The design and analysis of parallel experiments to produce structurally identifiable models

S. Y Amy Cheung, James W T Yates, Leon Aarons

    Research output: Contribution to journalArticlepeer-review


    Pharmacokinetic analysis in humans using compartmental models is restricted with respect to the estimation of parameter values. This is because the experimenter usually is only able to apply inputs and observations in a very small number of compartments in the system. This has implications for the structural identifiability of such systems and consequently limits the complexity and mechanistic relevance of the models that may be applied to such experiments. A number of strategies are presented whereby models are rendered globally identifiable by considering a series of experiments in parallel. Examples are taken from the pharmacokinetic literature and analysed using this parallel experiment methodology. It is concluded that considering a series of pharmacokinetic experiments where some, but not all, of the parameters may be shared across the experiments can improve the identifiability of some compartmental models. © 2013 Springer Science+Business Media New York.
    Original languageEnglish
    Pages (from-to)93-100
    Number of pages7
    JournalJournal of pharmacokinetics and pharmacodynamics
    Issue number1
    Publication statusPublished - Feb 2013


    • Bioequivalence
    • Covariates
    • Parameter estimation
    • Parent-metabolite models
    • Pharmacokinetic models
    • Structural identifiability


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