Computational exploration of mechanistic determinants of ADC pharmacokinetics using QSP modeling strategies

Abstract The pharmacokinetics of antibody drug conjugate (ADC) therapeutics typically show a discrepancy between the PK of total antibody (conjugated and unconjugated antibody) and that of conjugated antibody, carrying one or more payload molecules. This discrepancy is often attributed strictly to deconjugation (Kamath, 2014), however recent evidence suggests that the underlying mechanisms may be more complex. This work employs a computational quantitative systems pharmacology (QSP) approach that generates a hypotheses to better understand the impact of drug antibody ratio (DAR) and the resulting changes in molecular properties on overall PK and relative payload disposition as observed in preclinical and clinical studies. Our work establishes the benefit of using computational models to design novel ADCs and to optimize the discovery and development of existing ADCs to better enable clinical trial design. References: Kamath, A. V., and Iyer, S. (2014). Preclinical Pharmacokinetic Considerations for the Development of Antibody Drug Conjugates. Pharmaceutical Research, 32(11), 3470-3479. Citation Format: A. Katharina Wilkins, Andrew Matteson, Lore Gruenbaum, Jennifer Park, John M. Burke, Joshua F. Apgar. Computational exploration of mechanistic determinants of ADC pharmacokinetics using QSP modeling strategies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 4266.