Experimental Closed-Loop Control of Breast Cancer in Mice

Cancer therapy optimization is an issue that can be solved using the control engineering approach. An optimal therapy generation algorithm is presented and tested using a tractable mouse model of breast cancer. The optimized therapeutic protocol is calculated in a closed-loop manner at fixed time in...

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Bibliographic Details
Published in:Complexity (New York, N.Y.) N.Y.), 2022, Vol.2022 (1)
Main Authors: Kovács, Levente, Czakó, Bence, Siket, Máté, Ferenci, Tamás, Füredi, András, Gombos, Balázs, Szakács, Gergely, Drexler, Dániel András
Format: Article
Language:English
Subjects:
Algorithms
Approximation
Breast cancer
Chemotherapy
Control algorithms
Controllers
Drug dosages
Experiments
Feedback control
Growth models
Moving horizon state estimation
Nonlinear control
Numerical analysis
Optimization
Parameter estimation
Pharmacokinetics
Physiology
Prediction models
Predictive control
State estimation
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Summary:Cancer therapy optimization is an issue that can be solved using the control engineering approach. An optimal therapy generation algorithm is presented and tested using a tractable mouse model of breast cancer. The optimized therapeutic protocol is calculated in a closed-loop manner at fixed time instants, twice in a week. The controller consists of a nonlinear model predictive controller which uses the state estimation of a moving horizon estimator. The estimator also computes parameter estimates of the prediction model such that the time varying nature of tumor evolution can be captured. Results show that remission can be induced in a 28-day interval using the algorithm.
ISSN:1076-2787
1099-0526
DOI:10.1155/2022/9348166