title: The utility of modeling and simulation approaches to evaluate immunogenicity effect on the therapeutic protein pharmacokinetics.
abstract: While therapeutic proteins (TP), particularly recombinant human proteins and fully human monoclonal antibodies, are designed to have a low immunogenic potential in humans, a clinical immune response does sometimes occur and cannot be predicted from preclinical studies. Changes in TP pharmacokinetics may be perceived as an early indication of antibody formation and serve as a surrogate for later changes in efficacy and safety in individual subjects. Given the substantial increase in number of biological products, including biosimilars, there is an urgent need to quantitatively predict and quantify the immune response and any consequential changes in TP pharmacokinetics. The purpose of this communication is to review the utility of population-based modeling and simulation approaches developed to date for investigating the development of an immune response and assessing its impact on TP pharmacokinetics. Two examples of empirical modeling approaches for pharmacokinetic assessment are presented. The first example presents methods to analyze pharmacokinetic data in the presence of anti-drug antibody (ADA) and confirm the effect of immunogenicity on TP pharmacokinetics in early phases of drug development. The second example provides a framework to analyze pharmacokinetic data in the absence or with very low incidence of ADA and confirm with enough power the lack of an immunogenicity effect on TP pharmacokinetics in late phases of drug development. Finally, a theoretical mechanism-based modeling framework is presented to mathematically relate the complex interaction among TP, their targets, and ADA.
authors.affiliation: Quantitative Pharmacology, Department of Pharmacokinetics and Drug Metabolism, Amgen Inc., One Amgen Center Drive, Thousand Oaks, CA 91320, USA.
authors.forename: Juan Jose
authors.initials: JJ
authors.lastname: Perez Ruixo
authors.forename: Peiming
authors.initials: P
authors.lastname: Ma
authors.forename: Andrew T
authors.initials: AT
authors.lastname: Chow
mesh_terms: D000911:Antibodies, Monoclonal / Q000276:immunology* / Q000493:pharmacokinetics*; D061067:Antibodies, Monoclonal, Humanized; D003198:Computer Simulation; D006801:Humans; D008954:Models, Biological
chemical_list: C549611:AMG 317; D000911:Antibodies, Monoclonal; D061067:Antibodies, Monoclonal, Humanized