A Mechanistic, Multiscale Mathematical Model of Immunogenicity for Therapeutic Proteins: Part 2—Model Applications

Abstract

A mechanistic, multiscale mathematical model of immunogenicity for therapeutic proteins was built by recapitulating key underlying known biological processes for immunogenicity. The model is able to simulate immune responses based on protein-specific antigenic properties (e.g., number of T-epitopes and their major histocompatibility complex (MHC)-II binding affinities) and host-specific immunological/physiological characteristics (e.g., MHC-II allele genotype, drug clearance rate). Preliminary validation was performed using mouse studies with antigens such as ovalbumin (OVA) or OVA-derived peptide. Further, using adalimumab as an example therapeutic protein, the model is able to simulate immune responses against adalimumab in individual subjects and in a population, and also provides estimations of immunogenicity incidence and drug exposure reduction that can be validated experimentally. This is a first attempt at modeling immunogenicity of biologics, so the model simulations should be used to help understand the immunogenicity mechanisms and impacting factors, rather than making direct predictions. This prototype model needs to be subjected to extensive experimental validation and refinement before fulfilling its ultimate mission of predicting immunogenicity. Nevertheless, the current model could potentially set up the starting framework to integrate various in silico, in vitro, in vivo, and clinical immunogenicity assessment results to help meet the challenge of immunogenicity prediction.