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Probabilistically certified region of attraction of a tumor growth model with combined chemo‐ and immunotherapy
Author(s) -
Moussa Kaouther,
Fiacchini Mirko,
Alamir Mazen
Publication year - 2022
Publication title -
international journal of robust and nonlinear control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.361
H-Index - 106
eISSN - 1099-1239
pISSN - 1049-8923
DOI - 10.1002/rnc.6158
Subject(s) - certification , immunotherapy , probabilistic logic , parametric statistics , computer science , cancer , parametric model , order (exchange) , cancer immunotherapy , constraint (computer aided design) , medicine , artificial intelligence , mathematics , statistics , political science , economics , finance , law , geometry
The recent progress in immunology lead to a considerable interest in modeling cancer dynamics in order to better understand and analyze such complex systems. Many works have been carried out in order to design cancer treatment protocols using mathematical models. One of the main complexities of such models is the presence of different types of uncertainties, which remains less considered in the literature. This article deals with the estimation of regions of attraction (RoAs) under parametric uncertainties for a cancer growth model with combined therapies. We propose a framework of probabilistic certification, based on the randomized methods, in order to derive probabilistically certified RoAs of a cancer growth model. The model considered in this article describes the interaction between a tumor and the immune system in presence of a combined chemo‐ and immunotherapy treatment, with considerations on pharmacokinetics and pharmacodynamics of both treatments.