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整合来自表现出诱导、可逆抑制和基于机制的失活的化合物的体外动力学数据:体外研究设计。

Integrating in vitro kinetic data from compounds exhibiting induction, reversible inhibition and mechanism-based inactivation: in vitro study design.

作者信息

McConn Donavon J, Zhao Zhiyang

机构信息

Department of Drug Metabolism and Pharmacokinetics, GlaxoSmithKline, Research Triangle Park, NC 27709, USA.

出版信息

Curr Drug Metab. 2004 Apr;5(2):141-6. doi: 10.2174/1389200043489063.

Abstract

Drug:drug interactions continue to be an obstacle for the pharmaceutical industry in the development of potential drug candidates. Considering the number of compounds that have been withdrawn from the market due to drug:drug interactions (e.g. cisapride, terfenadine and mibefradil), more pressure is placed on the pharmaceutical industry to investigate potential interactions prior to regulatory submission. In particular, induction and inhibition of drug metabolizing enzymes can profoundly alter the pharmacological and toxicological effects observed during monotherapy. However, due to differences in the expression and regulation of both metabolic enzymes and nuclear receptors responsible for induction, in vivo studies with pre-clinical species are not predictive of the human clinical situation. Although in vitro kinetic data also have limitations when extrapolating in vivo, in vitro testing has become more commonplace due to reduced cost and higher throughput. However, in the in vitro setting, complex enzyme kinetics can alter the estimation of kinetic parameters. Time-dependent or non-Michaelis-Menten kinetics can alter parameter estimates if experimental conditions are not optimal, and can therefore confound clinical predictions. Furthermore, mechanism-based inactivation (MBI) will reduce the active enzyme pool, both in vitro and in vivo, and thus complicate any parameter estimates. To further complicate matters, some compounds (e.g., ritonavir) inhibit, induce, as well as cause mechanism-based enzyme inactivation. For compounds such as ritonavir, the accurate estimation of kinetic parameters requires optimal experimental design at a minimum. This review will highlight the challenges in estimating enzyme kinetic parameters when both inhibition and induction are present, and will offer experimental viewpoints for the optimization of the experimental conditions.

摘要

药物与药物之间的相互作用仍然是制药行业在开发潜在候选药物过程中的一个障碍。考虑到因药物与药物相互作用而从市场上撤下的化合物数量(如西沙必利、特非那定和米贝拉地尔),制药行业在提交监管申请之前研究潜在相互作用面临着更大的压力。特别是,药物代谢酶的诱导和抑制可深刻改变单药治疗期间观察到的药理和毒理效应。然而,由于负责诱导的代谢酶和核受体在表达和调控方面存在差异,临床前物种的体内研究并不能预测人类的临床情况。尽管体外动力学数据在推断体内情况时也有局限性,但由于成本降低和通量提高,体外测试已变得更为普遍。然而,在体外环境中,复杂的酶动力学可改变动力学参数的估计。如果实验条件不理想,时间依赖性或非米氏动力学可改变参数估计值,从而混淆临床预测。此外,基于机制的失活(MBI)将在体外和体内减少活性酶库,从而使任何参数估计变得复杂。更复杂的是,一些化合物(如利托那韦)会抑制、诱导以及导致基于机制的酶失活。对于利托那韦这类化合物,准确估计动力学参数至少需要优化实验设计。本综述将强调在存在抑制和诱导作用时估计酶动力学参数所面临的挑战,并提供优化实验条件的实验观点。

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