[SS09] Enhancing Drug Development and Patient Care through Model Informed Drug Development

[SS09-08] QSP support in Oncology Drug Development - Case Studies from ADC & TCE translation & Early clinical decision-making

*Rukmini Kumar¹ (1. Vantage Research Inc. (India))

Keywords:

Model informed Drug Development (MIDD),Quantitative & Systems Pharmacology (QSP),Antibody Drug Conjugate (ADC),T Cell Engager (TCE),First In Human

Several new modalities of treating cancers have recently emerged and have been a source of optimism. In particular, Antibody drug Conjugates (ADCs) and TCE (T Cell Engagers) are therapies targeted to antigens expressed in tumor cells and direct cytotoxic payload or antigen-specific T Cells to kill tumor cells. In both cases, the specificity can potentially for greater tumor growth inhibition. However, off-target toxicities such as cytopenia and cytokine release syndrome (CRS) have to be considered when determining dose. Quantitative Systems Pharmacology (QSP) models that capture drug mechanisms of action can support decision making in various stages of drug development. In particular, in this talk, we will show case studies on determining “First in Human” dose, based on data from preclinical species (usually efficacy data from xenograft mouse models and safety & pharmacokinetic (PK) data from cynomologus monkeys). Secondly, early clinical cohort data (where dose is being escalated) needs to be absorbed in real time into QSP platforms and refined predictions on the alternate dosing strategies for expanded cohorts can be evaluated using simulation strategies (e.g. digital twins). Quantitative, integrative approaches can lead to more rapid identification of optimized dosing strategies improving time to approval and patient outcomes.