A Bayesian approach for population pharmacokinetic modelling of sirolimus

Dansirikul, Chantaratsamon, Morris, Raymond G., Tett, Susan E. and Duffull, Stephen B. (2006) A Bayesian approach for population pharmacokinetic modelling of sirolimus. British Journal of Clinical Pharmacology, 62 4: 420-434.


Author Dansirikul, Chantaratsamon
Morris, Raymond G.
Tett, Susan E.
Duffull, Stephen B.
Title A Bayesian approach for population pharmacokinetic modelling of sirolimus
Journal name British Journal of Clinical Pharmacology  (ERA 2012 Listed)    (ERA 2010 Rank A)   Check publisher's open access policy
Publication date 2006
Sub-type Article
DOI 10.1111/j.1365-2125.2005.02533.x
Volume number 62
Issue number 4
ISSN 0306-5251
Start page 420
End page 434
Total pages 15
Editor E. J. Begg
J. M. Ritter
M. S. Lennard
Place of publication Oxford
Publisher Blackwell Publishing
Collection year 2006
Language eng
Subject C1
320503 Clinical Pharmacology and Therapeutics
730199 Clinical health not specific to particular organs, diseases and conditions
Formatted abstract Aims

To explore a Bayesian approach for the pharmacokinetic analysis of sirolimus concentration data arising from therapeutic drug monitoring (poorly informative concentration-time point design), and to explore possible covariate relationships for sirolimus pharmacokinetics.

Methods

Sirolimus concentration-time data were available as part of routine clinical care from 25 kidney transplant recipients. Most samples were taken at or near the trough time point at steady state. The data were analyzed using a fully conditional Bayesian approach with PKBUGS (v 1.1)/WinBUGS (v 1.3). Features of the data included noncompliance and missing concentration measurements below the limit of sensitivity of the assay. Informative priors were used.

Results

A two-compartment model with proportional residual error provided the best fit to the data (consisting of 315 sirolimus concentration-time points). The typical value for the apparent clearance (CL/F ) was 12.5 l h−1 at the median age of 44 years. Apparent CL was found to be inversely related to age with a posterior probability of a clinically significant effect of 0.734.

Conclusions

A population pharmacokinetic model was developed for sirolimus using a novel approach. Bayesian modelling with informative priors allowed interpretation of a significant covariate relationship, even using poorly informative data.
Keyword Bayesian Population Modelling
Population Pharmacokinetic Analysis
Prior Elicitation
Sirolimus
Winbugs
Pharmacology & Pharmacy
Transplant Recipients
Prior Distributions
Rapamycin
Tacrolimus
Volunteers
Prediction
Parameters
Outcomes
Therapy
Safety
Q-Index Code C1

 
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Created: Wed, 15 Aug 2007, 09:40:12 EST