title: Bayesian population pharmacokinetic and pharmacodynamic analyses using mixture models.
abstract: Population studies of the pharmacokinetics or pharmacodynamics of drugs help us, learn about the variability in drug disposition and effects, information that can be used to treat future patients at safe and effective doses. We present a new approach to population modeling based on a weighted mixture of normal distributions having random weights and means. This method allows estimation of underlying continuous population distributions without prespecifying the parametric form or shape of these probability distributions. Additionally, this method can carry out nonparametric regression of pharmacokinetic or dynamic parameters on patient covariates while estimating the underlying distributions. Two examples illustrate the method and its flexibility.
authors.affiliation: Department of Community and Family Medicine, Duke University Medical Center, Durham, North Carolina 27710, USA.
authors.forename: G L
authors.initials: GL
authors.lastname: Rosner
authors.forename: P
authors.initials: P
authors.lastname: Müller
mesh_terms: D001499:Bayes Theorem; D003198:Computer Simulation; D008432:Mathematical Computing; D008954:Models, Biological; D010599:Pharmacokinetics