Predicting drug-drug interactions: Application of physiologically based pharmacokinetic models under a systems biology approach

Karen Rowland Yeo, Masoud Jamei, Amin Rostami-Hodjegan

    Research output: Contribution to journalArticlepeer-review

    Abstract

    The development of in vitro-in vivo extrapolation (IVIVE), a 'bottom-up' approach, to predict pharmacokinetic parameters and drug-drug interactions (DDIs) has accelerated mainly due to an increase in the understanding of the multiple mechanisms involved in these interactions and the availability of appropriate in vitro systems that act as surrogates for delineating various elements of the interactions relevant to absorption, distribution, metabolism and elimination. Recent advances in the knowledge of the population variables required for IVIVE (demographic, anatomical, genetic and physiological parameters) have also contributed to the appreciation of the sources of variability and wider use of this approach for different scenarios within the pharmaceutical industry. Initially, the authors present an overview of the integration of IVIVE into 'static' and 'dynamic' models for the quantitative prediction of DDIs. The main purpose of this review is to discuss the application of IVIVE in conjunction with physiologically based pharmacokinetic modeling under a systems biology approach to characterize the potential DDIs in individual patients, including those who cannot be investigated in formal clinical trials for ethical reasons. In addition, we address the issues related to the prediction of complex DDIs involving the inhibition of cytochrome P- and transporter-mediated activities through multiple drugs. © 2013 Expert Reviews Ltd.
    Original languageEnglish
    Pages (from-to)143-157
    Number of pages14
    JournalExpert Review of Clinical Pharmacology
    Volume6
    Issue number2
    DOIs
    Publication statusPublished - Mar 2013

    Keywords

    • drug-drug interactions
    • modeling
    • pharmacokinetics
    • simulation
    • variability

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