Bayesian population pharmacokinetic and pharmacodynamic analyses using mixture models

Gary L. Rosner, Peter Müller

Research output: Contribution to journalReview article

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.

Original languageEnglish (US)
Pages (from-to)209-233
Number of pages25
JournalJournal of Pharmacokinetics and Biopharmaceutics
Volume25
Issue number2
DOIs
StatePublished - Jan 1 1997
Externally publishedYes

Keywords

  • Bayesian analysis
  • Dirichlet process
  • Kernel density estimation
  • Mixture models
  • Nonparametric regression

ASJC Scopus subject areas

  • Pharmacology, Toxicology and Pharmaceutics(all)
  • Pharmacology (medical)

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