealed substantial changes in the composition of derivative lots. A chloride channel inhibition cell-based bioassay suggested that substantial changes in crofelemer composition did not necessarily result in major changes to bioactivity. In two companion papers, machine learning and data mining approaches were applied to the analytical and biological data sets presented herein, along with chemical stability data sets derived from forced degradation studies, to develop an integrated mathematical model that can identify CQAs which are most relevent in distinguishing between different populations of crofelemer.
机译:Crofelemer是一种植物性聚合原花青素,可抑制氯离子通道活性,临床上用于治疗HIV相关的分泌性腹泻。 crofelemer批次可能由于原料的天然来源而表现出明显的理化变化。利用各种物理,化学和生物学测定方法来确定croofelemer的潜在关键质量属性(CQA),这可能有助于表征来源不同和/或加工的药物产品。从一个商业药品批次的片剂中提取出Crofelemer原料药,进行分馏,然后进行加速热降解研究,以生产化学和物理组成均可能代表制造和原料变化的衍生产品。液相色谱,紫外吸收光谱,质谱和NMR分析显示,衍生批次的组成发生了实质性变化。氯化物通道抑制细胞为基础的生物测定表明,croofelemer组成的实质性变化不一定会导致生物活性的重大变化。在两篇随附的论文中,将机​​器学习和数据挖掘方法应用于此处介绍的分析和生物学数据集,以及源自强制降解研究的化学稳定性数据集,以开发可以识别CQA最可靠的集成数学模型。区分不同的croofelemer人群。

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