Optimal sampling times in population pharmacokinetic studies

Jonathan R. Stroud, Peter Müller, Gary L. Rosner

Research output: Contribution to journalArticle

Abstract

We propose a simulation-based approach to decision theoretic Bayesian optimal design. The underlying probability model is a population pharmacokinetic model which allows for correlated responses (drug concentrations) and patient-to-patient heterogeneity. We consider the problem of choosing sampling times for the anticancer agent paclitaxel, using criteria related to the total area under the curve, the time above a critical threshold and the sampling cost.

Original languageEnglish (US)
Pages (from-to)345-359
Number of pages15
JournalJournal of the Royal Statistical Society. Series C: Applied Statistics
Volume50
Issue number3
DOIs
StatePublished - Jan 1 2001
Externally publishedYes

Keywords

  • Clinical trial
  • Limited sampling strategies
  • Longitudinal data
  • Markov chain Monte Carlo methods
  • Optimal design
  • Population model
  • Random-effects regression

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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