Perspective on high-throughput bioanalysis to support in vitro assays in early drug discovery: Supplementary tables

As the desire for a shortened design/make/test/learn cycle increases in early drug discovery, the
pressure to rapidly deliver drug metabolism pharmacokinetic data continues to rise. From a bioanalytical
standpoint, in vitro assays are challenging because they are amenable to automation and thus capable
of generating a high number of samples for analysis. To keep up with analysis demands, automated
method development workflows, rapid sample analysis approaches and efficient data analysis software
must be utilized. This work provides an outline of how we implemented those three aspects to provide
bioanalytical support for in vitro drug metabolism pharmacokinetic assays, which include developing
hundreds of mass spectrometry methods and analyzing thousands of samples per week, while delivering
a median bioanalytical turnaround time of 1–2 business days.

随着早期药物发现中缩短设计/制备/测试/学习周期的需求日益增长，快速交付药物代谢药代动力学数据的压力持续攀升。从生物分析视角来看，体外试验（in vitro assays）具有挑战性，因其适配自动化，故而能够生成大量待分析样本。为满足分析需求，必须采用自动化方法开发工作流程、快速样本分析策略及高效数据分析软件。本研究概述了我们如何整合这三个方面，为体外药物代谢药代动力学试验提供生物分析支持——包括每周开发数百种质谱方法（mass spectrometry methods）并分析数千份样本，同时实现1-2个工作日的中位生物分析周转时间。