The Yin–Yang of CYP3A4: a Bayesian meta-analysis to quantify inhibition and induction of CYP3A4 metabolism in humans and refine uncertainty factors for mixture risk assessment
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Quantifying differences in pharmacokinetics (PK) and toxicokinetics (TK) provides a science-based approach to refine uncertainty factors (UFs) for chemical risk assessment. Cytochrome P450 (CYP) 3A4—the major hepatic and intestinal human CYP—and the P-glycoprotein (Pgp) transporter share a vast range of common substrates for which PK may be modulated through inhibition or induction in the presence of grapefruit juice (GFJ) or St. John’s wort (SJW), respectively. Here, an extensive literature search was performed on PK interactions for CYP3A4 and Pgp substrates after oral co-exposure to GFJ and SJW. Relevant data from 109 publications, extracted for both markers of acute (Cmax) and chronic [clearance and area under the plasma concentration–time curve (AUC)] exposure, were computed into a Bayesian hierarchical meta-analysis model. Bioavailability (F) and substrate fraction metabolised by CYP3A4 (Fm) were identified as the variables exhibiting the highest impact on the magnitude of interaction. The Bayesian meta-regression model developed provided good predictions for magnitudes of inhibition (maximum 5.3-fold with GFJ) and induction (maximum 2.3-fold with SJW). Integration of CYP3A4 variability, F, Fm and magnitude of interaction provided the basis to derive a range of CYP3A4 and Pgp-related UFs. Such CYP3A4 and Pgp-related UFs can be derived in the absence of human data using in vitro TK evidence for CYP3A4/Pgp inhibition or induction as conservative in silico options. The future development of quantitative in vitro–in vivo extrapolation models for mixture risk assessment is discussed with particular attention to integrating human in vitro and in vivo P/TK data on interactions with pathway-related variability.
KeywordsCYP3A4 Interindividual variability Kinetic interactions Mixtures Risk assessment Uncertainty factors
This work has been financed by the European Food Safety Authority (EFSA) under contract CFT/EFSA/EMRISK/2012/01 and Analytica LASER. The authors would like to thank Katarzyna Miernik, Iwona Kuter, Mateusz Nikodem, Agnieszka Zyla, Camille Béchaux, Sonia Halhol, Laure Perreau and Céline Dubuquoy from Analytica LASER for data collection and analysis.
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Conflict of interest
The authors declare that they have no conflict of interest.
- Ainslie GR, Wolf KK, Li Y et al (2014) Assessment of a candidate marker constituent predictive of a dietary substance-drug interaction: case study with grapefruit juice and CYP3A4 drug substrates. J Pharmacol Exp Ther 351(3):576–584. https://doi.org/10.1124/jpet.114.216838 CrossRefPubMedPubMedCentralGoogle Scholar
- Bhat VS, Meek MEB, Valcke M, English C, Boobis A, Brown R (2017) Evolution of chemical-specific adjustment factors (CSAF) based on recent international experience; increasing utility and facilitating regulatory acceptance. Crit Rev Toxicol 47(9):729–749. https://doi.org/10.1080/10408444.2017.1303818 CrossRefPubMedGoogle Scholar
- EMA (2012) European Medicines Agency. Guideline on the investigation of drug interactions. Committee for Human Medicinal Products, LondonGoogle Scholar
- FDA (2009) Food and Drug Administration. Guidance for industry: evidence-based review system for the scientific evaluation of health claims—finalGoogle Scholar
- FDA (2012) Food and Drug Administration. Guidance for industry: drug interactions studies: study design, data analysis, implications for dosing, and labeling recommendations. US Department of Health and Human Services, FDA, Silver SpringGoogle Scholar
- Hoffmeyer S, Burk O, von Richter O et al (2000) Functional polymorphisms of the human multidrug-resistance gene: multiple sequence variations and correlation of one allele with P-glycoprotein expression and activity in vivo. Proc Natl Acad Sci USA 97(7):3473–3478. https://doi.org/10.1073/pnas.050585397 CrossRefPubMedGoogle Scholar
- Takahashi M, Onozawa S, Ogawa R, Uesawa Y, Echizen H (2015) Predictive performance of three practical approaches for grapefruit juice-induced 2-fold or greater increases in AUC of concomitantly administered drugs. J Clin Pharm Ther 40(1):91–97. https://doi.org/10.1111/jcpt.12231 CrossRefPubMedGoogle Scholar
- Wang XD, Li JL, Su QB et al (2009) Impact of the haplotypes of the human pregnane X receptor gene on the basal and St John’s wort-induced activity of cytochrome P450 3A4 enzyme. Br J Clin Pharmacol 67(2):255–261. https://doi.org/10.1111/j.1365-2125.2008.03344.x CrossRefPubMedPubMedCentralGoogle Scholar