A Quantitative Approach to the Prediction of Drug-Drug Interactions Mediated by Cytochrome P450 2C8 Inhibition

ABSTRACT

Background

Ohno and Colleagues proposed an approach for predicting drug–drug interactions (DDIs) mediated by cytochrome P450 (CYP) 3A4 based on the use of the ratio of the inhibited to non-inhibited area under the plasma concentration time curve (AUC) of substrates to estimate the fraction of the dose metabolized via CYP3A4 (contribution ratio, CR) and the in vivo inhibitory potency of a perpetrator (inhibition ratio, IR). This study evaluated the performance of this approach on DDIs mediated by CYP2C8 inhibitors.

Research design and methods

Initial estimates of CR and IR of CYP2C8 substrates and inhibitors were calculated for 33 DDI in vivo studies. The approach was externally validated with 17 additional studies. Bayesian orthogonal regression was used to refine the estimates of the parameters. Assessment of prediction success was conducted by plotting observed versus predicted AUC ratios.

Results

Final estimates of CRs and IRs were obtained for 19 CYP2C8 substrates and 23 inhibitors, respectively. The method demonstrated good predictive capacity, with only two values outside of the prespecified limits.

Conclusions

The approach may help to adapt dose regimens for CYP2C8 substrates when given in combination with CYP2C8 inhibitors and to map the potential DDIs of new molecular entities.

KEYWORDS:

• Prediction
• drug–drug interactions
• CYP2C8 inhibition
• static semi-physiological model

Declaration of interest

I Poggesi, at the time of this research, was an employee of Janssen, part of the Pharmaceutical Companies of Johnson and Johnson and holds stocks of Johnson and Johnson, and he is currently employee of Certara. L Quintieri is an employee of University of Padua. 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.

Author contribution statement

All authors contributed to the generation of the idea, collection of data, data analysis, manuscript preparation, and revision.

Supplementary material

Supplemental data for this article can be accessed here.