title: HIV model parameter estimates from interruption trial data including drug efficacy and reservoir dynamics.
abstract: Mathematical models based on ordinary differential equations (ODE) have had significant impact on understanding HIV disease dynamics and optimizing patient treatment. A model that characterizes the essential disease dynamics can be used for prediction only if the model parameters are identifiable from clinical data. Most previous parameter identification studies for HIV have used sparsely sampled data from the decay phase following the introduction of therapy. In this paper, model parameters are identified from frequently sampled viral-load data taken from ten patients enrolled in the previously published AutoVac HAART interruption study, providing between 69 and 114 viral load measurements from 3-5 phases of viral decay and rebound for each patient. This dataset is considerably larger than those used in previously published parameter estimation studies. Furthermore, the measurements come from two separate experimental conditions, which allows for the direct estimation of drug efficacy and reservoir contribution rates, two parameters that cannot be identified from decay-phase data alone. A Markov-Chain Monte-Carlo method is used to estimate the model parameter values, with initial estimates obtained using nonlinear least-squares methods. The posterior distributions of the parameter estimates are reported and compared for all patients.
authors: Department of Electrical and Computer Engineering, University of Delaware, Newark, Deleware, United States of America.
authors: Rutao
authors: R
authors: Luo
authors: Michael J
authors: MJ
authors: Piovoso
authors: Javier
authors: J
authors: Martinez-Picado
authors: Ryan
authors: R
authors: Zurakowski
mesh_terms: D000328:Adult; D019380:Anti-HIV Agents / Q000494:pharmacology / Q000627:therapeutic use*; D023241:Antiretroviral Therapy, Highly Active; D001499:Bayes Theorem; D015496:CD4-Positive T-Lymphocytes / Q000187:drug effects; D015658:HIV Infections / Q000188:drug therapy* / Q000276:immunology; D015497:HIV-1 / Q000187:drug effects / Q000502:physiology; D006801:Humans; D016018:Least-Squares Analysis; D015233:Models, Statistical; D017711:Nonlinear Dynamics; D016032:Randomized Controlled Trials as Topic; D013997:Time Factors; D019562:Viral Load / Q000187:drug effects; D028761:Withholding Treatment
chemical_list: D019380:Anti-HIV Agents