Optimal sampling times in population pharmacokinetic studies

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

doi:10.1111/1467-9876.00239

Optimal sampling times in population pharmacokinetic studies

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

Research output: Contribution to journal › Article › peer-review

24 Scopus citations

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 language	English (US)
Pages (from-to)	345-359
Number of pages	15
Journal	Journal of the Royal Statistical Society. Series C: Applied Statistics
Volume	50
Issue number	3
DOIs	https://doi.org/10.1111/1467-9876.00239
State	Published - 2001
Externally published	Yes

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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10.1111/1467-9876.00239

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KW - Limited sampling strategies

KW - Longitudinal data

KW - Markov chain Monte Carlo methods

KW - Optimal design

KW - Population model

KW - Random-effects regression

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Optimal sampling times in population pharmacokinetic studies

Abstract

Keywords

ASJC Scopus subject areas

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