Immunogenicity Prediction and Dose Optimization using Clinically-Validated In Silico Modeling & Simulation

Immunogenicity Prediction and Dose Optimization using Clinically-Validated In Silico Modeling & Simulation

As defined by the US FDA, Immunogenicity (IG) is the ability of a therapeutic product to trigger an immune response in the body. That response can be desired IG to support vaccine and allergen response or undesired IG causing immunologically related adverse events. Figure 1 provides a summary of the types of impact from undesired IG. This white paper focuses on how modeling and simulation (also called model-informed drug development or MIDD) and specifically, a quantitative systems pharmacology (QSP)-based approach can be used to predict and better manage undesired IG (and in the case of vaccines, desired IG) and as a tool to guide clinical and regulatory decision-making in drug development.

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