Cross-Species Extrapolation of Neonatal Fc Receptor (FcRn) Binding Affinity to Predict Monoclonal Antibody Pharmacokinetics in Humans Using Physiologically Based Pharmacokinetic Modeling (PBPK): Are We There Yet?

Abstract

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_dFcRn) 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_dFcRn) 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_dFcRn for each species. Cross-species correlations were established to explore extrapolation performances of K_dFcRn from animals to humans. As an alternative to using animal data, a direct prediction approach, based on the median of the 27 human K_dFcRn 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_dFcRn values within the prediction interval.