- Author:
- pmr2.import <nobody@models.cellml.org>
- Date:
- 2009-06-17 12:39:25+12:00
- Desc:
- committing version01 of bonhoeffer_rembiszewski_ortiz_nixon_2000
- Permanent Source URI:
- https://models.cellml.org/workspace/bonhoeffer_rembiszewski_ortiz_nixon_2000/rawfile/a48e6d79860d1355f1cb115df8a33ed8049f10db/bonhoeffer_rembiszewski_ortiz_nixon_2000_b.cellml
<?xml version='1.0' encoding='utf-8'?>
<!-- FILE : bonhoeffer_model_II_2000.xml
CREATED : 10th December 2003
LAST MODIFIED : 10th December 2003
AUTHOR : Catherine Lloyd
Bioengineering Institute
The University of Auckland
MODEL STATUS : This model conforms to the CellML 1.0 Specification released on
10th August 2001, and the 16/1/02 CellML Metadata 1.0 Specification.
DESCRIPTION : This file contains a CellML description of Bonhoeffer et al.'s 2nd 2000 mathematical model of virus dynamics.
CHANGES:
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<documentation xmlns="http://cellml.org/tmp-documentation">
<article>
<articleinfo>
<title>Modelling the Population Dynamics of Virus Infected Cells</title>
<author>
<firstname>Catherine</firstname>
<surname>Lloyd</surname>
<affiliation>
<shortaffil>Bioengineering Institute, University of Auckland</shortaffil>
</affiliation>
</author>
</articleinfo>
<section id="sec_status">
<title>Model Status</title>
<para>
This is the original unchecked version of the model imported from the previous
CellML model repository, 24-Jan-2006.
</para>
</section>
<sect1 id="sec_structure">
<title>Model Structure</title>
<para>
Despite advances in the development of antiretroviral inhibitors, HIV treatment is still not 100 percent successful. Although combination therapy leads to a sustained reduction in virus load in many patients, complete removal of the virus is often prevented due to the latent nature of the virus. This latent period also means that patients have to remain on the powerful, expensive drugs for long, indefinite periods, which is expensive and associated with side effects and the evolution of drug resistant viruses. In view of these problems, new treatment strategies are needed. One such strategy is structured therapy interruption (STI), in which patients are put on and taken off therapy over a defined period of time (see <xref linkend="fig_cell_diagram"/> below). The theory behind this is to boost the patients' HIV-1-specific immune responses with autologous virus in a process similar to vaccination. The enhanced immunity may then help to clear the virus during treatment, or maintain a low level of the virus once therapy is finished.
</para>
<para>
Although STI has potential benefits, there are also associated risks such as evolved drug resistance. The authors of this current study, Bonhoeffer <emphasis>et al.</emphasis>, believe that a mathematical framework could play a useful role in assessing the potential risks and benefits of STI. They develop three simple population dynamical models in order to assess the effect of structured therapy interruptions on:
<orderedlist inheritnum="ignore" continuation="restarts">
<listitem>
<para>the immune effector cells;</para>
</listitem>
<listitem>
<para>the latent cell compartment; and</para>
</listitem>
<listitem>
<para>the emergence of drug resistance.</para>
</listitem>
</orderedlist>
</para>
<para>
The models have been described here in CellML (the raw CellML description of the Bonhoeffer <emphasis>et al.</emphasis> 2000 models can be downloaded in various formats as described in <xref linkend="sec_download_this_model"/>).
</para>
<para>
The complete original paper reference is cited below:
</para>
<para>
<ulink url="http://www.aidsonline.com/pt/re/aids/abstract.00002030-200010200-00012.htm;jsessionid=A5gx129cZs2oUuGwRw2lGn2eBrbQBWrfsAXmnAUHRtKI1i42zG7T!-20242763!-949856032!9001!-1">Risks and benefits of structured antiretroviral drug therapy interruptions in HIV-1 infection</ulink>, Sebastian Bonhoeffer, Michal Rembiszewski, Gabriel M. Ortiz, and Douglas F. Nixon, 2000, <ulink url="http://www.aidsonline.com/pt/re/aids/home.htm;jsessionid=A5gx129cZs2oUuGwRw2lGn2eBrbQBWrfsAXmnAUHRtKI1i42zG7T!-20242763!-949856032!9001!-1">
<emphasis>AIDS</emphasis>
</ulink>, 14, 2313-2322. (<ulink url="http://www.aidsonline.com/pt/re/aids/fulltext.00002030-200010200-00012.htm;jsessionid=A5gx129cZs2oUuGwRw2lGn2eBrbQBWrfsAXmnAUHRtKI1i42zG7T!-20242763!-949856032!9001!-1">A full text (html)</ulink> and <ulink url="http://www.aidsonline.com/pt/re/aids/pdfhandler.00002030-200010200-00012.pdf;jsessionid=A5gx129cZs2oUuGwRw2lGn2eBrbQBWrfsAXmnAUHRtKI1i42zG7T!-20242763!-949856032!9001!-1">PDF</ulink> versions of the article are available to subscribers on the <emphasis>AIDS</emphasis> website.) <ulink url="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=11089619&dopt=Abstract">PubMed ID: 11089619</ulink>
</para>
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<caption>The structured therapy interruption paradigm: if a patient's virus load declines much faster during highly active antiretroviral therapy than the decline in HIV-specific cytotoxic T lymphocyte (CTL) frequency, will there be a point at which the CTL outnumber the infected cells to an extent that the CTL can suppress the virus load when the therapy is stopped?</caption>
</informalfigure>
<para>
From model simulations the authors concluded that STI only leads to transient or sustained virus control if the immune effector cells increase during drug therapy. This increase must more than compensate for the increase in susceptible target cells induced during therapy. The risk of drug resistance evolving, or repopulating the pool of latent cells during drug free periods may be small if the virus population remains at levels below the baseline. However, if the virus load increases during the drug-free period to levels similar to or greater than the baseline before therapy, both these risks increase significantly.
</para>
</sect1>
</article>
</documentation>
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The University of Auckland, Bioengineering Institute
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Bonhoeffer et al.'s 2nd 2000 mathematical model of virus dynamics.
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