Numerical-analytical method optimizes multi-stage neuroblastoma therapy, suggesting enhanced decision-making efficacy.
A numerical-analytical method for optimizing multi-stage high-risk neuroblastoma therapy is proposed, based on the differential transform method and a terminal control framework. The mathematical model of the “tumor-neuropil-immunity-pharmacokinetics” system is formulated in spectral form, enabling optimal control synthesis without numerical integration of the system of differential equations. The proposed approach yields a compact recurrent representation of the dynamics, an analytical form of the optimal control law, and a closed-loop control algorithm robust to parameter perturbations and individual patient responses. It is shown that the method provides significant computational acceleration compared to gradient-based optimization, making it suitable for near-real-time clinical decision support systems.
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Andriy Gusynin (2026) studied this question.
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