Riley Robert J, Kenna J Gerry
AstraZeneca R&D Charnwood, Department of Physical and Metabolic Science, Loughborough, Leicestershire LE11 5RH, UK.
Curr Opin Drug Discov Devel. 2004 Jan;7(1):86-99.
Deficiencies in ADMET (absorption, distribution, metabolism, excretion and toxicity) properties and drug-drug interactions are collectively the major causes of attrition during drug development. As such, assays have been developed with which to study and optimize these key properties in early dug discovery. While screening using systems expressing discrete proteins have provided valuable insight, quantitative structure-activity relationships (QSARs) and predictive computational models, the ability to study several processes in tandem is paramount to in vivo projection. In particular, the key role of transporter proteins in controlling access to drug metabolizing enzymes and other intracellular processes cannot be overlooked. In this respect, cellular models provide a key platform to study the complex interplay between xenobiotic transport and metabolism, which underlie many ADMET issues. In addition, uptake and accumulation in tissues may provide a mechanistic insight into false negatives arising from simple, primary screens, for example, cytochrome P450 (CYP) inhibition analysis. Qualitative and quantitative interspecies differences in the regulation, expression and functional activity of key ADMET processes confound extrapolation from animals to man. However, complementary screens using animal and human material may assist the interpretation of safety assessment findings and help project the risk for early human studies.
药物开发过程中,药物代谢动力学(吸收、分布、代谢、排泄和毒性)特性的缺陷以及药物相互作用是导致药物研发失败的主要原因。因此,在药物研发早期已开发出相关检测方法来研究和优化这些关键特性。虽然利用表达离散蛋白的系统进行筛选,以及定量构效关系(QSARs)和预测性计算模型已提供了有价值的见解,但串联研究多个过程的能力对于体内预测至关重要。特别是,转运蛋白在控制药物代谢酶的可及性和其他细胞内过程中的关键作用不容忽视。在这方面,细胞模型为研究外源性物质转运与代谢之间的复杂相互作用提供了关键平台,而这种相互作用是许多药物代谢动力学问题的基础。此外,组织中的摄取和蓄积可能为简单的初筛(例如细胞色素P450(CYP)抑制分析)中出现的假阴性结果提供机制上的见解。关键药物代谢动力学过程在调控、表达和功能活性方面的种间定性和定量差异,使得从动物到人类的外推变得复杂。然而,使用动物和人类材料进行的补充筛选可能有助于解释安全性评估结果,并帮助预测早期人体研究的风险。