Abstract
Purpose
The objective is to confirm if the prediction of the drug–drug interaction using a physiologically based pharmacokinetic (PBPK) model is more accurate. In vivo K i values were estimated using PBPK model to confirm whether in vitro K i values are suitable.
Method
The plasma concentration–time profiles for the substrate with coadministration of an inhibitor were collected from the literature and were fitted to the PBPK model to estimate the in vivo K i values. The AUC ratios predicted by the PBPK model using in vivo K i values were compared with those by the conventional method assuming constant inhibitor concentration.
Results
The in vivo K i values of 11 inhibitors were estimated. When the in vivo K i values became relatively lower, the in vitro K i values were overestimated. This discrepancy between in vitro and in vivo K i values became larger with an increase in lipophilicity. The prediction from the PBPK model involving the time profile of the inhibitor concentration was more accurate than the prediction by the conventional methods.
Conclusion
A discrepancy between the in vivo and in vitro K i values was observed. The prediction using in vivo K i values and the PBPK model was more accurate than the conventional methods.
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Abbreviations
- AUC:
-
area under the curve
- CYP:
-
cytochrome P450
- F :
-
bioavailability
- F a :
-
fraction absorbed
- F g :
-
intestinal availability
- F h :
-
hepatic availability
- I p,max,u :
-
maximum unbound concentration in the circulating blood
- I u,max :
-
maximum unbound concentration at the inlet to the liver
- K i :
-
inhibition constant
- PBPK:
-
physiologically based pharmacokinetic
- Q h :
-
hepatic blood flow rate
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Acknowledgments
The authors would like to thank the following companies for data collection, analysis and simulations: Ajonomoto Co., Inc., Astellas Pharma Inc., Chugai Pharmaceutical Co., Ltd., Daiichi Pharmaceutical Co., Ltd., Dainippon Pharmaceutical Co., Ltd., Esai Co., Ltd., Kaken Pharmaceutical Co., Ltd., Kowa Company, Ltd., Kyorin Pharmaceutical Co., Ltd., Kyowa Hakko Kogyo Co. Ltd., Meiji Seika Kaisya, Ltd., Mochida Pharmaceutical Co., Ltd., Nippon Boehringer Ingelheim Co., Ltd., Nippon Shinyaku Co., Ltd., Nissan Chemical industries, Ltd., Ono Pharmaceutical Co., Ltd., Organon Japan, Otsuka Pharmaceutical Co., Ltd., Otsuka Pharmaceutical Factory, Inc., Pfizer Japan Inc., Sankyo Co., Ltd., Sanwa Kagaku Kenkyusho Co., Ltd., Taiho Pharmaceutical Co., Ltd., Taisho Pharmaceutical Co., Ltd., Takeda Chemical industries, Ltd., Tanabe Seiyaku Co., Ltd., Toray Industries Inc. The authors would also like to thank Drs. S. Suzuki, T. Sato and H. Ameniya for valuable discussions. We appreciate the Pharsight Corporation for providing us a license for the academic use of the computer program, WinNonlin(R), as the Pharsight Academic License (PAL) program.
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Kato, M., Shitara, Y., Sato, H. et al. The Quantitative Prediction of CYP-mediated Drug Interaction by Physiologically Based Pharmacokinetic Modeling. Pharm Res 25, 1891–1901 (2008). https://doi.org/10.1007/s11095-008-9607-2
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DOI: https://doi.org/10.1007/s11095-008-9607-2