Mathematical Modeling of HIV Dynamics After Antiretroviral Therapy Initiation: A Review
Identifieur interne : 000234 ( Main/Exploration ); précédent : 000233; suivant : 000235Mathematical Modeling of HIV Dynamics After Antiretroviral Therapy Initiation: A Review
Auteurs : Pablo S. Rivadeneira ; Claude H. Moog ; Guy-Bart Stan ; Cecile Brunet ; François Raffi ; Virginie Ferré ; Vicente Costanza ; Marie J. Mhawej ; Federico Biafore ; Djomangan A. Ouattara ; Damien Ernst ; Raphael Fonteneau ; Xiaohua XiaSource :
- BioResearch Open Access [ 2164-7844 ] ; 2014.
Abstract
This review shows the potential ground-breaking impact that mathematical tools may have in the analysis and the understanding of the HIV dynamics. In the first part, early diagnosis of immunological failure is inferred from the estimation of certain parameters of a mathematical model of the HIV infection dynamics. This method is supported by clinical research results from an original clinical trial: data just after 1 month following therapy initiation are used to carry out the model identification. The diagnosis is shown to be consistent with results from monitoring of the patients after 6 months. In the second part of this review, prospective research results are given for the design of individual anti-HIV treatments optimizing the recovery of the immune system and minimizing side effects. In this respect, two methods are discussed. The first one combines HIV population dynamics with pharmacokinetics and pharmacodynamics models to generate drug treatments using impulsive control systems. The second one is based on optimal control theory and uses a recently published differential equation to model the side effects produced by highly active antiretroviral therapy therapies. The main advantage of these revisited methods is that the drug treatment is computed directly in amounts of drugs, which is easier to interpret by physicians and patients.
Url:
DOI: 10.1089/biores.2014.0024
PubMed: 25371860
PubMed Central: 4215334
Affiliations:
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<front><div type="abstract" xml:lang="en"><title>Abstract</title>
<p>This review shows the potential ground-breaking impact that mathematical tools may have in the analysis and the understanding of the HIV dynamics. In the first part, early diagnosis of immunological failure is inferred from the estimation of certain parameters of a mathematical model of the HIV infection dynamics. This method is supported by clinical research results from an original clinical trial: data just after 1 month following therapy initiation are used to carry out the model identification. The diagnosis is shown to be consistent with results from monitoring of the patients after 6 months. In the second part of this review, prospective research results are given for the design of individual anti-HIV treatments optimizing the recovery of the immune system and minimizing side effects. In this respect, two methods are discussed. The first one combines HIV population dynamics with pharmacokinetics and pharmacodynamics models to generate drug treatments using impulsive control systems. The second one is based on optimal control theory and uses a recently published differential equation to model the side effects produced by highly active antiretroviral therapy therapies. The main advantage of these revisited methods is that the drug treatment is computed directly in amounts of drugs, which is easier to interpret by physicians and patients.</p>
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