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高通量代谢稳定性筛选工作流程,具有自动化的数据质量评估功能,适用于制药行业。

A high throughput metabolic stability screening workflow with automated assessment of data quality in pharmaceutical industry.

机构信息

Takeda San Diego, Inc., 10410 Science Center Dr., San Diego, CA 92121, USA.

出版信息

J Chromatogr A. 2010 Mar 5;1217(10):1616-25. doi: 10.1016/j.chroma.2010.01.009. Epub 2010 Jan 14.

DOI:10.1016/j.chroma.2010.01.009
PMID:20132940
Abstract

One of the most commonly performed in vitro ADME assays during the lead generation and lead optimization stage of drug discovery is metabolic stability evaluation. Metabolic stability is typically assessed in liver microsomes, which contain Phase I metabolizing enzymes, mainly cytochrome P450 enzymes (CYPs). The amount of parent drug metabolized by these CYPs is determined by LC/MS/MS. The metabolic stability data are typically used to rank order compounds for in vivo evaluation. We describe a streamlined and intelligent workflow for the metabolic stability assay that permits high throughput analyses to be carried out while maintaining the standard of high quality. This is accomplished in the following ways: a novel post-incubation pooling strategy based on cLogD(3.0) values, coupled with ultra-performance liquid chromatography/tandem mass spectrometry (UPLC/MS/MS), enables sample analysis times to be reduced significantly while ensuring adequate chromatographic separation of compounds within a group, so as to reduce the likelihood of compound interference. Assay quality and fast turnaround of data reports is ensured by performing automated real-time intelligent re-analysis of discrete samples for compounds that do not pass user-definable criteria during the pooling analysis. Intelligent, user-independent data acquisition and data evaluation are accomplished via a custom visual basic program that ties together every step in the workflow, including cassette compound selection, compound incubation, compound optimization, sample analysis and re-analysis (when appropriate), data processing, data quality evaluation, and database upload. The workflow greatly reduces labor and improves data turnaround time while maintaining high data quality.

摘要

在药物发现的先导化合物生成和优化阶段,最常进行的体外 ADME 分析之一是代谢稳定性评估。代谢稳定性通常在肝微粒体中进行评估,其中包含 I 相代谢酶,主要是细胞色素 P450 酶(CYPs)。这些 CYP 代谢的母体药物的量通过 LC/MS/MS 确定。代谢稳定性数据通常用于对化合物进行体内评估的排序。我们描述了一种简化和智能的代谢稳定性测定工作流程,允许进行高通量分析,同时保持高质量的标准。这通过以下方式实现:一种新颖的基于 cLogD(3.0) 值的孵育后混合策略,与超高效液相色谱/串联质谱 (UPLC/MS/MS) 相结合,能够显著缩短样品分析时间,同时确保在一组化合物内有足够的色谱分离,从而降低化合物干扰的可能性。通过对在混合分析过程中未通过用户定义标准的化合物进行自动实时智能重新分析,确保了分析质量和数据报告的快速周转。智能、与用户无关的数据采集和数据评估是通过一个自定义的 Visual Basic 程序完成的,该程序将工作流程中的每一步联系在一起,包括盒式化合物选择、化合物孵育、化合物优化、样品分析和重新分析(如果需要)、数据处理、数据质量评估和数据库上传。该工作流程大大减少了劳动力,提高了数据周转时间,同时保持了高质量的数据。

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