A Mechanistic, Multiscale Mathematical Model of Immunogenicity for Therapeutic Proteins: Part 1—Theoretical Model

Abstract

A mechanistic, multiscale mathematical model of immunogenicity for therapeutic proteins was formulated by recapitulating key biological mechanisms, including antigen presentation, activation, proliferation, and differentiation of immune cells, secretion of antidrug antibodies (ADA), as well as in vivo disposition of ADA and therapeutic proteins. This system-level model contains three scales: a subcellular level representing antigen presentation processes by dendritic cells; a cellular level accounting for cell kinetics during humoral immune response; and a whole-body level accounting for therapeutic protein in vivo disposition. The model simulations for in vivo responses against antigenic protein challenge are consistent with many known immunological observations. By simulating immune responses under various initial parameter conditions, the model suggests hypotheses for future experimental investigation and contributes to the mechanistic understanding of immunogenicity. With future experimental validation, this model may potentially provide a platform to generate and test hypotheses about immunogenicity risk assessment and ultimately aid in immunogenicity prediction.

QSP Toolbox: Computational Implementation of Integrated Workflow Components for Deploying Multi-Scale Mechanistic Models

“…However, it is possible to use the examples as a starting point, and functions are provided to support the analysis (type Bhelp evaluateCorrelations^ (64). Functions to support a basic control coefficient analysis of sensitivity, similar to that applied to a model of immunogenicity (65), are provided (type Bhelp runControlCoefficientsSimulations^and Bhelp calculateControlCoefficients^). We also do not demonstrate implementation of pharmacokinetic (PK) variability according to a defined population model here, but for other projects we have implemented such variability by including the PK parameters as mechanistic axes and performing multivariate sampling for their coefficients from an established population PK model to set the axis coefficients.…”

Importance of Feedback and Feedforward Loops to Adaptive Immune Response Modeling

“…It will also help designing the de‐immunization strategy to reduce the overall immunogenicity. Recently, several mathematical models of the immune system have been developed to predict immunogenicity of drug therapeutics 93, 95, 96, 97. The investigation of feedback‐FFLs in the immune system is lacking, with some notable exceptions 98, 99, 100.…”

Therapeutic outcomes, assessments, risk factors and mitigation efforts of immunogenicity of therapeutic protein products

“…Algorithm development efforts would benefit from studies directed at identifying sequence motifs of peptides presented following MHC II-binding and HLA-DM editing. Recently, mechanistic and multiscale mathematical models have been proposed to simulate ADA formation over time [120][121][122]. These models provide estimation and forward simulations of TPP PK data and ADA formation, and could conceivably capture well-characterized immunological phenomena such as memory response and antibody affinity maturation.…”