Optimal Control Theory for Personalized Therapeutic Regimens in Oncology: Background, History, Challenges, and Opportunities
Optimal control theory is branch of mathematics that aims to optimize a solution to a dynamical system. While the concept of using optimal control theory to improve treatment regimens in oncology is not novel, many of the early applications of this mathematical technique were not designed to work wi...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-05-01
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| Series: | Journal of Clinical Medicine |
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| Online Access: | https://www.mdpi.com/2077-0383/9/5/1314 |
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| author | Angela M. Jarrett Danial Faghihi David A. Hormuth Ernesto A. B. F. Lima John Virostko George Biros Debra Patt Thomas E. Yankeelov |
| author_facet | Angela M. Jarrett Danial Faghihi David A. Hormuth Ernesto A. B. F. Lima John Virostko George Biros Debra Patt Thomas E. Yankeelov |
| author_sort | Angela M. Jarrett |
| collection | DOAJ |
| description | Optimal control theory is branch of mathematics that aims to optimize a solution to a dynamical system. While the concept of using optimal control theory to improve treatment regimens in oncology is not novel, many of the early applications of this mathematical technique were not designed to work with routinely available data or produce results that can eventually be translated to the clinical setting. The purpose of this review is to discuss clinically relevant considerations for formulating and solving optimal control problems for treating cancer patients. Our review focuses on two of the most widely used cancer treatments, radiation therapy and systemic therapy, as they naturally lend themselves to optimal control theory as a means to personalize therapeutic plans in a rigorous fashion. To provide context for optimal control theory to address either of these two modalities, we first discuss the major limitations and difficulties oncologists face when considering alternate regimens for their patients. We then provide a brief introduction to optimal control theory before formulating the optimal control problem in the context of radiation and systemic therapy. We also summarize examples from the literature that illustrate these concepts. Finally, we present both challenges and opportunities for dramatically improving patient outcomes <i>via</i> the integration of clinically relevant, patient-specific, mathematical models and optimal control theory. |
| first_indexed | 2024-03-10T20:04:09Z |
| format | Article |
| id | doaj.art-15ea1173593444fe830c27f394619e6a |
| institution | Directory Open Access Journal |
| issn | 2077-0383 |
| language | English |
| last_indexed | 2024-03-10T20:04:09Z |
| publishDate | 2020-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Clinical Medicine |
| spelling | doaj.art-15ea1173593444fe830c27f394619e6a2023-11-19T23:21:00ZengMDPI AGJournal of Clinical Medicine2077-03832020-05-0195131410.3390/jcm9051314Optimal Control Theory for Personalized Therapeutic Regimens in Oncology: Background, History, Challenges, and OpportunitiesAngela M. Jarrett0Danial Faghihi1David A. Hormuth2Ernesto A. B. F. Lima3John Virostko4George Biros5Debra Patt6Thomas E. Yankeelov7Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, TX 78712, USADepartment of Mechanical and Aerospace Engineering, The University at Buffalo, Buffalo, NY 14260, USAOden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, TX 78712, USAOden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, TX 78712, USALivestrong Cancer Institutes, The University of Texas at Austin, Austin, TX 78712, USAOden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, TX 78712, USATexas Oncology, Austin, TX 78731, USAOden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, TX 78712, USAOptimal control theory is branch of mathematics that aims to optimize a solution to a dynamical system. While the concept of using optimal control theory to improve treatment regimens in oncology is not novel, many of the early applications of this mathematical technique were not designed to work with routinely available data or produce results that can eventually be translated to the clinical setting. The purpose of this review is to discuss clinically relevant considerations for formulating and solving optimal control problems for treating cancer patients. Our review focuses on two of the most widely used cancer treatments, radiation therapy and systemic therapy, as they naturally lend themselves to optimal control theory as a means to personalize therapeutic plans in a rigorous fashion. To provide context for optimal control theory to address either of these two modalities, we first discuss the major limitations and difficulties oncologists face when considering alternate regimens for their patients. We then provide a brief introduction to optimal control theory before formulating the optimal control problem in the context of radiation and systemic therapy. We also summarize examples from the literature that illustrate these concepts. Finally, we present both challenges and opportunities for dramatically improving patient outcomes <i>via</i> the integration of clinically relevant, patient-specific, mathematical models and optimal control theory.https://www.mdpi.com/2077-0383/9/5/1314mathematical modelcancer treatmentpredicting responseoptimizing response |
| spellingShingle | Angela M. Jarrett Danial Faghihi David A. Hormuth Ernesto A. B. F. Lima John Virostko George Biros Debra Patt Thomas E. Yankeelov Optimal Control Theory for Personalized Therapeutic Regimens in Oncology: Background, History, Challenges, and Opportunities Journal of Clinical Medicine mathematical model cancer treatment predicting response optimizing response |
| title | Optimal Control Theory for Personalized Therapeutic Regimens in Oncology: Background, History, Challenges, and Opportunities |
| title_full | Optimal Control Theory for Personalized Therapeutic Regimens in Oncology: Background, History, Challenges, and Opportunities |
| title_fullStr | Optimal Control Theory for Personalized Therapeutic Regimens in Oncology: Background, History, Challenges, and Opportunities |
| title_full_unstemmed | Optimal Control Theory for Personalized Therapeutic Regimens in Oncology: Background, History, Challenges, and Opportunities |
| title_short | Optimal Control Theory for Personalized Therapeutic Regimens in Oncology: Background, History, Challenges, and Opportunities |
| title_sort | optimal control theory for personalized therapeutic regimens in oncology background history challenges and opportunities |
| topic | mathematical model cancer treatment predicting response optimizing response |
| url | https://www.mdpi.com/2077-0383/9/5/1314 |
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