Learn–confirm in model‐informed drug development: Assessing an immunogenicity quantitative systems pharmacology platform

Abstract

Abstract Immunogenicity against therapeutic proteins frequently causes attrition owing to its potential impact on pharmacokinetics, pharmacodynamics, efficacy, and safety. Predicting immunogenicity is complex because of its multifactorial drivers, including compound properties, subject characteristics, and treatment parameters. To integrate these, the Immunogenicity Simulator was developed using published, predominantly late‐stage trial data from 15 therapeutic proteins. This single‐blinded evaluation with subject‐level data from 10 further monoclonals assesses the Immunogenicity Simulator's credibility for application during the drug development process.