The importance of modeling interoccasion variability in population pharmacokinetic analyses
- 1.9k Downloads
Individual pharmacokinetic parameters may change randomly between study occasions. Analysis of simulated data with NONMEM shows that ignoring such interoccasion variability (IOV) may result in biased population parameter estimates. Particular parameters affected and the extent to which they are biased depend on study design and the magnitude of IOV and interindividual variability. Neglecting IOV also results in a high incidence of statistically significant spurious period effects. Perhaps most important, ignoring IOV can lead to a falsely optimistic impression of the potential value of therapeutic drug monitoring. A model incorporating IOV was developed and its performance in the presence and absence of IOV was evaluated. The IOV model performs well with respect to both model selection and population parameter estimation in all circumstances studied. Analysis of two real data examples using this model reveals significant IOV in all parameters for both drugs and supports the simulation findings for the case that IOV is ignored: predictable biases occur in parameter estimates and previously nonexistent period effects are found.
Key wordsinteroccasion variability interindividual variability intraindividual variability pharmacokinetics population analysis NONMEM
Unable to display preview. Download preview PDF.
- 1.M. Rowland. Intra-individual variability in pharmacokinetics. In: D. D. Breimer (ed.),Towards Better Safety of Drugs and Pharmaceutical Products, Elsevier, North-Holland, 1980.Google Scholar
- 2.A. Grahnen. The impact of time-dependent phenomena on bioequivalence studies. In: D. D. Breimer and P. Speiser (eds.),Topics in Pharmaceutical Sciences, Elsevier, Amsterdam, 1985.Google Scholar
- 3.S. L. Beal and L. B. Sheiner.NONMEM Users Guides, NONMEM Project Group UCSF, San Francisco, CA, 1992.Google Scholar
- 6.A. Schumitzky. Nonparametric EM Algorithms for estimating prior distributions. Technical Report: 90-3, Laboratory of Applied Pharmacokinetics, USC School of Medicine, 1990.Google Scholar