title: Estimation of population pharmacokinetic parameters of saquinavir in HIV patients with the MONOLIX software.
abstract: In nonlinear mixed-effects models, estimation methods based on a linearization of the likelihood are widely used although they have several methodological drawbacks. Kuhn and Lavielle (Comput. Statist. Data Anal. 49:1020-1038 (2005)) developed an estimation method which combines the SAEM (Stochastic Approximation EM) algorithm, with a MCMC (Markov Chain Monte Carlo) procedure for maximum likelihood estimation in nonlinear mixed-effects models without linearization. This method is implemented in the Matlab software MONOLIX which is available at http://www.math.u-psud.fr/~lavielle/monolix/logiciels. In this paper we apply MONOLIX to the analysis of the pharmacokinetics of saquinavir, a protease inhibitor, from concentrations measured after single dose administration in 100 HIV patients, some with advance disease. We also illustrate how to use MONOLIX to build the covariate model using the Bayesian Information Criterion. Saquinavir oral clearance (CL/F) was estimated to be 1.26 L/h and to increase with body mass index, the inter-patient variability for CL/F being 120%. Several methodological developments are ongoing to extend SAEM which is a very promising estimation method for population pharmacockinetic/pharmacodynamic analyses.
authors.affiliation: Department of Mathematics, University Paris 5; University Paris 11, Orsay, France. Marc.Lavielle@math.u-psud.fr
authors.forename: Marc
authors.initials: M
authors.lastname: Lavielle
authors.forename: France
authors.initials: F
authors.lastname: Mentré
mesh_terms: D000284:Administration, Oral; D000465:Algorithms; D001499:Bayes Theorem; D015658:HIV Infections / Q000097:blood / Q000188:drug therapy / Q000378:metabolism* / Q000821:virology; D017320:HIV Protease Inhibitors / Q000008:administration & dosage / Q000097:blood / Q000493:pharmacokinetics*; D015497:HIV-1; D006801:Humans; D016013:Likelihood Functions; D008390:Markov Chains; D008954:Models, Biological; D009010:Monte Carlo Method; D017711:Nonlinear Dynamics; D011159:Population Surveillance; D011446:Prospective Studies; D015203:Reproducibility of Results; D019258:Saquinavir / Q000008:administration & dosage / Q000097:blood / Q000493:pharmacokinetics*; D012720:Severity of Illness Index; D012984:Software; D013269:Stochastic Processes
chemical_list: D017320:HIV Protease Inhibitors; D019258:Saquinavir