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首页> 外文期刊>Journal of Pharmaceutical and Biomedical Analysis: An International Journal on All Drug-Related Topics in Pharmaceutical, Biomedical and Clinical Analysis >Use of high resolution LC-MSn analysis in conjunction with mechanism-based stress studies: identification of asarinin, an impurity from sesame oil in an animal health product.
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Use of high resolution LC-MSn analysis in conjunction with mechanism-based stress studies: identification of asarinin, an impurity from sesame oil in an animal health product.

机译:高分辨率LC-MSn分析与基于机理的压力研究一起使用:鉴定动物健康产品中麻油中的杂质Asarinin。

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摘要

During analysis of certain stability batches of an animal health product, an unknown peak was found at a level above the identification thresholds set by VICH. This unknown species is extremely labile in the gas phase under normal electrospray ionization (ESI) mass spectrometric condition. Multiple ions were detected with no clear indication of which one is the molecular ion. To overcome this challenge, we utilized tandem MS/MS analysis and multiple MS instruments. The slightly different ionization processes between the two different instruments provided strong, complementary evidence leading to the identification of the correct molecular ion. Based on the formula thus determined, the unknown species was found to be related to sesame oil, which is one of the major excipients used in this drug product. The unknown species was eventually identified as asarinin using high resolution LC-MSn in conjunction with mechanism-based stress studies, in which the unknown species was generated based on the degradation chemistry of sesamin as revealed by the LC-MSn analysis. This overall approach in combining LC-MSn analysis along with mechanism-based stress studies can be used as a general strategy for identification of unknown pharmaceutical impurities, especially the degradants related to the active pharmaceutical ingredient (API) and excipients.
机译:在对某些稳定性的动物保健产品批次进行分析时,发现一个未知峰,其水平高于VICH设定的鉴定阈值。在正常的电喷雾电离(ESI)质谱条件下,这种未知物种在气相中极为不稳定。检测到多种离子,但没有明确指示分子离子是哪一种。为了克服这一挑战,我们利用了串联MS / MS分析和多种MS仪器。两种不同仪器之间的电离过程略有不同,这提供了有力的补充证据,可识别正确的分子离子。根据由此确定的公式,发现未知物质与芝麻油有关,后者是该药物产品中使用的主要赋形剂之一。最终使用高分辨率LC-MSn结合基于机理的应力研究将未知物种鉴定为细辛胺,其中基于LC-MSn分析揭示的芝麻素降解化学产生了未知物种。将LC-MSn分析与基于机理的压力研究相结合的整体方法可以用作识别未知药物杂质(尤其是与活性药物成分(API)和赋形剂有关的降解物)的一般策略。

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