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转运体-酶相互作用:利用静态和动态机制模型解析肝脏转运体和酶对药物处置的影响

Transporter-Enzyme Interplay: Deconvoluting Effects of Hepatic Transporters and Enzymes on Drug Disposition Using Static and Dynamic Mechanistic Models.

作者信息

Varma Manthena V, El-Kattan Ayman F

机构信息

Pharmacokinetics, Dynamics and Metabolism, Worldwide Research and Development, Pfizer Inc, Groton, CT, USA.

Pharmacokinetics, Dynamics and Metabolism, Worldwide Research and Development, Pfizer Inc, Cambridge, MA, USA.

出版信息

J Clin Pharmacol. 2016 Jul;56 Suppl 7:S99-S109. doi: 10.1002/jcph.695.

DOI:10.1002/jcph.695
PMID:27385183
Abstract

A large body of evidence suggests hepatic uptake transporters, organic anion-transporting polypeptides (OATPs), are of high clinical relevance in determining the pharmacokinetics of substrate drugs, based on which recent regulatory guidances to industry recommend appropriate assessment of investigational drugs for the potential drug interactions. We recently proposed an extended clearance classification system (ECCS) framework in which the systemic clearance of class 1B and 3B drugs is likely determined by hepatic uptake. The ECCS framework therefore predicts the possibility of drug-drug interactions (DDIs) involving OATPs and the effects of genetic variants of SLCO1B1 early in the discovery and facilitates decision making in the candidate selection and progression. Although OATP-mediated uptake is often the rate-determining process in the hepatic clearance of substrate drugs, metabolic and/or biliary components also contribute to the overall hepatic disposition and, more importantly, to liver exposure. Clinical evidence suggests that alteration in biliary efflux transport or metabolic enzymes associated with genetic polymorphism leads to change in the pharmacodynamic response of statins, for which the pharmacological target resides in the liver. Perpetrator drugs may show inhibitory and/or induction effects on transporters and enzymes simultaneously. It is therefore important to adopt models that frame these multiple processes in a mechanistic sense for quantitative DDI predictions and to deconvolute the effects of individual processes on the plasma and hepatic exposure. In vitro data-informed mechanistic static and physiologically based pharmacokinetic models are proven useful in rationalizing and predicting transporter-mediated DDIs and the complex DDIs involving transporter-enzyme interplay.

摘要

大量证据表明,肝脏摄取转运体——有机阴离子转运多肽(OATPs)在决定底物药物的药代动力学方面具有高度临床相关性,基于此,近期对制药行业的监管指南建议对研究药物进行潜在药物相互作用的适当评估。我们最近提出了一个扩展清除分类系统(ECCS)框架,其中1B类和3B类药物的全身清除可能由肝脏摄取决定。因此,ECCS框架可在发现早期预测涉及OATPs的药物相互作用(DDIs)可能性以及SLCO1B1基因变异的影响,并有助于在候选药物选择和推进过程中做出决策。尽管OATP介导的摄取通常是底物药物肝脏清除中的限速过程,但代谢和/或胆汁成分也对肝脏的整体处置有贡献,更重要的是对肝脏暴露有贡献。临床证据表明,与基因多态性相关的胆汁外排转运或代谢酶的改变会导致他汀类药物药效学反应的变化,而他汀类药物的药理靶点位于肝脏。肇事药物可能同时对转运体和酶表现出抑制和/或诱导作用。因此,采用从机制角度构建这些多个过程的模型进行定量DDI预测,并解卷积各个过程对血浆和肝脏暴露的影响非常重要。体外数据支持的机制性静态和基于生理的药代动力学模型已被证明有助于合理化和预测转运体介导的DDIs以及涉及转运体 - 酶相互作用的复杂DDIs。

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