Optimisation of sampling windows design for population pharmacokinetic experiments

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    Abstract

    This paper describes an approach for optimising sampling windows for population pharmacokinetic experiments. Sampling windows designs are more practical in late phase drug development where patients are enrolled in many centres and in out-patient clinic settings. Collection of samples under the uncontrolled environment at these centres at fixed times may be problematic and can result in uninformative data. Population pharmacokinetic sampling windows design provides an opportunity to control when samples are collected by allowing some flexibility and yet provide satisfactory parameter estimation. This approach uses information obtained from previous experiments about the model and parameter estimates to optimise sampling windows for population pharmacokinetic experiments within a space of admissible sampling windows sequences. The optimisation is based on a continuous design and in addition to sampling windows the structure of the population design in terms of the proportion of subjects in elementary designs, number of elementary designs in the population design and number of sampling windows per elementary design is also optimised. The results obtained showed that optimal sampling windows designs obtained using this approach are very efficient for estimating population PK parameters and provide greater flexibility in terms of when samples are collected. The results obtained also showed that the generalized equivalence theorem holds for this approach. © 2008 Springer Science+Business Media, LLC.
    Original languageEnglish
    Pages (from-to)465-482
    Number of pages17
    JournalJournal of pharmacokinetics and pharmacodynamics
    Volume35
    Issue number4
    DOIs
    Publication statusPublished - Aug 2008

    Keywords

    • D-optimality
    • Fisherinformation matrix
    • Nonlinear mixed effects
    • Optimal design
    • Pharmacokinetics
    • Sampling windows

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