Mathematical Modeling and Optimal Control of Combined Virotherapy and Adoptive T Cell Therapy for Cancer Treatment

ABSTRACT In this study, we investigate the synergistic roles of adoptive T cell therapy (ACT), specifically using tumor‐infiltrating lymphocytes (TILs) and oncolytic virus (OV) therapy in enhancing cancer treatment efficacy. While OVs can initiate tumor destruction, they often fail to achieve complete tumor eradication or generate a strong antitumor immune response. ACT with TILs can enhance this immune response, making OV therapy more effective. Conversely, in some cancer types, where cancer cells show low responsiveness to ACT, OV therapy can improve outcomes by converting “cold” tumors into “hot” tumors, increasing their susceptibility to immunotherapy. To explore these interactions, we developed and analyzed a mathematical model that captures the dynamics of tumor cells, OVs, immune responses enhanced by TIL therapy, and interleukin‐2 (IL‐2) as an immune‐stimulating agent. Qualitative analysis of the model revealed that monotherapies, either virotherapy or IL‐2 immunotherapy, can reduce tumor burden but are insufficient for complete eradication. In contrast, TIL therapy alone or in combination with IL‐2 shows potential for complete tumor clearance. Furthermore, the combination of virotherapy and IL‐2 leads to enhanced immune activation and improved tumor control, even when total eradication is not achieved. Notably, the combination of TIL therapy, IL‐2 immunotherapy, and virotherapy leads to complete tumor eradication. To identify the influence of model parameters on treatment outcomes, particularly tumor cell dynamics and oncolytic virus (OV) behavior, we conducted a sensitivity analysis using latin hypercube sampling (LHS) and computed partial rank correlation coefficients (PRCCs) along with their associated ‐values. This analysis offers valuable insights into the roles of specific parameters in tumor progression, immune‐virus interactions, and viral sustainability. The immune‐mediated killing rate of uninfected tumor cells and TIL therapy consistently emerged as strong contributors to tumor suppression across all time points. In contrast, the infection rate and viral burst size played critical roles in sustaining OV levels, though they have limited impact on tumor reduction, especially in the early stages of treatment. The infected cell lysis rate strongly contributed to OV suppression during early treatment but shifted toward supporting viral maintenance in later stages. Additionally, the tumor growth rate was found to support OV persistence throughout the treatment timeline. Model simulations further demonstrated that higher infection rates and burst sizes are associated with more substantial tumor reduction. Additionally, the results also demonstrated that increased TIL therapy led to a greater tumor reduction. To optimize the therapeutic strategy, we employed an optimal control framework to determine the ideal dosing regimen. The numerical results of the optimal control problem demonstrate that, although immunotherapy (combining ACT therapy and IL‐2) and virotherapy individually contribute.