Cargando…

Mathematical Modeling of HIV Dynamics After Antiretroviral Therapy Initiation: A Review

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 infe...

Descripción completa

Detalles Bibliográficos
Autores principales: Rivadeneira, Pablo S., Moog, Claude H., Stan, Guy-Bart, Brunet, Cecile, Raffi, François, Ferré, Virginie, Costanza, Vicente, Mhawej, Marie J., Biafore, Federico, Ouattara, Djomangan A., Ernst, Damien, Fonteneau, Raphael, Xia, Xiaohua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Mary Ann Liebert, Inc. 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4215334/
https://www.ncbi.nlm.nih.gov/pubmed/25371860
http://dx.doi.org/10.1089/biores.2014.0024
_version_ 1782342072895799296
author Rivadeneira, Pablo S.
Moog, Claude H.
Stan, Guy-Bart
Brunet, Cecile
Raffi, François
Ferré, Virginie
Costanza, Vicente
Mhawej, Marie J.
Biafore, Federico
Ouattara, Djomangan A.
Ernst, Damien
Fonteneau, Raphael
Xia, Xiaohua
author_facet Rivadeneira, Pablo S.
Moog, Claude H.
Stan, Guy-Bart
Brunet, Cecile
Raffi, François
Ferré, Virginie
Costanza, Vicente
Mhawej, Marie J.
Biafore, Federico
Ouattara, Djomangan A.
Ernst, Damien
Fonteneau, Raphael
Xia, Xiaohua
author_sort Rivadeneira, Pablo S.
collection PubMed
description 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.
format Online
Article
Text
id pubmed-4215334
institution National Center for Biotechnology Information
language English
publishDate 2014
publisher Mary Ann Liebert, Inc.
record_format MEDLINE/PubMed
spelling pubmed-42153342014-11-04 Mathematical Modeling of HIV Dynamics After Antiretroviral Therapy Initiation: A Review Rivadeneira, Pablo S. Moog, Claude H. Stan, Guy-Bart Brunet, Cecile Raffi, François Ferré, Virginie Costanza, Vicente Mhawej, Marie J. Biafore, Federico Ouattara, Djomangan A. Ernst, Damien Fonteneau, Raphael Xia, Xiaohua Biores Open Access Mini-Review 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. Mary Ann Liebert, Inc. 2014-10-01 /pmc/articles/PMC4215334/ /pubmed/25371860 http://dx.doi.org/10.1089/biores.2014.0024 Text en Copyright 2014, Mary Ann Liebert, Inc.
spellingShingle Mini-Review
Rivadeneira, Pablo S.
Moog, Claude H.
Stan, Guy-Bart
Brunet, Cecile
Raffi, François
Ferré, Virginie
Costanza, Vicente
Mhawej, Marie J.
Biafore, Federico
Ouattara, Djomangan A.
Ernst, Damien
Fonteneau, Raphael
Xia, Xiaohua
Mathematical Modeling of HIV Dynamics After Antiretroviral Therapy Initiation: A Review
title Mathematical Modeling of HIV Dynamics After Antiretroviral Therapy Initiation: A Review
title_full Mathematical Modeling of HIV Dynamics After Antiretroviral Therapy Initiation: A Review
title_fullStr Mathematical Modeling of HIV Dynamics After Antiretroviral Therapy Initiation: A Review
title_full_unstemmed Mathematical Modeling of HIV Dynamics After Antiretroviral Therapy Initiation: A Review
title_short Mathematical Modeling of HIV Dynamics After Antiretroviral Therapy Initiation: A Review
title_sort mathematical modeling of hiv dynamics after antiretroviral therapy initiation: a review
topic Mini-Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4215334/
https://www.ncbi.nlm.nih.gov/pubmed/25371860
http://dx.doi.org/10.1089/biores.2014.0024
work_keys_str_mv AT rivadeneirapablos mathematicalmodelingofhivdynamicsafterantiretroviraltherapyinitiationareview
AT moogclaudeh mathematicalmodelingofhivdynamicsafterantiretroviraltherapyinitiationareview
AT stanguybart mathematicalmodelingofhivdynamicsafterantiretroviraltherapyinitiationareview
AT brunetcecile mathematicalmodelingofhivdynamicsafterantiretroviraltherapyinitiationareview
AT raffifrancois mathematicalmodelingofhivdynamicsafterantiretroviraltherapyinitiationareview
AT ferrevirginie mathematicalmodelingofhivdynamicsafterantiretroviraltherapyinitiationareview
AT costanzavicente mathematicalmodelingofhivdynamicsafterantiretroviraltherapyinitiationareview
AT mhawejmariej mathematicalmodelingofhivdynamicsafterantiretroviraltherapyinitiationareview
AT biaforefederico mathematicalmodelingofhivdynamicsafterantiretroviraltherapyinitiationareview
AT ouattaradjomangana mathematicalmodelingofhivdynamicsafterantiretroviraltherapyinitiationareview
AT ernstdamien mathematicalmodelingofhivdynamicsafterantiretroviraltherapyinitiationareview
AT fonteneauraphael mathematicalmodelingofhivdynamicsafterantiretroviraltherapyinitiationareview
AT xiaxiaohua mathematicalmodelingofhivdynamicsafterantiretroviraltherapyinitiationareview