Sample-size calculations for multi-group comparison in population pharmacokinetic experiments

    Research output: Contribution to journalArticlepeer-review

    Abstract

    This paper describes an approach for calculating sample size for population pharmacokinetic experiments that involve hypothesis testing based on multi-group comparison detecting the difference in parameters between groups under mixed-effects modelling. This approach extends what has been described for generalized linear models and nonlinear population pharmacokinetic models that involve only binary covariates to more complex nonlinear population pharmacokinetic models. The structural nonlinear model is linearized around the random effects to obtain the marginal model and the hypothesis testing involving model parameters is based on Wald's test. This approach provides an efficient and fast method for calculating sample size for hypothesis testing in population pharmacokinetic models. The approach can also handle different design problems such as unequal allocation of subjects to groups and unbalanced sampling times between and within groups. The results obtained following application to a one compartment intravenous bolus dose model that involved three different hypotheses under different scenarios showed good agreement between the power obtained from NONMEM simulations and nominal power. Copyright © 2009 John Wiley & Sons, Ltd.
    Original languageEnglish
    Pages (from-to)255-268
    Number of pages13
    JournalPharmaceutical Statistics
    Volume9
    Issue number4
    DOIs
    Publication statusPublished - Oct 2010

    Keywords

    • mixed-effects modelling
    • multi-group comparison
    • population pharmacokinetics
    • power
    • sample size

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