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探讨血浆蛋白结合在药物发现和开发中的重要性的最新进展。

An update on the importance of plasma protein binding in drug discovery and development.

机构信息

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

出版信息

Expert Opin Drug Discov. 2021 Dec;16(12):1453-1465. doi: 10.1080/17460441.2021.1961741. Epub 2021 Aug 17.

Abstract

Plasma protein binding (PPB) remains a controversial topic in drug discovery and development. Fraction unbound (f) is a critical parameter that needs to be measured accurately, because it has significant impacts on the predictions of drug-drug interactions (DDI), estimations of therapeutic indices (TI), and developments of PK/PD relationships.  However, it is generally not advisable to change PPB through structural modifications, because PPB on its own has little relevance for in vivo efficacy. PPB fundamentals are discussed including the three main classes of drug binding proteins (i.e., albumin, alpha1-acid glycoprotein, and lipoproteins) and their physicochemical properties, in vivo half-life, and synthesis rate.  State-of-the-art methodologies for PPB are highlighted. Applications of PPB in drug discovery and development are presented. PPB is an old topic in pharmacokinetics, but there are still many misconceptions. Improving the accuracy of PPB for highly bound compounds is an ongoing effort in the field with high priority. As the field continues to generate high quality data, the regulatory agencies will increase their confidence in our ability to accurately measure PPB of highly bound compounds, and experimental fu values below 0.01 will more likely be used for DDI predictions in the future.

摘要

血浆蛋白结合(PPB)仍然是药物发现和开发中的一个有争议的话题。未结合分数(f)是一个需要准确测量的关键参数,因为它对药物相互作用(DDI)的预测、治疗指数(TI)的估计和 PK/PD 关系的发展有重大影响。然而,通常不建议通过结构修饰来改变 PPB,因为 PPB 本身与体内疗效相关性不大。本文讨论了 PPB 的基本原理,包括三种主要的药物结合蛋白(即白蛋白、α1-酸性糖蛋白和脂蛋白)及其理化性质、体内半衰期和合成率。强调了 PPB 的最新方法。介绍了 PPB 在药物发现和开发中的应用。PPB 是药代动力学中的一个老话题,但仍存在许多误解。提高高度结合化合物的 PPB 准确性是该领域的一项持续努力,具有很高的优先级。随着该领域不断生成高质量的数据,监管机构将增强对我们准确测量高度结合化合物 PPB 的能力的信心,并且在未来,实验 f u 值低于 0.01 更有可能用于 DDI 预测。

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