霍普夫分叉
背景(考古学)
控制理论(社会学)
免疫疗法
效应器
数学
理论(学习稳定性)
免疫系统
分叉
最优控制
计算机科学
免疫学
医学
数学优化
控制(管理)
非线性系统
生物
物理
机器学习
古生物学
人工智能
量子力学
作者
Fathalla A. Rihan,K. Udhayakumar
标识
DOI:10.1016/j.chaos.2023.113670
摘要
The aim of this paper is to present a mathematical model of tumor vaccine efficacy in the context of immunotherapy treatment. The model is governed by fractional-order delay differential equations with a control variable. Transforming growth factor beta (TGF-β) inhibition alone gives limited clinical advantages, but when combined with a tumor vaccine, it can dramatically increase the immune system's anti-tumor response. The mathematical model takes into account tumor growth dynamics, TGF-β concentrations, cytotoxic effector cells, and regulatory T-cells. The non-negativity of the solutions to such a model has been examined. The steady-state stability and Hopf bifurcation of tumor time delays τ are investigated. An optimal fractional-order control problem is derived and analyzed in the presence of immunotherapy treatments. Using Adams–Bashforth–Moulton predictor–corrector algorithms, we illustrate numerical examples that confirm the analytical findings. The optimal control treatment method reduces the load of tumor cells while increasing the effector cells.
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