Stoner Chad L, Gifford Eric, Stankovic Charles, Lepsy Christopher S, Brodfuehrer Joanne, Prasad J V N Vara, Surendran Narayanan
Department of Pharmacokinetics, Dynamics, and Metabolism, Pfizer Global Research and Development, 2800 Plymouth Road, Ann Arbor, Michigan 48105, USA.
J Pharm Sci. 2004 May;93(5):1131-41. doi: 10.1002/jps.20020.
The pharmaceutical industry has large investments in compound library enrichment, high throughput biological screening, and biopharmaceutical (ADME) screening. As the number of compounds submitted for in vitro ADME screens increases, data analysis, interpretation, and reporting will become rate limiting in providing ADME-structure-activity relationship information to guide the synthetic strategy for chemical series. To meet these challenges, a software tool was developed and implemented that enables scientists to explore in vitro and in silico ADME and chemistry data in a multidimensional framework. The present work integrates physicochemical and ADME data, encompassing results for Caco-2 permeability, human liver microsomal half-life, rat liver microsomal half-life, kinetic solubility, measured log P, rule of 5 descriptors (molecular weight, hydrogen bond acceptors, hydrogen bond donors, calculated log P), polar surface area, chemical stability, and CYP450 3A4 inhibition. To facilitate interpretation of this data, a semicustomized software solution using Spotfire was designed that allows for multidimensional data analysis and visualization. The solution also enables simultaneous viewing and export of chemical structures with the corresponding ADME properties, enabling a more facile analysis of ADME-structure-activity relationship. In vitro and in silico ADME data were generated for 358 compounds from a series of human immunodeficiency virus protease inhibitors, resulting in a data set of 5370 experimental values which were subsequently analyzed and visualized using the customized Spotfire application. Implementation of this analysis and visualization tool has accelerated the selection of molecules for further development based on optimum ADME characteristics, and provided medicinal chemistry with specific, data driven structural recommendations for improvements in the ADME profile.
制药行业在化合物库富集、高通量生物筛选和生物制药（ADME）筛选方面投入巨大。随着提交用于体外ADME筛选的化合物数量增加，数据分析、解读和报告将成为向化学系列合成策略提供ADME-构效关系信息的限速环节。为应对这些挑战，开发并实施了一种软件工具，使科学家能够在多维框架中探索体外和计算机模拟的ADME及化学数据。目前的工作整合了物理化学和ADME数据，包括Caco-2通透性、人肝微粒体半衰期、大鼠肝微粒体半衰期、动力学溶解度、实测log P、五规则描述符（分子量、氢键受体、氢键供体、计算log P）、极性表面积、化学稳定性和CYP450 3A4抑制作用的结果。为便于对这些数据进行解读，设计了一种使用Spotfire的半定制软件解决方案，可进行多维数据分析和可视化。该解决方案还能同时查看和导出具有相应ADME特性的化学结构，从而更轻松地分析ADME-构效关系。对一系列人类免疫缺陷病毒蛋白酶抑制剂中的358种化合物生成了体外和计算机模拟的ADME数据，得到了一个包含5370个实验值的数据集，随后使用定制的Spotfire应用程序对其进行了分析和可视化。这种分析和可视化工具的实施加快了基于最佳ADME特性选择进一步开发分子的速度，并为药物化学提供了基于数据的具体结构建议，以改善ADME特性。
