抗血管生成治疗和化疗在肿瘤中给药的最优控制方法。

IF 1.9 4区 生物学 Q4 CELL BIOLOGY IET Systems Biology Pub Date : 2021-02-01 Epub Date: 2021-01-25 DOI:10.1049/syb2.12010
Pariya Khalili, Sareh Zolatash, Ramin Vatankhah, Sajjad Taghvaei
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引用次数: 5

摘要

有许多数学模型通过考虑不同治疗策略(如化疗)的各种状态来模拟癌症的行为。在这些模型中,我们开发了一个能够考虑肿瘤附近血管生成(血管生成)和抗血管生成治疗效果的模型。在上述模型中,将正常细胞、癌细胞、内皮细胞、化疗药物和抗血管生成药物作为状态变量,并将后两者的注射速率作为控制输入。由于控制肿瘤的生长对患者的生命是一件具有挑战性的事情,因此药物注射的时间表设计非常重要。采用开环(变分法)和闭环(状态相关Riccati方程)两种最优控制策略对系统进行优化,以找到每次药物注射的最优时间调度。通过定义合适的代价函数,为每一种情况设计最优控制信号。两种得到的控制输入都有合理的答案,系统最终都得到了控制,但通过比较,两种方法都有各自的好处,这将在结论部分详细讨论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Optimal control methods for drug delivery in cancerous tumour by anti-angiogenic therapy and chemotherapy.

There are numerous mathematical models simulating the behaviour of cancer by considering variety of states in different treatment strategies, such as chemotherapy. Among the models, one is developed which is able to consider the blood vessel-production (angiogenesis) in the vicinity of the tumour and the effect of anti-angiogenic therapy. In the mentioned-model, normal cells, cancer cells, endothelial cells, chemotherapy and anti-angiogenic agents are taking into account as state variables, and the rate of injection of the last two are considered as control inputs. Since controlling the cancerous tumour growth is a challenging matter for patient's life, the time schedule design of drug injection is very significant. Two optimal control strategies, an open-loop (calculus of variations) and a closed-loop (state-dependent Riccati equation), are applied on the system in order to find an optimal time scheduling for each drug injection. By defining a proper cost function, an optimal control signal is designed for each one. Both obtained control inputs have reasonable answers, and the system is controlled eventually, but by comparing them, it is concluded that both methods have their own benefits which will be discussed in details in the conclusion section.

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来源期刊
IET Systems Biology
IET Systems Biology 生物-数学与计算生物学
CiteScore
4.20
自引率
4.30%
发文量
17
审稿时长
>12 weeks
期刊介绍: IET Systems Biology covers intra- and inter-cellular dynamics, using systems- and signal-oriented approaches. Papers that analyse genomic data in order to identify variables and basic relationships between them are considered if the results provide a basis for mathematical modelling and simulation of cellular dynamics. Manuscripts on molecular and cell biological studies are encouraged if the aim is a systems approach to dynamic interactions within and between cells. The scope includes the following topics: Genomics, transcriptomics, proteomics, metabolomics, cells, tissue and the physiome; molecular and cellular interaction, gene, cell and protein function; networks and pathways; metabolism and cell signalling; dynamics, regulation and control; systems, signals, and information; experimental data analysis; mathematical modelling, simulation and theoretical analysis; biological modelling, simulation, prediction and control; methodologies, databases, tools and algorithms for modelling and simulation; modelling, analysis and control of biological networks; synthetic biology and bioengineering based on systems biology.
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