A Physiologically-Based Pharmacokinetic (PBPK) Model Network for the Prediction of CYP1A2 and CYP2C19 Drug–Drug–Gene Interactions with Fluvoxamine, Omeprazole, S-mephenytoin, Moclobemide, Tizanidine, Mexiletine, Ethinylestradiol, and Caffeine
Abstract
:1. Introduction
2. Methods
2.1. Data Sources and Software
2.2. Model Development and Evaluation
2.3. Sensitivity Analyses
3. Results
3.1. Fluvoxamine
3.2. Omeprazole
3.3. S-mephenytoin
3.4. Moclobemide
3.5. Tizanidine
3.6. Mexiletine
3.7. Ethinylestradiol
4. Discussion
4.1. Strong CYP1A2 and CYP2C19 Inhibition
4.2. Moderate to Weak CYP2C19 Inhibition
4.3. Moderate CYP1A2 Inhibition
4.4. Impact of Genetic Polymorphism
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
- Goldstein, J.A. Clinical Relevance of Genetic Polymorphisms in The Human Cyp2c Subfamily. Br. J. Clin. Pharmacol. 2001, 52, 349–355. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Desta, Z.; Zhao, X.; Shin, J.G.; Flockhart, D.A. Clinical Significance of The Cytochrome P450 2c19 Genetic Polymorphism. Clin. Pharmacokinet. 2002, 41, 913–958. [Google Scholar] [CrossRef] [PubMed]
- Zhou, S.F.; Yang, L.P.; Zhou, Z.W.; Liu, Y.H.; Chan, E. Insights into The Substrate Specificity, Inhibitors, Regulation, And Polymorphisms and the Clinical Impact of Human Cytochrome P450 1a2. AAPS J. 2009, 11, 481–494. [Google Scholar] [CrossRef] [Green Version]
- Bertilsson, L. Geographical/Interracial Differences in Polymorphic Drug Oxidation. Current State of Knowledge of Cytochromes P450 (Cyp) 2d6 and 2c19. Clin. Pharmacokinet. 1995, 29, 192–209. [Google Scholar] [CrossRef]
- Zhao, P.; Zhang, L.; Grillo, J.A.; Liu, Q.; Bullock, J.M.; Moon, Y.J.; Song, P.; Brar, S.S.; Madabushi, R.; Wu, T.C.; et al. Applications of Physiologically Based Pharmacokinetic (Pbpk) Modeling and Simulation During Regulatory Review. Clin. Pharmacol. Ther. 2011, 89, 259–267. [Google Scholar] [CrossRef]
- Shebley, M.; Sandhu, P.; Emami Riedmaier, A.; Jamei, M.; Narayanan, R.; Patel, A.; Peters, S.A.; Reddy, V.P.; Zheng, M.; de Zwart, L.; et al. Physiologically Based Pharmacokinetic Model Qualification and Reporting Procedures for Regulatory Submissions: A Consortium Perspective. Clin. Pharmacol. Ther. 2018, 104, 88–110. [Google Scholar] [CrossRef]
- Zhao, P.; Rowland, M.; Huang, S.M. Best Practice in The Use of Physiologically Based Pharmacokinetic Modeling and Simulation to Address Clinical Pharmacology Regulatory Questions. Clin. Pharmacol. Ther. 2012, 92, 17–20. [Google Scholar] [CrossRef]
- European Medicines Agency. Guideline on the Investigation of Drug Interactions 2012; European Medicines Agency: Amsterdam, The Netherlands, 2012. [Google Scholar]
- U.S. Food and Drug Administration. Clinical Drug Interaction Studies—Study Design, Data Analysis, And Clinical Implications. Guidance for Industry. Draft Guidance; US FDA: Silver Spring, MD, USA, 2017.
- U.S. Food and Drug Administration. Drug Development and Drug Interactions: Table of Substrates, Inhibitors and Inducers; US FDA: Silver Spring, MD, USA, 2017.
- Wu, F.; Gaohua, L.; Zhao, P.; Jamei, M.; Huang, S.M.; Bashaw, E.D.; Lee, S.C. Predicting Nonlinear Pharmacokinetics of Omeprazole Enantiomers and Racemic Drug Using Physiologically Based Pharmacokinetic Modeling and Simulation: Application to Predict Drug/Genetic Interactions. Pharm. Res. 2014, 31, 1919–1929. [Google Scholar] [CrossRef]
- Hassan-Alin, M.; Andersson, T.; Bredberg, E.; Rohss, K. Pharmacokinetics of Esomeprazole After Oral and Intravenous Administration of Single and Repeated Doses to Healthy Subjects. Eur. J. Clin. Pharmacol. 2000, 56, 665–670. [Google Scholar] [CrossRef]
- Olivares-Morales, A.; Ghosh, A.; Aarons, L.; Rostami-Hodjegan, A. Development of A Novel Simplified Pbpk Absorption Model to Explain the Higher Relative Bioavailability of The Oros(R) Formulation of Oxybutynin. AAPS J. 2016, 18, 1532–1549. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Adedoyin, A.; Arns, P.A.; Richards, W.O.; Wilkinson, G.R.; Branch, R.A. Selective Effect of Liver Disease on the Activities of Specific Metabolizing Enzymes: Investigation of Cytochromes P450 2c19 and 2d6. Clin. Pharmacol. Ther. 1998, 64, 8–17. [Google Scholar] [CrossRef]
- Gram, L.F.; Guentert, T.W.; Grange, S.; Vistisen, K.; Brosen, K. Moclobemide, A Substrate of Cyp2c19 And an Inhibitor of Cyp2c19, Cyp2d6, And Cyp1a2: A Panel Study. Clin. Pharmacol. Ther. 1995, 57, 670–677. [Google Scholar] [CrossRef]
- Mayersohn, M.; Guentert, T.W. Clinical Pharmacokinetics of the Monoamine Oxidase-A Inhibitor Moclobemide. Clin. Pharmacokinet. 1995, 29, 292–332. [Google Scholar] [CrossRef] [PubMed]
- Hoskins, J.; Shenfield, G.; Murray, M.; Gross, A. Characterization of Moclobemide N-Oxidation in Human Liver Microsomes. Xenobiotica 2001, 31, 387–397. [Google Scholar] [CrossRef]
- Britz, H.; Hanke, N.; Volz, A.K.; Spigset, O.; Schwab, M.; Eissing, T.; Wendl, T.; Frechen, S.; Lehr, T. Physiologically-Based Pharmacokinetic Models for Cyp1a2 Drug-Drug Interaction Prediction: A Modeling Network of Fluvoxamine, Theophylline, Caffeine, Rifampicin, And Midazolam. CPT Pharmacomet. Syst. Pharmacol. 2019, 8, 296–307. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Iga, K. Dynamic and Static Simulations of Fluvoxamine-Perpetrated Drug-Drug Interactions Using Multiple Cytochrome P450 Inhibition Modeling, And Determination of Perpetrator-Specific Cyp Isoform Inhibition Constants and Fractional Cyp Isoform Contributions to Victim Clearance. J. Pharm. Sci. 2016, 105, 1307–1317. [Google Scholar]
- Nielsen, K.K.; Flinois, J.P.; Beaune, P.; Brosen, K. The Biotransformation of Clomipramine In Vitro, Identification of the Cytochrome P450s Responsible for the Separate Metabolic Pathways. J. Pharmacol. Exp. Ther. 1996, 277, 1659–1664. [Google Scholar]
- Liu, K.H.; Kim, M.J.; Shon, J.H.; Moon, Y.S.; Seol, S.Y.; Kang, W.; Cha, I.J.; Shin, J.G. Stereoselective Inhibition of Cytochrome P450 Forms by Lansoprazole and Omeprazole In Vitro. Xenobiotica 2005, 35, 27–38. [Google Scholar] [CrossRef]
- Wei, X.; Dai, R.; Zhai, S.; Thummel, K.E.; Friedman, F.K.; Vestal, R.E. Inhibition of Human Liver Cytochrome P-450 1a2 By the Class Ib Antiarrhythmics Mexiletine, Lidocaine, And Tocainide. J. Pharmacol. Exp. Ther. 1999, 289, 853–858. [Google Scholar]
- Culm-Merdek, K.E.; Von Moltke, L.L.; Harmatz, J.S.; Greenblatt, D.J. Fluvoxamine Impairs Single-Dose Caffeine Clearance Without Altering Caffeine Pharmacodynamics. Br. J. Clin. Pharmacol. 2005, 60, 486–493. [Google Scholar] [CrossRef] [Green Version]
- Yao, C.; Kunze, K.L.; Trager, W.F.; Kharasch, E.D.; Levy, R.H. Comparison of in Vitro And in Vivo Inhibition Potencies of Fluvoxamine Toward Cyp2c19. Drug Metab. Dispos. 2003, 31, 565–571. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Yao, C.; Kunze, K.L.; Kharasch, E.D.; Wang, Y.; Trager, W.F.; Ragueneau, I.; Levy, R.H. Fluvoxamine-Theophylline Interaction: Gap Between In Vitro And In Vivo Inhibition Constants Toward Cytochrome P4501a2. Clin. Pharmacol. Ther. 2001, 70, 415–424. [Google Scholar] [CrossRef]
- Lukacova, V.; Parrot, N.; Howard, M.; Woltosz, W.; Bolger, M. Prediction of Omeprazole’s Disposition and Drug-Drug Interactions Using A Physiologically-Based Pharmacokinetic Model; Admet Europe: London, UK, 2010. [Google Scholar]
- Reddy, V.P.; Jones, B.C.; Colclough, N.; Srivastava, A.; Wilson, J.; Li, D. An Investigation into The Prediction of The Plasma Concentration-Time Profile and Its Interindividual Variability for A Range of Flavin-Containing Monooxygenase Substrates Using A Physiologically Based Pharmacokinetic Modeling Approach. Drug Metab. Dispos. 2018, 46, 1259–1267. [Google Scholar] [CrossRef] [PubMed]
- Wijnen, P.A.; Op den Buijsch, R.A.; Drent, M.; Kuijpers, P.M.; Neef, C.; Bast, A.; Bekers, O.; Koek, G.H. Review Article: The Prevalence and Clinical Relevance of Cytochrome P450 Polymorphisms. Aliment. Pharmacol. Ther. 2007, 26 (Suppl. 2), 211–219. [Google Scholar] [CrossRef] [PubMed]
Strong CYP2C19 inhibition |
|
Strong CYP1A2 inhibition |
|
Moderate CYP2C19 inhibition |
|
Moderate CYP1A2 inhibition |
|
|
Inhibitor Category | Inhibitor | Substrate | Pred AUCR/ Obs AUCR | Pred CmaxR/ Obs CmaxR |
---|---|---|---|---|
Strong CYP2C19 | Fluvoxamine | Omeprazole | EM: 1.13 * PM: 0.83 | EM: 1.00 * PM: 0.89 |
S-mephenytoin | 27.5mg Fl: 1.00 64.1mg Fl: 1.03 | 27.5mg Fl: 1.21 64.1 mg Fl: 1.33 | ||
Strong CYP1A2 | Fluvoxamine | Caffeine | 1.40 | 1.01 |
Tizanidine | 1.18 a | 1.36 a | ||
Mexiletine | 1.12 | 1.00 | ||
Moderate CYP2C19 | Omeprazole | Moclobemide | 1.07 | 0.89 |
Moclobemide | Omeprazole | EM: 0.79 PM: 0.86 | EM: 0.77 PM: 1.02 | |
Moderate CYP1A2 | Mexiletine | Caffeine | 0.61 | 0.53 |
Tizanidine | 0.63 | 0.63 | ||
Ethinylestradiol | Caffeine | 1.75 b | 0.94 b | |
Tizanidine | +CI: 0.26 +TDI: 0.96 c | +CI: 0.33 +TDI: 1.09 c |
Inhibitor Category | Inhibitor | Substrate | Ki |
---|---|---|---|
Strong CYP2C19 | Fluvoxamine | Omeprazole | 3.6 nM [19] |
S-mephenytoin | 2.6 nM [19] | ||
Strong CYP1A2 | Fluvoxamine | Caffeine | 2.97 nM [19] |
Tizanidine | 0.8697 nM a | ||
Mexiletine | 2.97 nM [19] | ||
Moderate CYP2C19 | Moclobemide | Omeprazole | 203.83 µM [20] (TDI 94.85 µM) |
Omeprazole | Moclobemide | S-ome: 3.1 µM [11,21] (TDI 0.3 µM) R-ome: 5.3 µM [11,21] (TDI 1.6 µM) | |
Moderate CYP1A2 | Mexiletine | Caffeine | 0.28 µM [22] |
Tizanidine | 0.28 µM [22] | ||
Ethinylestradiol | Caffeine | 0.48 µM b | |
Tizanidine | 0.48 µM b |
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Kanacher, T.; Lindauer, A.; Mezzalana, E.; Michon, I.; Veau, C.; Mantilla, J.D.G.; Nock, V.; Fleury, A. A Physiologically-Based Pharmacokinetic (PBPK) Model Network for the Prediction of CYP1A2 and CYP2C19 Drug–Drug–Gene Interactions with Fluvoxamine, Omeprazole, S-mephenytoin, Moclobemide, Tizanidine, Mexiletine, Ethinylestradiol, and Caffeine. Pharmaceutics 2020, 12, 1191. https://0-doi-org.brum.beds.ac.uk/10.3390/pharmaceutics12121191
Kanacher T, Lindauer A, Mezzalana E, Michon I, Veau C, Mantilla JDG, Nock V, Fleury A. A Physiologically-Based Pharmacokinetic (PBPK) Model Network for the Prediction of CYP1A2 and CYP2C19 Drug–Drug–Gene Interactions with Fluvoxamine, Omeprazole, S-mephenytoin, Moclobemide, Tizanidine, Mexiletine, Ethinylestradiol, and Caffeine. Pharmaceutics. 2020; 12(12):1191. https://0-doi-org.brum.beds.ac.uk/10.3390/pharmaceutics12121191
Chicago/Turabian StyleKanacher, Tobias, Andreas Lindauer, Enrica Mezzalana, Ingrid Michon, Celine Veau, Jose David Gómez Mantilla, Valerie Nock, and Angèle Fleury. 2020. "A Physiologically-Based Pharmacokinetic (PBPK) Model Network for the Prediction of CYP1A2 and CYP2C19 Drug–Drug–Gene Interactions with Fluvoxamine, Omeprazole, S-mephenytoin, Moclobemide, Tizanidine, Mexiletine, Ethinylestradiol, and Caffeine" Pharmaceutics 12, no. 12: 1191. https://0-doi-org.brum.beds.ac.uk/10.3390/pharmaceutics12121191