HIV reservoirs and immune surveillance evasion cause the failure of structured treatment interruptions : a computational study

Continuous antiretroviral therapy is currently the most effective way to treat HIV infection. Unstructured interruptions are quite common due to side effects and toxicity, among others, and cannot be prevented. Several attempts to structure these interruptions failed due to an increased morbidity co...

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Main Authors: Mancini, Emiliano, Castiglione, Filippo, Bernaschi, Massimo, De Luca, Andrea, Sloot, Peter M. A.
Other Authors: School of Computer Engineering
Format: Article
Language:English
Published: 2013
Online Access:https://hdl.handle.net/10356/94952
http://hdl.handle.net/10220/9358
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-949522022-02-16T16:26:46Z HIV reservoirs and immune surveillance evasion cause the failure of structured treatment interruptions : a computational study Mancini, Emiliano Castiglione, Filippo Bernaschi, Massimo De Luca, Andrea Sloot, Peter M. A. School of Computer Engineering Continuous antiretroviral therapy is currently the most effective way to treat HIV infection. Unstructured interruptions are quite common due to side effects and toxicity, among others, and cannot be prevented. Several attempts to structure these interruptions failed due to an increased morbidity compared to continuous treatment. The cause of this failure is poorly understood and often attributed to drug resistance. Here we show that structured treatment interruptions would fail regardless of the emergence of drug resistance. Our computational model of the HIV infection dynamics in lymphoid tissue inside lymph nodes, demonstrates that HIV reservoirs and evasion from immune surveillance themselves are sufficient to cause the failure of structured interruptions. We validate our model with data from a clinical trial and show that it is possible to optimize the schedule of interruptions to perform as well as the continuous treatment in the absence of drug resistance. Our methodology enables studying the problem of treatment optimization without having impact on human beings. We anticipate that it is feasible to steer new clinical trials using computational models. Published version 2013-03-07T08:02:43Z 2019-12-06T19:05:15Z 2013-03-07T08:02:43Z 2019-12-06T19:05:15Z 2012 2012 Journal Article Mancini, E., Castiglione, F., Bernaschi, M., de Luca, A., & Sloot, P. M. A. (2012). HIV Reservoirs and Immune Surveillance Evasion Cause the Failure of Structured Treatment Interruptions: A Computational Study. PLoS ONE, 7(4). 1932-6203 https://hdl.handle.net/10356/94952 http://hdl.handle.net/10220/9358 10.1371/journal.pone.0036108 22558348 en PLoS One © 2012 The Authors. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
description Continuous antiretroviral therapy is currently the most effective way to treat HIV infection. Unstructured interruptions are quite common due to side effects and toxicity, among others, and cannot be prevented. Several attempts to structure these interruptions failed due to an increased morbidity compared to continuous treatment. The cause of this failure is poorly understood and often attributed to drug resistance. Here we show that structured treatment interruptions would fail regardless of the emergence of drug resistance. Our computational model of the HIV infection dynamics in lymphoid tissue inside lymph nodes, demonstrates that HIV reservoirs and evasion from immune surveillance themselves are sufficient to cause the failure of structured interruptions. We validate our model with data from a clinical trial and show that it is possible to optimize the schedule of interruptions to perform as well as the continuous treatment in the absence of drug resistance. Our methodology enables studying the problem of treatment optimization without having impact on human beings. We anticipate that it is feasible to steer new clinical trials using computational models.
author2 School of Computer Engineering
author_facet School of Computer Engineering
Mancini, Emiliano
Castiglione, Filippo
Bernaschi, Massimo
De Luca, Andrea
Sloot, Peter M. A.
format Article
author Mancini, Emiliano
Castiglione, Filippo
Bernaschi, Massimo
De Luca, Andrea
Sloot, Peter M. A.
spellingShingle Mancini, Emiliano
Castiglione, Filippo
Bernaschi, Massimo
De Luca, Andrea
Sloot, Peter M. A.
HIV reservoirs and immune surveillance evasion cause the failure of structured treatment interruptions : a computational study
author_sort Mancini, Emiliano
title HIV reservoirs and immune surveillance evasion cause the failure of structured treatment interruptions : a computational study
title_short HIV reservoirs and immune surveillance evasion cause the failure of structured treatment interruptions : a computational study
title_full HIV reservoirs and immune surveillance evasion cause the failure of structured treatment interruptions : a computational study
title_fullStr HIV reservoirs and immune surveillance evasion cause the failure of structured treatment interruptions : a computational study
title_full_unstemmed HIV reservoirs and immune surveillance evasion cause the failure of structured treatment interruptions : a computational study
title_sort hiv reservoirs and immune surveillance evasion cause the failure of structured treatment interruptions : a computational study
publishDate 2013
url https://hdl.handle.net/10356/94952
http://hdl.handle.net/10220/9358
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