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Nonlinear Adaptive Optimal Controller Design for Anti-Angiogenic Tumor Treatment
Angiogenesis is an important process in tumor growth as it represents the regime when the tumor recruits blood vessels from the surrounding tissue to support further tumor growth. Anti-angiogenic treatments aim to shrink the tumor by interrupting the vascularization of the tumor; however, the anti-a...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9953489/ https://www.ncbi.nlm.nih.gov/pubmed/36831033 http://dx.doi.org/10.3390/biomedicines11020497 |
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author | Nath, Nitendra Kil, Irfan Hasirci, Ugur Groff, Richard E. Burg, Timothy C. |
author_facet | Nath, Nitendra Kil, Irfan Hasirci, Ugur Groff, Richard E. Burg, Timothy C. |
author_sort | Nath, Nitendra |
collection | PubMed |
description | Angiogenesis is an important process in tumor growth as it represents the regime when the tumor recruits blood vessels from the surrounding tissue to support further tumor growth. Anti-angiogenic treatments aim to shrink the tumor by interrupting the vascularization of the tumor; however, the anti-angiogenic agents are costly and the tumor response to these agents is nonlinear. Simple dosing schemes, e.g., a constant dose, may yield higher cost or lower efficacy than an approach that considers the tumor system dynamics. Hence, in this study, the administration of anti-angiogenic treatment is considered as a nonlinear control problem. The main aim of the controller design is to optimize the anti-angiogenic tumor therapy, specifically, to minimize the tumor volume and drug dose. Toward this aim, two nonlinear optimal controllers are presented. The first controller ensures exponential tracking of a desired, optimal tumor volume profile under the assumption that all parameters in the system model are known. The second controller, on the other hand, assumes all the parameters are unknown and provides asymptotic tracking. Both controllers take pharmacokinetics and pharmacodynamics into account, as well as the carrying capacity of the vascular network. Lyapunov based arguments are used to design the controllers, using stability arguments, and numerical simulation results are presented to demonstrate the effectiveness of the proposed method. |
format | Online Article Text |
id | pubmed-9953489 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-99534892023-02-25 Nonlinear Adaptive Optimal Controller Design for Anti-Angiogenic Tumor Treatment Nath, Nitendra Kil, Irfan Hasirci, Ugur Groff, Richard E. Burg, Timothy C. Biomedicines Article Angiogenesis is an important process in tumor growth as it represents the regime when the tumor recruits blood vessels from the surrounding tissue to support further tumor growth. Anti-angiogenic treatments aim to shrink the tumor by interrupting the vascularization of the tumor; however, the anti-angiogenic agents are costly and the tumor response to these agents is nonlinear. Simple dosing schemes, e.g., a constant dose, may yield higher cost or lower efficacy than an approach that considers the tumor system dynamics. Hence, in this study, the administration of anti-angiogenic treatment is considered as a nonlinear control problem. The main aim of the controller design is to optimize the anti-angiogenic tumor therapy, specifically, to minimize the tumor volume and drug dose. Toward this aim, two nonlinear optimal controllers are presented. The first controller ensures exponential tracking of a desired, optimal tumor volume profile under the assumption that all parameters in the system model are known. The second controller, on the other hand, assumes all the parameters are unknown and provides asymptotic tracking. Both controllers take pharmacokinetics and pharmacodynamics into account, as well as the carrying capacity of the vascular network. Lyapunov based arguments are used to design the controllers, using stability arguments, and numerical simulation results are presented to demonstrate the effectiveness of the proposed method. MDPI 2023-02-08 /pmc/articles/PMC9953489/ /pubmed/36831033 http://dx.doi.org/10.3390/biomedicines11020497 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Nath, Nitendra Kil, Irfan Hasirci, Ugur Groff, Richard E. Burg, Timothy C. Nonlinear Adaptive Optimal Controller Design for Anti-Angiogenic Tumor Treatment |
title | Nonlinear Adaptive Optimal Controller Design for Anti-Angiogenic Tumor Treatment |
title_full | Nonlinear Adaptive Optimal Controller Design for Anti-Angiogenic Tumor Treatment |
title_fullStr | Nonlinear Adaptive Optimal Controller Design for Anti-Angiogenic Tumor Treatment |
title_full_unstemmed | Nonlinear Adaptive Optimal Controller Design for Anti-Angiogenic Tumor Treatment |
title_short | Nonlinear Adaptive Optimal Controller Design for Anti-Angiogenic Tumor Treatment |
title_sort | nonlinear adaptive optimal controller design for anti-angiogenic tumor treatment |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9953489/ https://www.ncbi.nlm.nih.gov/pubmed/36831033 http://dx.doi.org/10.3390/biomedicines11020497 |
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