Abstract
Background
Cytochrome P450 (CYP) 3A4 is the most prevalent metabolising enzyme in the human liver and is also a target for various drug interactions of significant clinical concern. Even though there are numerous reports regarding drug interactions involving CYP3A4, it is far from easy to estimate all potential interactions, since too many drugs are metabolised by CYP3A4. For this reason, a comprehensive framework for the prediction of CYP3A4-mediated drug interactions would be of considerable clinical importance.
Objective
The objective of this study was to provide a robust and practical method for the prediction of drug interactions mediated by CYP3A4 using minimal in vivo information from drug-interaction studies, which are often carried out early in the course of drug development.
Data sources
The analysis was based on 113 drug-interaction studies reported in 78 published articles over the period 1983–2006. The articles were used if they contained sufficient information about drug interactions. Information on drug names, doses and the magnitude of the increase in the area under the concentration-time curve (AUC) were collected.
Methods
The ratio of the contribution of CYP3A4 to oral clearance (CRCYP3A4) was calculated for 14 substrates (midazolam, alprazolam, buspirone, cerivastatin, atorvastatin, ciclosporin, felodipine, lovastatin, nifedipine, nisoldipine, simvastatin, triazolam, zolpidem and telithromycin) based on AUC increases observed in interaction studies with itraconazole or ketoconazole. Similarly, the time-averaged apparent inhibition ratio of CYP3A4 (IRCYP3A4) was calculated for 18 inhibitors (ketoconazole, voriconazole, itraconazole, telithromycin, clarithromycin, saquinavir, nefazodone, erythromycin, diltiazem, fluconazole, verapamil, cimetidine, ranitidine, roxithromycin, fluvoxamine, azithromycin, gatifloxacin and fluoxetine) primarily based on AUC increases observed in drug-interaction studies with midazolam. The increases in the AUC of a substrate associated with coadministration of an inhibitor were estimated using the equation 1/(1 - CRCYP3A4 · IRCYP3A4), based on pharmacokinetic considerations.
Results
The proposed method enabled predictions of the AUC increase by interactions with any combination of these substrates and inhibitors (total 251 matches). In order to validate the reliability of the method, the AUC increases in 60 additional studies were analysed. The method successfully predicted AUC increases within 67–150% of the observed increase for 50 studies (83%) and within 50–200% for 57 studies (95%). Midazolam is the most reliable standard substrate for evaluation of the in vivo inhibition of CYP3A4. The present analysis suggests that simvastatin, lovastatin and buspirone can be used as alternatives. To evaluate the in vivo contribution of CYP3A4, ketoconazole or itraconazole is the selective inhibitor of choice.
Conclusion
This method is applicable to (i) prioritise clinical trials for investigating drug interactions during the course of drug development and (ii) predict the clinical significance of unknown drug interactions. If a drug-interaction study is carefully designed using appropriate standard drugs, significant interactions involving CYP3A4 will not be missed. In addition, the extent of CYP3A4-mediated interactions between many other drugs can be predicted using the current method.
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Acknowledgements
Dr Akihiro Hisaka now works in Pharmacology and Pharmacokinetics at the University of Tokyo Hospital Faculty of Medicine, University of Tokyo, Tokyo, Japan.
This study was supported by Health and Labor Sciences Research Grants for Research on Regulatory Science of Pharmaceuticals and Medical Devices from the Ministry of Health, Labor and Welfare, Japan. The authors have no conflicts of interest that are directly relevant to the content of this study.
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Ohno, Y., Hisaka, A. & Suzuki, H. General Framework for the Quantitative Prediction of CYP3A4-Mediated Oral Drug Interactions Based on the AUC Increase by Coadministration of Standard Drugs. Clin Pharmacokinet 46, 681–696 (2007). https://doi.org/10.2165/00003088-200746080-00005
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DOI: https://doi.org/10.2165/00003088-200746080-00005