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The role of quantitative ADME proteomics to support construction of physiologically based pharmacokinetic models for use in small molecule drug development

机译:定量ADME蛋白质组学的作用支持在小分子药物发育中使用的生理基于药代动力学模型的构建

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Pharmacokinetics (PK) refers to the time course of drug concentrations in the body and since knowledge of PK aids understanding of drug efficacy and safety, numerous PK studies are performed in animals and humans during the drug development process. In vitro to in vivo extrapolation and physiologically based pharmacokinetic (PBPK) modeling are tools that integrate data from various in silico, in vitro, and in vivo sources to deliver mechanistic quantitative simulations of in vivo PK. PBPK models are used to predict human PK and to evaluate the effects of intrinsic factors such as organ dysfunction, age, and genetics as well as extrinsic factors such as co-administered drugs. In recent years, the use of PBPK within the industry has greatly increased. However, insufficient data on how the abundance of metabolic enzymes and membrane transporters vary in different human patient populations and in different species has been a limitation. A major advance is therefore expected through reliable quantification of the abundance of these proteins in tissues. This review describes the role of PBPK modeling in drug discovery and development, outlines the assumptions involved in integrating protein abundance data, and describes the advances made and expected in determining abundance of relevant proteins through mass spectrometric techniques.
机译:药代动力学(PK)是指身体中的药物浓度的时间,而且由于PK艾滋病了解药物疗效和安全性,在药物开发过程中,在动物和人类中进行了许多PK研究。体外以体内外推和生理基础的药代动力学(PBPK)建模是将来自硅,体外和体内源的各种数据集成的工具,以提供体内PK的机械定量模拟。 PBPK模型用于预测人类PK,并评估内在因素,如器官功能障碍,年龄和遗传学以及外在因素,如共同施用的药物。近年来,业内人员内的PBPK大大增加。然而,关于代谢酶和膜转运蛋白在不同人类患者和不同物种中如何变化的数据不足是一个限制。因此,通过可靠地定量组织中这些蛋白质的丰度的可靠定量预期预期主要提前。本综述描述了PBPK建模在药物发现和开发中的作用,概述了整合蛋白质丰富数据的假设,并描述了通过质谱技术确定相关蛋白质的预期和预期的预期。

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