Sun Jiayue, Dai Jing, Zhang Huaguang, Yu Shuhang, Xu Shun, Wang Jiajun
IEEE Trans Cybern. 2023 Mar;53(3):1944-1953. doi: 10.1109/TCYB.2022.3179302. Epub 2023 Feb 15.
This article investigates optimal regulation scheme between tumor and immune cells based on the adaptive dynamic programming (ADP) approach. The therapeutic goal is to inhibit the growth of tumor cells to allowable injury degree and maximize the number of immune cells in the meantime. The reliable controller is derived through the ADP approach to make the number of cells achieve the specific ideal states. First, the main objective is to weaken the negative effect caused by chemotherapy and immunotherapy, which means that the minimal dose of chemotherapeutic and immunotherapeutic drugs can be operational in the treatment process. Second, according to the nonlinear dynamical mathematical model of tumor cells, chemotherapy and immunotherapeutic drugs can act as powerful regulatory measures, which is a closed-loop control behavior. Finally, states of the system and critic weight errors are proved to be ultimately uniformly bounded with the appropriate optimization control strategy and the simulation results are shown to demonstrate the effectiveness of the cybernetics methodology.
本文基于自适应动态规划（ADP）方法研究肿瘤细胞与免疫细胞之间的最优调控方案。治疗目标是将肿瘤细胞的生长抑制到允许的损伤程度，同时使免疫细胞数量最大化。通过ADP方法推导可靠的控制器，以使细胞数量达到特定的理想状态。首先，主要目标是减弱化疗和免疫疗法所造成的负面影响，这意味着在治疗过程中可使用最小剂量的化疗和免疫治疗药物。其次，根据肿瘤细胞的非线性动力学数学模型，化疗和免疫治疗药物可作为有力的调控措施，这是一种闭环控制行为。最后，证明了在适当的优化控制策略下系统状态和评判权重误差最终一致有界，并给出仿真结果以证明控制论方法的有效性。
