Optimal dynamic control approach in a multi-objective therapeutic scenario: application to drug delivery in the treatment of prostate cancer
Keywords: 
Computational biology
Optimization problems
Dosing schedules
Anticancer agents
Issue Date: 
2018
Publisher: 
Public Library of Science
ISSN: 
1553-7358
Note: 
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Citation: 
Irurzun-Arana, I. (Itziar); Janda, A. (Álvaro); Ardanza-Trevijano, S. (Sergio); et al. "Optimal dynamic control approach in a multi-objective therapeutic scenario: application to drug delivery in the treatment of prostate cancer". Plos computational biology. 14 (4), 2018, e1006087
Abstract
Numerous problems encountered in computational biology can be formulated as optimization problems. In this context, optimization of drug release characteristics or dosing schedules for anticancer agents has become a prominent area not only for the development of new drugs, but also for established drugs. However, in complex systems, optimization of drug exposure is not a trivial task and cannot be efficiently addressed through trial-error simulation exercises. Finding a solution to those problems is a challenging task which requires more advanced strategies like optimal control theory. In this work, we perform an optimal control analysis on a previously developed computational model for the testosterone effects of triptorelin in prostate cancer patients with the goal of finding optimal drug-release characteristics. We demonstrate how numerical control optimization of non-linear models can be used to find better therapeutic approaches in order to improve the final outcome of the patients.

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