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Activity Number:
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400
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Type:
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Invited
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Date/Time:
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Wednesday, August 5, 2009 : 8:30 AM to 10:20 AM
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Sponsor:
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ENAR
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| Abstract - #302865 |
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Title:
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Parameters Estimation and Model Selection of Long-Term Dynamic Models of HIV
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Author(s):
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Marc Lavielle*+ and Adeline Samson and Ana Karina Fermin and France Mentré
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Companies:
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INRIA Saclay and Université Paris-Descartes and Université Nanterre and INERM-Université Paris-Diderot
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Address:
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Université Paris-Sud, Bât 425, Orsay, 91400, France
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Keywords:
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HIV dynamics ; SAEM ; MONOLIX ; nonlinear mixed effects models ; Maximum Likelihood Estimation ; Model Selection
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Abstract:
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HIV dynamics studies, based on differential equations, have significantly improved the knowledge of HIV infection. We aim to simultaneously analyze the HIV viral load decrease and the CD4 increase based on a long-term HIV dynamic system. We consider three mechanistic models and compare them with respect to their ability to represent HIV-infected patients under reverse transcriptase and protease inhibitor therapy. We propose to use the SAEM algorithm, a powerful maximum likelihood estimation method for nonlinear mixed effects models. We use this methodology to analyze data from the clinical trial Cophar 2-ANRS 111. We show that a latently model provides good fits and that the model chosen can be used to quantify the different activities of the three protease inhibitors on HIV dynamics. All the numerical experiments were performed with the MONOLIX software (http://software.monolix.org).
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