Pharmacokinetcis, Dynamics and Metabolism, Pfizer Inc., Cambridge, Massachusetts, USA.
Pharmacokinetcis, Dynamics and Metabolism, Pfizer Inc., Groton, Connecticut, USA.
Pharm Res. 2016 Dec;33(12):3021-3030. doi: 10.1007/s11095-016-2024-z. Epub 2016 Sep 12.
To assess the utility of Extended Clearance Classification System (ECCS) in understanding absorption, distribution, metabolism, and elimination (ADME) attributes and enabling victim drug-drug interaction (DDI) predictions.
A database of 368 drugs with relevant ADME parameters, main metabolizing enzymes, uptake transporters, efflux transporters, and highest change in exposure (%AUC) in presence of inhibitors was developed using published literature. Drugs were characterized according to ECCS using ionization, molecular weight and estimated permeability.
Analyses suggested that ECCS class 1A drugs are well absorbed and systemic clearance is determined by metabolism mediated by CYP2C, esterases, and UGTs. For class 1B drugs, oral absorption is high and the predominant clearance mechanism is hepatic uptake mediated by OATP transporters. High permeability neutral/basic drugs (class 2) showed high oral absorption, with metabolism mediated generally by CYP3A, CYP2D6 and UGTs as the predominant clearance mechanism. Class 3A/4 drugs showed moderate absorption with dominant renal clearance involving OAT/OCT2 transporters. Class 3B drugs showed low to moderate absorption with hepatic uptake (OATPs) and/or renal clearance as primary clearance mechanisms. The highest DDI risk is typically seen with class 2/1B/3B compounds manifested by inhibition of either CYP metabolism or active hepatic uptake. Class 2 showed a wider range in AUC change likely due to a variety of enzymes involved. DDI risk for class 3A/4 is small and associated with inhibition of renal transporters.
ECCS provides a framework to project ADME profiles and further enables prediction of victim DDI liabilities in drug discovery and development.
评估扩展清除分类系统（ECCS）在理解吸收、分布、代谢和消除（ADME）属性以及实现受者药物相互作用（DDI）预测方面的作用。
使用已发表的文献，建立了一个包含 368 种药物的相关 ADME 参数、主要代谢酶、摄取转运体、外排转运体和抑制剂存在时暴露量变化最大（%AUC）的数据库。根据 ECCS，药物通过离子化、分子量和估计的渗透性进行分类。
分析表明，ECCS 类 1A 药物吸收良好，全身清除率由 CYP2C、酯酶和 UGT 介导的代谢决定。对于 1B 类药物，口服吸收良好，主要清除机制是由 OATP 转运体介导的肝摄取。高通透性中性/碱性药物（2 类）表现出高口服吸收，其代谢通常由 CYP3A、CYP2D6 和 UGT 介导，作为主要清除机制。3A/4 类药物吸收中等，主要的肾清除机制涉及 OAT/OCT2 转运体。3B 类药物吸收低至中等，主要的清除机制为肝摄取（OATPs）和/或肾清除。通常情况下，2/1B/3B 类化合物的 DDI 风险最高，表现为 CYP 代谢或主动肝摄取的抑制。2 类由于涉及多种酶，其 AUC 变化范围较宽。3A/4 类的 DDI 风险较小，与抑制肾转运体有关。
ECCS 提供了一个预测 ADME 特征的框架，并进一步能够预测药物发现和开发中受者 DDI 的责任。
