Abstract 2732: A mathematical model for optimization of combination therapy involving targeted radionuclide and CAR-T cell therapy

Abstract

Abstract Background: Immunotherapy with chimeric antigen receptor - T (CAR-T) cells and targeted radionuclide therapy (TRT) are two highly promising therapies in cancer treatment. Often, these therapies show limited efficacy in complete eradication of cancer cells making the combination of these two therapies an attractive cancer treatment option. The complications involved in dosing and scheduling of these therapies make mathematical modeling an appropriate method for analyzing and predicting disease response to these therapies. Here we propose a mathematical model evaluating disease response to the combination of these two therapies and explore the optimization of their dosing and scheduling. Methods: An ordinary differential equation-based formalism is proposed for simulation of tumor response to CAR-T cell therapy as well as TRT. CAR-T cell dose and injected radioactivity was input to the model. Among others, key model parameters included tumor proliferation rate, tumor cell and CAR-T cell radiosensitivity, CAR-T cell killing rate, CAR-T cell decay rate indicating persistence. Preclinical experiments involving CS1- CAR-T cell therapy and 225Ac-DOTA-Daratumumab TRT in a multiple myeloma mice model were used to parameterize the model. Sensitivity study of the model parameters using overall survival (OS) and progression-free survival (PFS) as evaluation metrics, was performed to elucidate the parameters with highest impact. Results: OS and PFS were 97 and 55 days when CAR-T cell therapy was given prior to TRT as compared to OS of 43 days for untreated control mice. Sensitivity study of model parameters showed that tumor proliferation has the highest impact on survival metrics. For a ±50% change in tumor proliferation rate, OS changed by -41%/+111% and PFS changed by -62%/+147%. Similar changes in TRT injected activity and CAR-T cell dose changed OS by ± 15% and ±21% respectively. Accordingly, PFS changed by roughly ±32% and ±45% respectively. A variation of the interval between the therapies showed that faster growing tumors required a shorter interval between the two therapies. The sequence of therapies was also changed and TRT prior to CAR-T cell therapy demonstrated shorter PFS (43 days) due to the adverse effects of radiation on CAR-T cells. Conclusion: For a fixed dose of TRT and CAR-T cells, tumor proliferation rate was found to be the prime factor impacting therapy interval. The presented work shows the key parameters required for planning and optimizing preclinical experiments and clinical trials. Using disease, CAR-T cell and radionuclide-specific parameters as shown in this work as well as incorporating immune stimulating effects of radiation would make it an extremely potent tool for optimizing combination therapies. Citation Format: Vikram Adhikarla, Dennis Awuah, Alexander B. Brummer, Enrico Caserta, Amrita Krishnan, Flavia Pichiorri, Megan M. Minnix, John E. Shively, Jeffrey Y.C. Wong, Xiuli Wang, Russell C. Rockne. A mathematical model for optimization of combination therapy involving targeted radionuclide and CAR-T cell therapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2732.