Construction of a translational whole-body physiologically based pharmacokinetic model to investigate the biodistribution of lipid nanoparticle-based mRNA therapeutics for intracellular protein targets

Abstract

Lipid nanoparticle (LNP)–based messenger RNA (mRNA) therapeutics enable in vivo production of diverse protein modalities, but their translation is complicated by multiscale pharmacokinetics encompassing tissue transport, cellular uptake, and intracellular processing. We developed a platform translational whole-body physiologically based pharmacokinetic (PBPK) model to mechanistically characterize the biodistribution and protein expression of intravenously administered mRNA–LNP therapeutics. The model integrates receptor-mediated, saturable tissue infiltration, lymphatic recirculation, hepatic uptake, and explicit intracellular processes including endosomal degradation, mRNA escape, translation, and protein turnover. Parameters were calibrated using comprehensive rat biodistribution data containing both tissue-level mRNA and translated protein measurements, enabling characterization of rapid early tissue deposition and dominant hepatic protein production. Sensitivity analyses identified endosomal degradation, mRNA stability, and translation efficiency as the primary determinants of hepatic protein exposure, whereas increasing tissue influx alone yielded minimal effect. Using fundamental allometric scaling principle, the model was translated from rat to human and evaluated against published clinical plasma mRNA pharmacokinetics of an mRNA-encoded monoclonal antibody. Virtual population simulations reproduced dose-dependent peak timing and clearance across multiple dosing regimens. Cell-type specific simulation analyses further demonstrated the competing roles of Kupffer cells and hepatocytes in shaping liver protein exposure. This whole-body PBPK framework provides a mechanistic and predictive platform to support first-in-human dose selection, to interrogate multilevel determinants of mRNA pharmacokinetics, and to guide rational mRNA-LNP design.