Literature DB >> 21899913

Computer simulation of structured treatment interruption for HIV infection.

Jorge Ferreira1, Esteban A Hernandez-Vargas, Richard H Middleton.   

Abstract

The use of highly active antiretroviral therapy (HAART) for suppression of measurable levels of virus in the body has greatly contributed to restoration and preservation of the immune system in HIV positive patients. However, short and long term problems associated with HAART have led to proposals for alternative treatment strategies for controlling HIV infection. In particular, structured treatment interruptions (STIs) that consist of therapy withdrawal and re-initiation according to specific criteria have been considered. The aim of these STIs was one or both of: (i) to stimulate the immune system to react to HIV, (ii) to allow re-emergence of wild-type virus and thereby reduce problems of drug resistance. However, a number of clinical trials of STIs have shown adverse outcomes for patients under discontinuous therapy, including serious health risks associated with treatment interruptions. In this paper we consider in some detail two of the larger clinical studies, namely, (a) strategies for management of anti-retroviral therapy (SMART); (b) Staccato study. For each of these studies we perform computer simulations of the treatment strategies. These simulations suggest several underlying reasons for the adverse outcomes during treatment interruption. In particular, HIV infection exhibits rapid dynamic load changes, and therefore measurement based treatment regimes need to be carefully designed to avoid large transients in healthy CD4+ T cell count. Furthermore, repeated treatment interruptions may accelerate the emergence of resistant mutant virus and may increase the infection of long term reservoirs such as macrophages which will accelerate progression to AIDS.
Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

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Year:  2011        PMID: 21899913     DOI: 10.1016/j.cmpb.2011.07.011

Source DB:  PubMed          Journal:  Comput Methods Programs Biomed        ISSN: 0169-2607            Impact factor:   5.428


  3 in total

1.  HIV model parameter estimates from interruption trial data including drug efficacy and reservoir dynamics.

Authors:  Rutao Luo; Michael J Piovoso; Javier Martinez-Picado; Ryan Zurakowski
Journal:  PLoS One       Date:  2012-07-16       Impact factor: 3.240

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

Authors:  Emiliano Mancini; Filippo Castiglione; Massimo Bernaschi; Andrea de Luca; Peter M A Sloot
Journal:  PLoS One       Date:  2012-04-27       Impact factor: 3.240

3.  Windows of opportunity for Ebola virus infection treatment and vaccination.

Authors:  Van Kinh Nguyen; Esteban A Hernandez-Vargas
Journal:  Sci Rep       Date:  2017-08-21       Impact factor: 4.379

  3 in total

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