Predicting drug–drug interactions: application of physiologically based pharmacokinetic models under a systems biology approach

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.

Keywords::

• drug–drug interactions
• modeling
• pharmacokinetics
• simulation
• variability

Acknowledgements

The authors thank James Kay for his assistance with the preparation of this manuscript.

Financial & competing interests disclosure

KR Yeo and M Jamei are employed by, and A Rostami-Hodjegan is currently seconded to on a part-time basis, Simcyp (a Certara company), which provides a commercial physiologically based pharmacokinetic in vitro–in vivo extrapolation simulator for the pharmaceutical industry. The simulator is freely available, after the completion of the relevant workshops, to centers of excellence in pharmacology and pharmacometrics within the academic and other not-for-profit institutions for research and teaching purposes. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

No writing assistance was utilized in the production of this manuscript.