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Journal of Pharmacokinetics and Biopharmaceutics

, Volume 21, Issue 6, pp 735–750 | Cite as

The importance of modeling interoccasion variability in population pharmacokinetic analyses

  • M. O. Karlsson
  • L. B. Sheiner
Pharmacometrics

Abstract

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 words

interoccasion variability interindividual variability intraindividual variability pharmacokinetics population analysis NONMEM 

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Copyright information

© Plenum Publishing Corporation 1993

Authors and Affiliations

  • M. O. Karlsson
    • 1
    • 3
  • L. B. Sheiner
    • 1
    • 2
  1. 1.Department of Pharmacy, School of PharmacyUniversity of CaliforniaSan Francisco
  2. 2.Department of Laboratory Medicine, School of MedicineUniversity of CaliforniaSan Francisco
  3. 3.Division of Pharmacokinetics, Faculty of PharmacyUppsala UniversityUppsalaSweden

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