Evaluation of various static in vitro-in vivo extrapolation models for risk assessment of the CYP3A inhibition potential of an investigational drug

Clinical Pharmacology and Therapeutics

Volumn 95, Issue 2, 2014, Pages 189-198

  Vieira, Md L T ^a   Kirby, B ^b   Ragueneau Majlessi, I ^b   Galetin, A ^c   Chien, J Y L ^d   Einolf, H J ^e   Fahmi, O A ^f   Fischer, V ^g   Fretland, A ^d   Grime, K ^h   Hall, S D ^d   Higgs, R ^d   Plowchalk, D ^f   Riley, R ⁱ   Seibert, E ^j   Skordos, K ^k   Snoeys, J ^l   Venkatakrishnan, K ^m   Waterhouse, T ^d   Obach, R S ^f   Berglund, E G ⁿ   Zhang, L ^a   Zhao, P ^a   Reynolds, K S ^a   Huang, S M ^a   more..

^a CENTER FOR DRUG EVALUATION AND RESEARCH   (United States)

^b UNIVERSITY OF WASHINGTON   (United States)

^c UNIVERSITY OF MANCHESTER   (United Kingdom)

^d ELI LILLY AND COMPANY   (United States)

^e NOVARTIS PHARMA AG   (Switzerland)

^f PFIZER INC   (United States)

^g ABBVIE INC   (United States)

^h ASTRAZENECA R AND D   (Sweden)

ⁱ ASTRAZENECA   (United Kingdom)

^j BOEHRINGER INGELHEIM PHARMACEUTICALS INC   (United States)

^k GLAXOSMITHKLINE   (United States)

^l JANSSEN RESEARCH FOUNDATION   (Belgium)

^m MILLENNIUM PHARMACEUTICALS INC   (United States)

ⁿ MEDICAL PRODUCTS AGENCY   (Sweden)

more..

Author keywords

[No Author keywords available]

Indexed keywords

CYTOCHROME P-450 CYP3A; DRUG INTERACTIONS; DRUGS, INVESTIGATIONAL; HUMANS; MIDAZOLAM; MODELS, BIOLOGICAL; RISK ASSESSMENT;

EID: 84893740148     PISSN: 00099236     EISSN: 15326535     Source Type: Journal    
DOI: 10.1038/clpt.2013.187     Document Type: Article

References (33)

1. Zhang, L., Reynolds, K.S., Zhao, P.& Huang, S.M. Drug interactions evaluation: An integrated part of risk assessment of therapeutics. Toxicol Appl Pharmacol. 243, 134-145 (2010).
2. Huang, S.M., Temple, R., Throckmorton, D.C. & Lesko, L.J. Drug interaction studies: Study design, data analysis, and implications for dosing and labeling. Clin. Pharmacol. Ther. 81, 298-304 (2007).
3. Galetin, A., Ito, K., Hallifax, D. & Houston, J.B. CYP3A4 substrate selection and substitution in the prediction of potential drug-drug interactions. J. Pharmacol. Exp. Ther. 314, 180-190 (2005).
4. Galetin, A., Burt, H., Gibbons, L. & Houston, J.B. Prediction of time-dependent CYP3A4 drug-drug interactions: Impact of enzyme degradation, parallel elimination pathways, and intestinal inhibition. Drug Metab. Dispos. 34, 166-175 (2006).
5. Grimm, S.W. et al. The conduct of in vitro studies to address timedependent inhibition of drug-metabolizing enzymes: A perspective of the pharmaceutical research and manufacturers of America. Drug Metab. Dispos. 37, 1355-1370 (2009).
6. Obach, R.S., Walsky, R.L. & Venkatakrishnan, K. Mechanism-based inactivation of human cytochrome p450 enzymes and the prediction of drug-drug interactions. Drug Metab. Dispos. 35, 246-255 (2007).
7. US Food and Drug Administration. Draft guidance for industry: Drug interaction studies -study design, data analysis, and implications for dosing and labeling (2012).
8. Ito, K., Iwatsubo, T., Kanamitsu, S., Ueda, K., Suzuki, H. & Sugiyama, Y. Prediction of pharmacokinetic alterations caused by drug-drug interactions: Metabolic interaction in the liver. Pharmacol. Rev. 50, 387-412 (1998).
9. Ito, K., Hallifax, D., Obach, R.S. & Houston, J.B. Impact of parallel pathways of drug elimination and multiple cytochrome P450 involvement on drug-drug interactions: CYP2D6 paradigm. Drug Metab. Dispos. 33, 837-844 (2005).
10. Ito, K., Brown, H.S. & Houston, J.B. Database analyses for the prediction of in vivo drug-drug interactions from in vitro data. Br. J. Clin. Pharmacol. 57, 473-486 (2004).
11. Houston, J.B. & Galetin, A. Progress towards prediction of human pharmacokinetic parameters from in vitro technologies. Drug Metab. Rev. 35, 393-415 (2003).
12. Fahmi, O.A., Maurer, T.S., Kish, M., Cardenas, E., Boldt, S. & Nettleton, D. A combined model for predicting CYP3A4 clinical net drug-drug interaction based on CYP3A4 inhibition, inactivation, and induction determined in vitro. Drug Metab. Dispos. 36, 1698-1708 (2008).
13. Fahmi, O.A. et al. Comparison of different algorithms for predicting clinical drug-drug interactions, based on the use of CYP3A4 in vitro data: Predictions of compounds as precipitants of interaction. Drug Metab. Dispos. 37, 1658-1666 (2009).
14. Brown, H.S., Ito, K., Galetin, A. & Houston, J.B. Prediction of in vivo drug-drug interactions from in vitro data: Impact of incorporating parallel pathways of drug elimination and inhibitor absorption rate constant. Br. J. Clin. Pharmacol. 60, 508-518 (2005).
15. Obach, R.S., Walsky, R.L., Venkatakrishnan, K., Gaman, E.A., Houston, J.B. & Tremaine, L.M. The utility of in vitro cytochrome P450 inhibition data in the prediction of drug-drug interactions. J. Pharmacol. Exp. Ther. 316, 336-348 (2006).
16. Einolf, H.J. Comparison of different approaches to predict metabolic drugdrug interactions. Xenobiotica. 37, 1257-1294 (2007).
17. European Medicines Agency. Guideline on the investigation of drug interactions (2012).
18. Paine, M.F., Hart, H.L., Ludington, S.S., Haining, R.L., Rettie, A.E. & Zeldin, D.C. The human intestinal cytochrome P450 "pie". Drug Metab. Dispos. 34, 880-886 (2006).
19. Obach, R.S. Predicting drug-drug interactions from in vitro drug metabolism data: Challenges and recent advances. Curr. Opin. Drug Discov. Devel. 12, 81-89 (2009).
20. Tucker, G.T., Houston, J.B. & Huang, S.M. Optimizing drug development: Strategies to assess drug metabolism/transporter interaction potentialtoward a consensus. Clin. Pharmacol. Ther. 70, 103-114 (2001).
21. Obach, R.S., Walsky, R.L., Venkatakrishnan, K., Houston, J.B. & Tremaine, L.M. In vitro cytochrome P450 inhibition data and the prediction of drug-drug interactions: Qualitative relationships, quantitative predictions, and the rank-order approach. Clin. Pharmacol. Ther. 78, 582-592 (2005).
22. Rostami-Hodjegan, A. & Tucker, G.T. 'In silico' simulations to assess the 'in vivo' consequences of 'in vitro' metabolic drug-drug interactions. Drug Discov. Today: Technol. 1, 441-448 (2004).
23. Wang, Y.H., Jones, D.R. & Hall, S.D. Prediction of cytochrome P450 3A inhibition by verapamil enantiomers and their metabolites. Drug Metab. Dispos. 32, 259-266 (2004).
24. Venkatakrishnan, K. & Obach, R.S. Drug-drug interactions via mechanismbased cytochrome P450 inactivation: Points to consider for risk assessment from in vitro data and clinical pharmacologic evaluation. Curr. Drug Metab. 8, 449-462 (2007).
25. Mayhew, B.S., Jones, D.R. & Hall, S.D. An in vitro model for predicting in vivo inhibition of cytochrome P450 3A4 by metabolic intermediate complex formation. Drug Metab. Dispos. 28, 1031-1037 (2000).
26. Kenny, J.R. et al. Drug-drug interaction potential of marketed oncology drugs: In vitro assessment of time-dependent cytochrome P450 inhibition, reactive metabolite formation and drug-drug interaction prediction. Pharm. Res. 29, 1960-1976 (2012).
27. Guest, E.J., Rowland-Yeo, K., Rostami-Hodjegan, A., Tucker, G.T., Houston, J.B. & Galetin, A. Assessment of algorithms for predicting drug-drug interactions via inhibition mechanisms: Comparison of dynamic and static models. Br. J. Clin. Pharmacol. 71, 72-87 (2011).
28. McGinnity, D.F., Waters, N.J., Tucker, J. & Riley, R.J. Integrated in vitro analysis for the in vivo prediction of cytochrome P450-mediated drug-drug interactions. Drug Metab. Dispos. 36, 1126-1134 (2008).
29. Grime, K.H., Bird, J., Ferguson, D. & Riley, R.J. Mechanism-based inhibition of cytochrome P450 enzymes: An evaluation of early decision making in vitro approaches and drug-drug interaction prediction methods. Eur. J. Pharm. Sci. 36, 175-191 (2009).
30. Zhang, L., Zhang, Y.D., Strong, J.M., Reynolds, K.S. & Huang, S.M. A regulatory viewpoint on transporter-based drug interactions. Xenobiotica. 38, 709-724 (2008).
31. Einolf, H.J. et al. Evaluation of various static and dynamic modeling methods to predict clinical CYP3A induction using in vitro CYP3A4 mRNA induction data. Clin. Pharmacol. Ther. (2013) e-pub ahead of print 23 October 2013. (doi: 10.1038/clpt.2013.170).
32. Yang, J., Jamei, M., Yeo, K.R., Tucker, G.T. & Rostami-Hodjegan, A. Prediction of intestinal first-pass drug metabolism. Curr. Drug Metab. 8, 676-684 (2007).
33. Yang, J., Jamei, M., Yeo, K.R., Rostami-Hodjegan, A. & Tucker, G.T. Misuse of the well-stirred model of hepatic drug clearance. Drug Metab. Dispos. 35, 501-502 (2007).