A Semi-Mechanistic Mathematical Model of Immune Tolerance Induction to Support Preclinical Studies of Human Monoclonal Antibodies in Rats

<b>Background/Objectives:</b> The administration of human monoclonal antibodies (mAb) in preclinical pharmacokinetics and toxicology studies often triggers an immune response, leading to the formation of anti-drug antibodies (ADA). To mitigate this effect, we have recently performed and reported on studies using short-term immunosuppressive regimens to induce prolonged immune tolerance towards a human mAb, erenumab, in rats. Here, we report on the development of a semi-mechanistic modeling approach that quantitatively integrates pharmacokinetic and immunogenicity assessments from immune tolerance induction studies to provide a framework for the simulation-based evaluation of different immune induction scenarios for the maintenance of prolonged immune tolerance towards human mAbs. <b>Methods:</b> The integrated pharmacokinetic/pharmacodynamic (PK/PD) modeling approach combined a semi-mechanistic model of the adaptive immune system to predict ADA formation kinetics with a population pharmacokinetic model to assess the impact of the time course of the ADA magnitude on the PK of erenumab in rats. Model-derived erenumab concentration-time profiles served as input for a quantitative system pharmacology-style semi-mechanistic model of the adaptive immune system to conceptualize the ADA response as a function of the kinetics of CD4⁺ T helper cells and T regulatory cells. <b>Results:</b> The model adequately described the observed ADA magnitude-time profiles in all treatment groups and reasonably simulated the kinetics of selected immune cells responsible for ADA formation. It also successfully captured the impact of tacrolimus/sirolimus immunomodulation on ADA formation, demonstrating that the regimen effectively suppressed ADA formations and induced immune tolerance. <b>Conclusions</b>: This work demonstrates the utility of modeling approaches to integrate pharmacokinetic and immunogenicity assessment data for the prospective planning of long-term toxicology studies to support the preclinical development of mAbs.