Parallel-Competitive Absorption-Presystemic Metabolism Model for Subcutaneous Bioavailability Prediction of Monoclonal Antibodies

Monoclonal antibody therapeutics are often administered subcutaneously rather than intravenously to improve patient compliance and reduce healthcare costs. However, systemic absorption after a subcutaneous injection is often incomplete and variable. The bioavailability prediction model applied herein utilized a two-compartment pharmacokinetic framework in conjunction with parallel-competitive absorption and presystemic metabolism pathways. This study aimed to broaden the former validation of human bioavailability prediction by including linear and nonlinear-pharmacokinetics compounds. Validation was significantly expanded using a data set from 79 monoclonal antibodies (mAbs), spanning a bioavailability range of 29-100% (and a geometric mean bioavailability of 66%). By applying a single absorption rate constant alongside compound-specific estimates of presystemic metabolism rates, proportional to systemic clearance parameters, human subcutaneous bioavailability predictions were generated with a root-mean-square error (RMSE) of 13.1%. This mechanistic predictive method offers a preliminary estimate of subcutaneous bioavailability solely on the basis of pharmacokinetic data, which can be derived from intravenous administration.