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成功和失败预测人类肝脏清除率以优化 lead。

Successful and Unsuccessful Prediction of Human Hepatic Clearance for Lead Optimization.

机构信息

Department of Bioengineering and Therapeutic Sciences, Schools of Pharmacy and Medicine, University of California San Francisco, San Francisco, California 94143, United States.

出版信息

J Med Chem. 2021 Apr 8;64(7):3546-3559. doi: 10.1021/acs.jmedchem.0c01930. Epub 2021 Mar 25.

Abstract

Development of new chemical entities is costly, time-consuming, and has a low success rate. Accurate prediction of pharmacokinetic properties is critical to progress compounds with favorable drug-like characteristics in lead optimization. Of particular importance is the prediction of hepatic clearance, which determines drug exposure and contributes to projection of dose, half-life, and bioavailability. The most commonly employed methodology to predict hepatic clearance is termed to extrapolation (IVIVE) that involves measuring drug metabolism , scaling-up this intrinsic clearance to a prediction of intrinsic clearance by reconciling the enzymatic content between the incubation and an average human liver, and applying a model of hepatic disposition to account for limitations of protein binding and blood flow to predict clearance. This manuscript reviews common techniques used to predict hepatic clearance as well as current challenges and recent theoretical advancements in IVIVE.

摘要

新化学实体的开发成本高、耗时且成功率低。准确预测药代动力学性质对于具有良好药物特性的化合物在先导优化中取得进展至关重要。特别重要的是肝清除率的预测,它决定了药物暴露量,并有助于预测剂量、半衰期和生物利用度。最常用于预测肝清除率的方法称为体外推测(IVIVE),它涉及测量药物代谢,通过协调孵育和平均人体肝脏之间的酶含量,将这种内在清除率放大到预测内在清除率,然后应用肝处置模型来解释蛋白质结合和血流对清除率的限制。本文综述了预测肝清除率的常用技术以及 IVIVE 目前的挑战和最新理论进展。

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