Discrete ARMA Model Applied for Tumor Growth Inhibition Modeling and LQR-based Chemotherapy Optimization
| Autor: | George S. Stavrakakis, Sotirios G. Liliopoulos |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Chemotherapy
State-space representation Mathematical model Computer science General Neuroscience medicine.medical_treatment General Medicine Linear-quadratic regulator Optimal control General Biochemistry Genetics and Molecular Biology Nonlinear system Control theory medicine Autoregressive–moving-average model General Agricultural and Biological Sciences |
| Zdroj: | WSEAS TRANSACTIONS ON BIOLOGY AND BIOMEDICINE. 18:141-145 |
| ISSN: | 2224-2902 1109-9518 |
| DOI: | 10.37394/23208.2021.18.17 |
| Popis: | Mathematical models for tumor growth inhibition (TGI) are an important tool in the battle against cancer allowing preclinical evaluation of potential anti-cancer drugs and treatment schedules. However, most of these models are nonlinear and their structure is based on complex hypotheses. Therefore, tumor growth mathematical models with simple structure and minimal number of parameters could be of great importance. In this article, an autoregressive moving average (ARMA) model for cancer tumor growth and equivalent its state space representation are estimated, presented and evaluated based on laboratory data of TGI in mice. The proposed model was proven capable of describing with accuracy the tumor growth under single-agent chemotherapy. At the same time, an optimal control problem was formulated to identify optimal drug dosages for the tumor eradication. The linear quadratic regulator (LQR) controller was used with success in optimizing both periodic and intermittent chemotherapy treatment schedules reducing the tumor mass while keeping dosages under acceptable toxicity |
| Databáze: | OpenAIRE |
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