Bench to Bedside Modeling of mRNA Encoding IgG Using a Multiscale Mechanistic Pharmacokinetic-Toxicokinetic (PK-TK) Model: A Case Study With Anti-Claudin 18.2

Abstract

In vivo expression of mRNA-encoded antibodies offers a novel platform for targeted therapies. However, translating preclinical findings to clinical applications remains challenging due to complex processes, including nanoparticle delivery, cellular uptake, mRNA translation, and target binding. This study developed a multiscale mechanistic pharmacokinetic-toxicokinetic (PK-TK) model to characterize and predict the in vivo behavior of an mRNA therapeutic encoding an anti-claudin 18.2 IgG, scaling from preclinical models to human predictions. The model integrates key processes: (i) lipid nanoparticle (LNP)-mediated delivery and endocytosis via low-density lipoprotein receptors (LDLR), (ii) endosomal escape and mRNA release, (iii) cytoplasmic mRNA translation into IgG, (iv) IgG systemic distribution and target binding, and (v) transient cytokine elevation triggered by exogenous mRNA. Model development leveraged published in vitro and in vivo data from mice, rats, and non-human primates (NHPs). Allometric scaling principles and inter-species differences in LDLR expression enabled human translation. Sensitivity analysis identified critical translational bottlenecks. The model successfully recapitulated the time course of mRNA, expressed IgG, and cytokine/chemokine levels in mice following intravenous administration. For human predictions, simulations of receptor occupancy and systemic exposure of encoded antibody informed the selection of 0.01 mg/kg as the starting dose for first-in-human trials. By highlighting species-specific differences in nanoparticle processing and mRNA translation kinetics, this framework provides a rational basis for dose selection. Applicable to other mRNA-based protein therapeutics, this multiscale PK-TK model enhances translational predictability, streamlining clinical development.