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

Autores
Rivadeneira Paz, Pablo Santiago; Moog, Claude H.; Stan, Guy Bart; Brunet, Cecile; Raffi, Francois; Ferre, Virginie; Costanza, Vicente; Mhawej, Marie; Biafore, Federico Leonardo; Ouattara, Djomangan; Ernst, Damien; Fonteneau, Raphael; Xia, Xiaohua
Año de publicación
2014
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
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
Fil: Rivadeneira Paz, Pablo Santiago. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico Para la Industria Química (i); Argentina
Fil: Moog, Claude H.. Centre National de la Recherche Scientifique; Francia
Fil: Stan, Guy Bart. Imperial College London; Reino Unido
Fil: Brunet, Cecile. Universite de Nantes; Francia
Fil: Raffi, Francois. Universite de Nantes; Francia
Fil: Ferre, Virginie. Universite de Nantes; Francia
Fil: Costanza, Vicente. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico Para la Industria Química (i); Argentina
Fil: Mhawej, Marie. Universite de Nantes; Francia
Fil: Biafore, Federico Leonardo. Universidad Nacional de San Martin. Escuela de Ciencia y Tecnologia. Centro de Matematica Aplicada; Argentina
Fil: Ouattara, Djomangan. Centre National de la Recherche Scientifique; Francia
Fil: Ernst, Damien. Montefiore Institute; Bélgica
Fil: Fonteneau, Raphael. Montefiore Institute; Bélgica
Fil: Xia, Xiaohua. University of Pretoria; Sudáfrica
Materia
HIV
side-effects
optimal control
apoptosis
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/9260
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/9260
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Mathematical Modeling of HIV Dynamics After Antiretroviral Therapy Initiation: A ReviewRivadeneira Paz, Pablo SantiagoMoog, Claude H.Stan, Guy BartBrunet, CecileRaffi, FrancoisFerre, VirginieCostanza, VicenteMhawej, MarieBiafore, Federico LeonardoOuattara, DjomanganErnst, DamienFonteneau, RaphaelXia, XiaohuaHIVside-effectsoptimal controlapoptosishttps://purl.org/becyt/ford/2.2https://purl.org/becyt/ford/2This 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 patientsFil: Rivadeneira Paz, Pablo Santiago. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico Para la Industria Química (i); ArgentinaFil: Moog, Claude H.. Centre National de la Recherche Scientifique; FranciaFil: Stan, Guy Bart. Imperial College London; Reino UnidoFil: Brunet, Cecile. Universite de Nantes; FranciaFil: Raffi, Francois. Universite de Nantes; FranciaFil: Ferre, Virginie. Universite de Nantes; FranciaFil: Costanza, Vicente. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico Para la Industria Química (i); ArgentinaFil: Mhawej, Marie. Universite de Nantes; FranciaFil: Biafore, Federico Leonardo. Universidad Nacional de San Martin. Escuela de Ciencia y Tecnologia. Centro de Matematica Aplicada; ArgentinaFil: Ouattara, Djomangan. Centre National de la Recherche Scientifique; FranciaFil: Ernst, Damien. Montefiore Institute; BélgicaFil: Fonteneau, Raphael. Montefiore Institute; BélgicaFil: Xia, Xiaohua. University of Pretoria; SudáfricaMary Ann Liebert Inc2014-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/9260Rivadeneira Paz, Pablo Santiago; Moog, Claude H.; Stan, Guy Bart; Brunet, Cecile; Raffi, Francois; et al.; Mathematical Modeling of HIV Dynamics After Antiretroviral Therapy Initiation: A Review; Mary Ann Liebert Inc; BioResearch Open Access; 3; 5; 10-2014; 1-92164-7860enginfo:eu-repo/semantics/altIdentifier/url/http://online.liebertpub.com/doi/abs/10.1089/biores.2014.0024info:eu-repo/semantics/altIdentifier/doi/10.1089/biores.2014.0024info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:40:41Zoai:ri.conicet.gov.ar:11336/9260instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 09:40:41.443CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Mathematical Modeling of HIV Dynamics After Antiretroviral Therapy Initiation: A Review
title Mathematical Modeling of HIV Dynamics After Antiretroviral Therapy Initiation: A Review
spellingShingle Mathematical Modeling of HIV Dynamics After Antiretroviral Therapy Initiation: A Review
Rivadeneira Paz, Pablo Santiago
HIV
side-effects
optimal control
apoptosis
title_short 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_sort Mathematical Modeling of HIV Dynamics After Antiretroviral Therapy Initiation: A Review
dc.creator.none.fl_str_mv Rivadeneira Paz, Pablo Santiago
Moog, Claude H.
Stan, Guy Bart
Brunet, Cecile
Raffi, Francois
Ferre, Virginie
Costanza, Vicente
Mhawej, Marie
Biafore, Federico Leonardo
Ouattara, Djomangan
Ernst, Damien
Fonteneau, Raphael
Xia, Xiaohua
author Rivadeneira Paz, Pablo Santiago
author_facet Rivadeneira Paz, Pablo Santiago
Moog, Claude H.
Stan, Guy Bart
Brunet, Cecile
Raffi, Francois
Ferre, Virginie
Costanza, Vicente
Mhawej, Marie
Biafore, Federico Leonardo
Ouattara, Djomangan
Ernst, Damien
Fonteneau, Raphael
Xia, Xiaohua
author_role author
author2 Moog, Claude H.
Stan, Guy Bart
Brunet, Cecile
Raffi, Francois
Ferre, Virginie
Costanza, Vicente
Mhawej, Marie
Biafore, Federico Leonardo
Ouattara, Djomangan
Ernst, Damien
Fonteneau, Raphael
Xia, Xiaohua
author2_role author
author
author
author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv HIV
side-effects
optimal control
apoptosis
topic HIV
side-effects
optimal control
apoptosis
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.2
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv 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
Fil: Rivadeneira Paz, Pablo Santiago. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico Para la Industria Química (i); Argentina
Fil: Moog, Claude H.. Centre National de la Recherche Scientifique; Francia
Fil: Stan, Guy Bart. Imperial College London; Reino Unido
Fil: Brunet, Cecile. Universite de Nantes; Francia
Fil: Raffi, Francois. Universite de Nantes; Francia
Fil: Ferre, Virginie. Universite de Nantes; Francia
Fil: Costanza, Vicente. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico Para la Industria Química (i); Argentina
Fil: Mhawej, Marie. Universite de Nantes; Francia
Fil: Biafore, Federico Leonardo. Universidad Nacional de San Martin. Escuela de Ciencia y Tecnologia. Centro de Matematica Aplicada; Argentina
Fil: Ouattara, Djomangan. Centre National de la Recherche Scientifique; Francia
Fil: Ernst, Damien. Montefiore Institute; Bélgica
Fil: Fonteneau, Raphael. Montefiore Institute; Bélgica
Fil: Xia, Xiaohua. University of Pretoria; Sudáfrica
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
publishDate 2014
dc.date.none.fl_str_mv 2014-10
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/9260
Rivadeneira Paz, Pablo Santiago; Moog, Claude H.; Stan, Guy Bart; Brunet, Cecile; Raffi, Francois; et al.; Mathematical Modeling of HIV Dynamics After Antiretroviral Therapy Initiation: A Review; Mary Ann Liebert Inc; BioResearch Open Access; 3; 5; 10-2014; 1-9
2164-7860
url http://hdl.handle.net/11336/9260
identifier_str_mv Rivadeneira Paz, Pablo Santiago; Moog, Claude H.; Stan, Guy Bart; Brunet, Cecile; Raffi, Francois; et al.; Mathematical Modeling of HIV Dynamics After Antiretroviral Therapy Initiation: A Review; Mary Ann Liebert Inc; BioResearch Open Access; 3; 5; 10-2014; 1-9
2164-7860
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://online.liebertpub.com/doi/abs/10.1089/biores.2014.0024
info:eu-repo/semantics/altIdentifier/doi/10.1089/biores.2014.0024
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Mary Ann Liebert Inc
publisher.none.fl_str_mv Mary Ann Liebert Inc
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.070432

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