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arXiv · 2511.05527

A Mechanistic Framework for in Silico Optimization of Neuroblastoma Chemo-Immunotherapy

Kate Brockman·Brian Colburn·Joseph Garza·Yidong Liao·B. Veena S. N. Rao
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Abstract

A critical need exists for optimal therapeutic strategies for neuroblastoma, a prevalent and often fatal pediatric solid malignancy. To address the demand for quantitative models that can guide clinical decision-making, a novel mathematical framework was developed. Combination therapies involving immunotherapy, such as Interleukin-2 (IL-2), and chemotherapy, exemplified by Cyclophosphamide, have shown significant clinical potential by enhancing anti-tumor immune responses. In this study, a nonlinear system of coupled ordinary differential equations was formulated to mechanistically describe the interactions among tumor cells, natural killer (NK) cells, and cytotoxic T lymphocytes (CTLs). The pharmacodynamic effects of both IL-2 and Cyclophosphamide on these key immune populations were explicitly incorporated, allowing for the simulation of tumor dynamics across distinct patient risk profiles. The resulting computational framework provides a robust platform for the \textit{\textbf{in silico}} \textbf{optimization} of therapeutic regimens, presenting a quantitative pathway toward the improvement of clinical outcomes for patients with neuroblastoma.

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Kate Brockman, Brian Colburn, Joseph Garza, Yidong Liao, B. Veena S. N. Rao. 2025-10-28. A Mechanistic Framework for in Silico Optimization of Neuroblastoma Chemo-Immunotherapy. https://arxiv.org/abs/2511.05527

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