Sr Director, QSP Lead Incyte Corporation Wilmington, Delaware, United States
Disclosure(s):
Limei Cheng, PhD: No relevant disclosure to display
Objectives: The development of dual-targeting T cell modulators is hindered by complex binding dynamics, limited early phase clinical data, and difficulty in characterizing their mechanism of action. To overcome these challenges and support decision-making in early-stage clinical development of novel therapies, we developed a minimal Quantitative Systems Pharmacology (mQSP) model for immuno-oncology (mQSP-IO) in solid tumors.
Methods: Building on the original QSP-IO platform developed by Popel’s group [1], we employed a modular approach to construct the mQSP-IO model. The model comprises four interconnected compartments—central, peripheral, tumor, and lymph node—linked via lymphatic transport, and incorporating T cell populations and binding interactions. Each physiological subsystem was developed as an independent module, with a modular approach also applied to parameter definitions. This structure facilitated streamlined parameter tracking and flexible refinement of the mQSP-IO model during development. For the investigated dual-targeting T cell modulators, the observed internal data were adapted to preserve qualitative dose-response behavior while removing sensitive information and were then replaced by realistic simulated observed data. The model was calibrated using publicly available data as well as proprietary simulated observed data and was then applied to simulate virtual patients and generate simulated scenario analysis.
Results: The mQSP-IO model was applied to simulate receptor occupancy dynamics of T cell modulators. The model differentiated two binding mechanisms of the T cell modulators and revealed that a first-arm oriented binding strategy provided a broader therapeutic window and higher trimer formation compared with a nonselective arm binding strategy. With a first-arm oriented binding mechanism, the first arm dominates the trimer formation process; monomeric binding of the second arm is rare and may only happen at high antibody concentration. Sensitivity analysis further highlighted the critical role of second-arm affinity and receptor density in shaping pharmacodynamic responses, not only concept-proving the advantages of a first-arm oriented binding strategy but also offering insights to guide dose selection and biomarker strategies.
Conclusions: We have developed a mQSP-IO model that preserves the essential components necessary to capture the dynamics and binding mechanisms of the IO system while requiring fewer data and being less complex than the full QSP-IO model. Our mQSP-IO model effectively tested potential binding mechanisms, providing insights into expected pharmacokinetic-pharmacodynamic responses, as well as aiding dose selection and the choice of predictive biomarkers in the clinical development of T cell modulators for the treatment of patients with solid tumors.
Citations: 1. Wang H, et al. Dynamics of tumor-associated macrophages in a quantitative systems pharmacology model of immunotherapy in triple-negative breast cancer. iScience. 2022;25(8):104702.
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