Mittler1998_HIV1_interactingTargetCells

This a model from the article:
Influence of delayed viral production on viral dynamics in HIV-1 infected
patients.
Mittler JE, Sulzer B, Neumann AU, Perelson AS. Math Biosci
1998 Sep;152(2):143-63 9780612
,
Abstract:
We present and analyze a model for the interaction of human immunodeficiency
virus type 1 (HIV-1) with target cells that includes a time delay between
initial infection and the formation of productively infected cells. Assuming
that the variation among cells with respect to this 'intracellular' delay can be
approximated by a gamma distribution, a high flexible distribution that can
mimic a variety of biologically plausible delays, we provide analytical
solutions for the expected decline in plasma virus concentration after the
initiation of antiretroviral therapy with one or more protease inhibitors. We
then use the model to investigate whether the parameters that characterize viral
dynamics can be identified from biological data. Using non-linear least-squares
regression to fit the model to simulated data in which the delays conform to a
gamma distribution, we show that good estimates for free viral clearance rates,
infected cell death rates, and parameters characterizing the gamma distribution
can be obtained. For simulated data sets in which the delays were generated
using other biologically plausible distributions, reasonably good estimates for
viral clearance rates, infected cell death rates, and mean delay times can be
obtained using the gamma-delay model. For simulated data sets that include added
simulated noise, viral clearance rate estimates are not as reliable. If the mean
intracellular delay is known, however, we show that reasonable estimates for the
viral clearance rate can be obtained by taking the harmonic mean of viral
clearance rate estimates from a group of patients. These results demonstrate
that it is possible to incorporate distributed intracellular delays into
existing models for HIV dynamics and to use these refined models to estimate the
half-life of free virus from data on the decline in HIV-1 RNA following
treatment.
This model was taken from the CellML repository
and automatically converted to SBML.
The original model was:
Mittler JE, Sulzer B, Neumann AU, Perelson AS. (1998) - version=1.0
The original CellML model was created by:
Catherine Lloyd
c.lloyd@auckland.ac.nz
The University of Auckland
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Influence of delayed viral production on viral dynamics in HIV-1 infected patients.
- Mittler JE, Sulzer B, Neumann AU, Perelson AS
- Mathematical biosciences , 9/ 1998 , Volume 152 , pages: 143-163 , PubMed ID: 9780612
- Theoretical Biology and Biophysics Group, Los Alamos National Laboratory, MS-K710, NM 87545, USA. jmittler@t10.lanl.gov
- We present and analyze a model for the interaction of human immunodeficiency virus type 1 (HIV-1) with target cells that includes a time delay between initial infection and the formation of productively infected cells. Assuming that the variation among cells with respect to this 'intracellular' delay can be approximated by a gamma distribution, a high flexible distribution that can mimic a variety of biologically plausible delays, we provide analytical solutions for the expected decline in plasma virus concentration after the initiation of antiretroviral therapy with one or more protease inhibitors. We then use the model to investigate whether the parameters that characterize viral dynamics can be identified from biological data. Using non-linear least-squares regression to fit the model to simulated data in which the delays conform to a gamma distribution, we show that good estimates for free viral clearance rates, infected cell death rates, and parameters characterizing the gamma distribution can be obtained. For simulated data sets in which the delays were generated using other biologically plausible distributions, reasonably good estimates for viral clearance rates, infected cell death rates, and mean delay times can be obtained using the gamma-delay model. For simulated data sets that include added simulated noise, viral clearance rate estimates are not as reliable. If the mean intracellular delay is known, however, we show that reasonable estimates for the viral clearance rate can be obtained by taking the harmonic mean of viral clearance rate estimates from a group of patients. These results demonstrate that it is possible to incorporate distributed intracellular delays into existing models for HIV dynamics and to use these refined models to estimate the half-life of free virus from data on the decline in HIV-1 RNA following treatment.
Submitter of this revision: Camille Laibe
Modellers: Camille Laibe
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- Model originally submitted by : Camille Laibe
- Submitted: Jun 23, 2010 10:12:16 AM
- Last Modified: Jun 25, 2010 2:18:20 PM
Revisions
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Version: 2
- Submitted on: Jun 25, 2010 2:18:20 PM
- Submitted by: Camille Laibe
- With comment: Current version of Mittler1998_HIV1_interactingTargetCells
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Version: 1
- Submitted on: Jun 23, 2010 10:12:16 AM
- Submitted by: Camille Laibe
- With comment: Original import of Mittler1998_HIV1_interactingTargetCells
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