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基于药物剂量调节机制的生物体组合治疗自适应控制。

Combination Therapy-Based Adaptive Control for Organism Using Medicine Dosage Regulation Mechanism.

出版信息

IEEE Trans Cybern. 2024 Jan;54(1):199-208. doi: 10.1109/TCYB.2022.3196003. Epub 2023 Dec 20.

Abstract

In this article, the optimal control strategy for organism is investigated by using the adaptive dynamic programming (ADP) method under the architecture of nonzero-sum games (NZSGs). First, a tumor model is established to formulate the interaction relationships among normal cells, tumor cells, endothelial cells, and the concentrations of drugs. Then, the ADP-based method of single-critic network architecture is proposed to approximate the coupled Hamilton-Jacobi equations (HJEs) under the medicine dosage regulation mechanism (MDRM). According to the game theory, the approximate MDRM-based optimal strategy can be derived, which is of great practical significance. Owing to the proposed mechanism, the dosages of the chemotherapy and anti-angiogenic drugs can be regulated timely and necessarily. Furthermore, the stability of the closed-loop system with the obtained strategy is analyzed via the Lyapunov theory. Finally, a simulation experiment is conducted to verify the effectiveness of the proposed method.

摘要

本文采用非零和博弈(NZSGs)架构下的自适应动态规划(ADP)方法,研究了生物的最优控制策略。首先,建立肿瘤模型,以制定正常细胞、肿瘤细胞、内皮细胞和药物浓度之间的相互作用关系。然后,提出基于单评论家网络架构的 ADP 方法,以逼近药物剂量调节机制(MDRM)下的耦合 Hamilton-Jacobi 方程(HJE)。根据博弈论,可以推导出近似的基于 MDRM 的最优策略,这具有重要的实际意义。由于所提出的机制,化疗和抗血管生成药物的剂量可以及时且必要地进行调节。此外,通过 Lyapunov 理论分析了获得的策略的闭环系统的稳定性。最后,通过仿真实验验证了所提出方法的有效性。

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