Prospective evaluation of a D-optimal designed population pharmacokinetic study

Green, B and Duffull, SB (2003) Prospective evaluation of a D-optimal designed population pharmacokinetic study. Journal of Pharmacokinetics And Pharmacodynamics, 30 2: 145-161. doi:10.1023/A:1024467714170

Author Green, B
Duffull, SB
Title Prospective evaluation of a D-optimal designed population pharmacokinetic study
Journal name Journal of Pharmacokinetics And Pharmacodynamics   Check publisher's open access policy
ISSN 1567-567X
Publication date 2003-01-01
Sub-type Article (original research)
DOI 10.1023/A:1024467714170
Volume 30
Issue 2
Start page 145
End page 161
Total pages 17
Editor T. Ludden
M. Rowland
Place of publication USA
Publisher Plenum
Language eng
Subject C1
730199 Clinical health not specific to particular organs, diseases and conditions
320503 Clinical Pharmacology and Therapeutics
Abstract Recently, methods for computing D-optimal designs for population pharmacokinetic studies have become available. However there are few publications that have prospectively evaluated the benefits of D-optimality in population or single-subject settings. This study compared a population optimal design with an empirical design for estimating the base pharmacokinetic model for enoxaparin in a stratified randomized setting. The population pharmacokinetic D-optimal design for enoxaparin was estimated using the PFIM function (MATLAB version The optimal design was based on a one-compartment model with lognormal between subject variability and proportional residual variability and consisted of a single design with three sampling windows (0-30 min, 1.5-5 hr and 11 - 12 hr post-dose) for all patients. The empirical design consisted of three sample time windows per patient from a total of nine windows that collectively represented the entire dose interval. Each patient was assigned to have one blood sample taken from three different windows. Windows for blood sampling times were also provided for the optimal design. Ninety six patients were recruited into the study who were currently receiving enoxaparin therapy. Patients were randomly assigned to either the optimal or empirical sampling design, stratified for body mass index. The exact times of blood samples and doses were recorded. Analysis was undertaken using NONMEM (version 5). The empirical design supported a one compartment linear model with additive residual error, while the optimal design supported a two compartment linear model with additive residual error as did the model derived from the full data set. A posterior predictive check was performed where the models arising from the empirical and optimal designs were used to predict into the full data set. This revealed the optimal'' design derived model was superior to the empirical design model in terms of precision and was similar to the model developed from the full dataset. This study suggests optimal design techniques may be useful, even when the optimized design was based on a model that was misspecified in terms of the structural and statistical models and when the implementation of the optimal designed study deviated from the nominal design.
Keyword Pharmacology & Pharmacy
Population Analysis
D-optimal Design
Optimal Sampling Theory
Information Matrix
Q-Index Code C1

Document type: Journal Article
Sub-type: Article (original research)
Collections: Excellence in Research Australia (ERA) - Collection
2004 Higher Education Research Data Collection
School of Pharmacy Publications
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Citation counts: TR Web of Science Citation Count  Cited 42 times in Thomson Reuters Web of Science Article | Citations
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Created: Wed, 15 Aug 2007, 12:24:47 EST