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MODEL8102792069 - Nelson2000_HIV-1_intracellular_delay


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Reference Publication
Publication ID: 10701304
Nelson PW, Murray JD, Perelson AS.
A model of HIV-1 pathogenesis that includes an intracellular delay.
Math Biosci 2000 Feb; 163(2): 201-215
Department of Mathematics, Duke University, Durham, NC 27708, USA.  [more]
Original Model: MODEL8102792069.origin
Submitter: Lukas Endler
Submission Date: 20 Jul 2009 17:13:17 UTC
Last Modification Date: 23 Sep 2009 16:49:46 UTC
Creation Date: 15 Jul 2009 12:56:50 UTC
bqmodel:isDerivedFrom PubMed 9780612
PubMed 8599114
bqbiol:isVersionOf Gene Ontology response to drug
Human Disease Ontology Human immunodeficiency virus infectious disease
bqbiol:hasTaxon Taxonomy Homo sapiens

described in: A model of HIV-1 pathogenesis that includes an intracellular delay.
Nelson PW, Murray JD, Perelson AS; Math Biosci. 2000 Feb;163(2):201-15. PMID: 10701304 ; doi: 10.1016/S0025-5564(99)00055-3
Mathematical modeling combined with experimental measurements have yielded important insights into HIV-1 pathogenesis. For example, data from experiments in which HIV-infected patients are given potent antiretroviral drugs that perturb the infection process have been used to estimate kinetic parameters underlying HIV infection. Many of the models used to analyze data have assumed drug treatments to be completely efficacious and that upon infection a cell instantly begins producing virus. We consider a model that allows for less then perfect drug effects and which includes a delay in the initiation of virus production. We present detailed analysis of this delay differential equation model and compare the results to a model without delay. Our analysis shows that when drug efficacy is less than 100%, as may be the case in vivo, the predicted rate of decline in plasma virus concentration depends on three factors: the death rate of virus producing cells, the efficacy of therapy, and the length of the delay. Thus, previous estimates of infected cell loss rates can be improved upon by considering more realistic models of viral infection.
Author Keywords: HIV; Delay; Viral life cycle; T-cells

As the initial conditions for the intergrations where not known, approximate inital conditions for the steady state at k=3.47*10 -8 where chosen ( T * =1675 ). The model does not reprodue the results given in the article quantitatively, but the time courses are quite similar. For running the model, the initial conditions for t < 0 should be the same as the steady state ones.

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