Optimal Treatment of Prostate Cancer Based on State Constraint

As a new tumor therapeutic strategy, adaptive therapy involves utilizing the competition between cancer cells to suppress the growth of drug-resistant cells, maintaining a certain tumor burden. However, it is difficult to determine the appropriate time and drug dose. In this paper, we consider the c...

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Bibliographic Details
Published in:Mathematics (Basel) 2023-09, Vol.11 (19), p.4025
Main Authors: Luo, Wenhui, Tan, Xuewen, Zou, Xiufen, Tan, Qing
Format: Article
Language:English
Subjects:
Analysis
Cancer
Cancer therapies
Care and treatment
Chemotherapy
Competition
Drug dosages
Drug resistance
Drug therapy
drug toxicity
Health aspects
Mathematical models
Numerical analysis
optimal control
Pharmacokinetics
problems in pharmacology
Prostate cancer
Simulation methods
state constraints
Strategy
Titration
Toxicity
tumor burden
Tumors
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Summary:As a new tumor therapeutic strategy, adaptive therapy involves utilizing the competition between cancer cells to suppress the growth of drug-resistant cells, maintaining a certain tumor burden. However, it is difficult to determine the appropriate time and drug dose. In this paper, we consider the competition model between drug-sensitive cells and drug-resistant cells, propose the problem of drug concentration, and provide two state constraints: the upper limit of the maximum allowable drug concentration and the tumor burden. Using relevant theories, we propose the best treatment strategy. Through a numerical simulation and quantitative analysis, the effects of drug concentrations and different tumor burdens on treatments are studied, and the effects of cell-to-cell competitive advantage on cell changes are taken into account. The clinical dose titration method is further simulated; the results show that our therapeutic regimen can better suppress the growth of drug-resistant cells, control the tumor burden, limit drug toxicity, and extend the effective treatment time.
ISSN:2227-7390
2227-7390
DOI:10.3390/math11194025