基于生理学的药代动力学模型
药代动力学
单克隆抗体
新生儿Fc受体
外推法
药理学
化学
抗体
医学
免疫球蛋白G
数学
免疫学
数学分析
作者
Salih Benamara,Carla Troisi,Florence Gattacceca,Erik Sjögren,Laurent Nguyen,Donato Teutonico
标识
DOI:10.1021/acsptsci.5c00356
摘要
Physiologically based pharmacokinetic (PBPK) modeling is a useful tool during drug development due to its ability to extrapolate pharmacokinetics (PK) between species and populations. For monoclonal antibodies (mAbs), these models can be used to support dose selection, especially for first-in-human (FIH) trials. In the PBPK model for biologics in the software PK-Sim, salvaging from endosomal degradation via the neonatal fragment crystallizable receptor (FcRn) is a critical process for the systemic clearance of mAbs. However, high variability is associated with in vitro measurements of the dissociation constant ( K d ) for FcRn ( K d FcRn ) in human. Furthermore, predicting affinity for FcRn in human presents a significant challenge due to the lack of a standardized methodology. In this paper, we evaluated different predictors of the K d for FcRn ( K d FcRn ) in humans to enhance the precision of mAbs PK projections for FIH trials. A database comprising PK profiles for 27 mAbs was constructed across different species. Plasma concentration–time courses for each drug and species were used to develop a PBPK model for each compound, by estimating the K d FcRn for each species. Cross-species correlations were established to explore extrapolation performances of K d FcRn from animals to humans. As an alternative to using animal data, a direct prediction approach, based on the median of the 27 human K d FcRn values, was assessed. When considering a prediction error of 100% (2-fold deviation), both the extrapolation from preclinical species and the direct approach based on the median human value accurately predict at least 80% of the K d FcRn values within the prediction interval.
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