Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, USA.
Department of Exploratory Medicine and Pharmacology, Lilly Research Laboratories, Lilly Corporate Center, Indianapolis, IN, USA.
MAbs. 2022 Jan-Dec;14(1):2056944. doi: 10.1080/19420862.2022.2056944.
A model-based framework is presented to predict monoclonal antibody (mAb) pharmacokinetics (PK) in humans based on measures of antibody physiochemical properties. A physiologically based pharmacokinetic (PBPK) model is used to explore the predictive potential of 14 assays designed to measure various antibody physiochemical properties, including nonspecific cell-surface interactions, FcRn binding, thermal stability, hydrophobicity, and self-association. Based on the mean plasma PK time course data of 22 mAbs from humans reported in the literature, we found a significant positive correlation (R = 0.64, p = .0013) between the model parameter representing antibody-specific vascular to endothelial clearance and heparin relative retention time, an measure of nonspecific binding. We also found that antibody-specific differences in paracellular transport due to convection and diffusion could be partially explained by antibody heparin relative retention time (R = 0.52, p = .012). Other physiochemical properties, including antibody thermal stability, hydrophobicity, cross-interaction and self-association, in and of themselves were not predictive of model-based transport parameters. In contrast to other studies that have reported empirically derived expressions relating measures of antibody physiochemical properties directly to antibody clearance, the proposed PBPK model-based approach for predicting mAb PK incorporates fundamental mechanisms governing antibody transport and processing, informed by measures of antibody physiochemical properties, and can be expanded to include more descriptive representations of each of the antibody processing subsystems, as well as other antibody-specific information.
本文提出了一种基于模型的框架，可根据抗体理化性质的测量值来预测人源单克隆抗体（mAb）的药代动力学（PK）。采用生理药代动力学（PBPK）模型来探索 14 种旨在测量各种抗体理化性质的检测方法的预测潜力，包括非特异性细胞表面相互作用、FcRn 结合、热稳定性、疏水性和自缔合。基于文献中报道的 22 个人源 mAb 的平均血浆 PK 时间过程数据，我们发现代表抗体特异性血管内皮清除率的模型参数与肝素相对保留时间之间存在显著正相关（R=0.64，p=0.0013），肝素相对保留时间是一种非特异性结合的衡量指标。我们还发现，由于对流和扩散引起的抗体特异性跨细胞转运差异可以部分用抗体肝素相对保留时间（R=0.52，p=0.012）来解释。其他理化性质，包括抗体热稳定性、疏水性、交叉相互作用和自缔合，本身并不能预测基于模型的转运参数。与其他报告将抗体理化性质的测量值与抗体清除率直接相关的经验推导表达式的研究不同，所提出的基于 PBPK 模型的 mAb PK 预测方法纳入了控制抗体转运和处理的基本机制，这些机制是由抗体理化性质的测量值提供信息的，并可以扩展到包括每个抗体处理子系统的更具描述性的表示，以及其他抗体特异性信息。
