Mathematical Modeling of Immunotherapy for Tumors: Computational Analysis of Adoptive Cell Therapy with Interleukin-2
DOI:
https://doi.org/10.32635/2176-9745.RBC.2024v70n1.4446Keywords:
Models, Theoretical, Computer Simulation, Immunotherapy, Adoptive, Neoplasms/epidemiologyAbstract
Introduction: Cancer is one of the main causes of death in the world, but there are still unknown aspects of its dynamics. An important tool for its study is mathematical modeling, which analyzes and projects tumor behavior. A model must be validated in silico to be useful. Objective: Validate a mathematical model for immunotherapy against tumors, to evaluate how the cellular composition of the adoptive cell therapy interferes with the response and which is the most appropriate scheme for administering interleukin-2 in terms of dose and time of use. Method: An ordinary differential equation model was developed. The parameters were obtained from the literature, adapted or simulated. The solutions were found using Octave 8.1.0 software and compared with the literature. Results: The results, compared with data from clinical trials and other modeling, show that the model is valid for reproducing tumor dynamics. In addition, infusion of adoptive cell therapy with a predominance of CD8+ T lymphocytes appears slightly more advantageous than infusion with a predominance of CD4+ T lymphocytes; high but tolerable doses of interleukin-2 generate a better anti-tumor response; and longer administration of interleukin-2 maximizes the response. Conclusion: The model is valid for studying tumor dynamics and can help in the development of new research. In addition, immunotherapy with a predominance of CD8+ T lymphocytes over CD4+ T lymphocytes and with interleukin-2 in higher doses and for longer periods, respecting tolerance, showed better results in silico.
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