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治疗性蛋白的生物分布:机制、对药代动力学的影响及评估方法。

The biodistribution of therapeutic proteins: Mechanism, implications for pharmacokinetics, and methods of evaluation.

机构信息

Dept. of Pharmacokinetics and Drug Metabolism, Amgen Inc, 1120 Veterans Blvd, South San Francisco, CA 94080, USA.

出版信息

Pharmacol Ther. 2020 Aug;212:107574. doi: 10.1016/j.pharmthera.2020.107574. Epub 2020 May 17.

Abstract

Therapeutic proteins (TPs) are a diverse drug class that include monoclonal antibodies (mAbs), recombinantly expressed enzymes, hormones and growth factors, cytokines (e.g. chemokines, interleukins, interferons), as well as a wide range of engineered fusion scaffolds containing IgG1 Fc domain for half-life extension. As the pharmaceutical industry advances more potent and selective protein-based medicines through discovery and into the clinical stages of development, it has become widely appreciated that a comprehensive understanding of the mechanisms of TP biodistribution can aid this endeavor. This review aims to highlight the literature that has advanced our understanding of the determinants of TP biodistribution. A particular emphasis is placed on the multi-faceted role of the neonatal Fc receptor (FcRn) in mAb and Fc-fusion protein disposition. In addition, characterization of the TP-target interaction at the cell-level is discussed as an essential strategy to establish pharmacokinetic-pharmacodynamic (PK/PD) relationships that may lead to more informed human dose projections during clinical development. Methods for incorporation of tissue and cell-level parameters defining these characteristics into higher-order mechanistic and semi-mechanistic PK models will also be presented.

摘要

治疗性蛋白(TPs)是一类多样化的药物,包括单克隆抗体(mAbs)、重组表达的酶、激素和生长因子、细胞因子(如趋化因子、白细胞介素、干扰素),以及广泛的工程化融合支架,其中含有 IgG1 Fc 结构域以延长半衰期。随着制药行业通过发现和进入开发的临床阶段推进更有效和选择性的基于蛋白质的药物,人们越来越认识到,全面了解 TP 生物分布的机制可以帮助实现这一目标。本篇综述旨在强调阐明 TP 生物分布决定因素的文献。特别强调了新生 Fc 受体(FcRn)在 mAb 和 Fc 融合蛋白处置中的多方面作用。此外,还讨论了在细胞水平上对 TP-靶标相互作用的表征,作为建立药代动力学-药效学(PK/PD)关系的必要策略,这可能导致在临床开发过程中更明智的人体剂量预测。还将介绍将定义这些特征的组织和细胞水平参数纳入更高阶的机制和半机制 PK 模型的方法。

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