Quantitative Systems Pharmacology Model Predicts Enhanced Antitumor Efficacy of Combined Cytotoxic T-Lymphocyte-Associated Protein 4 (CTLA-4) and Programmed Cell Death Protein 1 (PD-1) Blockade in a Syngeneic Mouse Model of Breast Cancer

Abstract Immune-checkpoint inhibitors targeting PD-1 and CTLA-4 have transformed cancer therapy, yet most patients still fail to respond, and the reasons remain incompletely understood. To dissect this heterogeneity and support translational development, we built a preclinical quantitative systems pharmacology model of α-PD-1, α-CTLA-4, and their combination in syngeneic mouse models, calibrating it jointly against vehicle, monotherapy, and combination tumor growth data. The calibrated model captures all four treatment arms across the measured time course and supports a mechanistic explanation for the observed tumor-growth inhibition based on two distinct mechanisms: α-PD-1 lifts the PD-1/PD-L1 brake on tumor-infiltrating effector T cells, while α-CTLA-4 depletes regulatory T cells, in the tumor and in the periphery, through Fc-dependent antibody-dependent cellular cytotoxicity, a mode of action specific to the syngeneic mouse setting and distinct from the clinical mechanism of ipilimumab. Because the two pathways engage different cell populations, the combination produces antitumor activity beyond what either drug achieves alone, with synergy analysis indicating approximately 4-fold reciprocal potency synergy. A virtual cohort of 500 mice reproduces this effect, expands the fraction of strong responders under combination therapy, and identifies the balance between IL-2-driven CD4+ and CD8+ T-cell expansion, together with intrinsic tumor growth rate, as the dominant determinants of interindividual response. Because the model shares its structural architecture with our previously published human QSP-IO platform, it provides a quantitative scaffold for guiding preclinical-to-clinical evaluation of checkpoint-combination strategies.