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Published on: June 21, 2018
Quantitative prediction of CYP3A induction-mediated drug-drug interactions in clinical practice
Haruka Tsutsui1, Motohiro Kato2, Shino Kuramoto3
1Chugai Pharmaceutical Co., Ltd., 216 Totsukacho, Totsuka-ku, Yokohama-shi, Kanagawa, 244-8602, Japan; Department of Molecular Toxicology, School of Pharmaceutical Sciences, University of Shizuoka, Shizuoka, Japan.
Abstract:
There have been no reports on the quantitative prediction of CYP3A induction-mediated decreases in AUC and Cmax for drug candidates identified as a "victims" of CYP3A induction. Our previous study separately evaluated the fold-induction of hepatic and intestinal CYP3A by known inducers using clinical induction data and revealed that we were able to quantitatively predict the AUC ratio (AUCR) of a few CYP3A substrates in the presence and absence of CYP3A inducers. In the present study, we investigate the predictability of AUCR and also Cmax ratio (CmaxR) in additional 54 clinical studies. The fraction metabolized by CYP3A (fm), the intestinal bioavailability (Fg), and the hepatic intrinsic clearance (CLint) of substrates were determined by the in vitro experiments as well as clinical data used for calculating AUCR and CmaxR. The result showed that 65-69% and 65-67% of predictions were within 2-fold of observed AUCR and CmaxR, respectively. A simulation using multiple parameter combinations suggested that the variability of fm and Fg within a certain range might have a minimal impact on the calculation output. These findings suggest that clinical AUCR and CmaxR of CYP3A substrates can be quantitatively predicted from the preclinical stage.
Insights
This study demonstrates quantitative prediction of drug exposure changes due to CYP3A induction. Findings suggest clinical drug-drug interaction ratios can be predicted early in development.
Area of Science:
- Pharmacokinetics
- Drug Metabolism and Transportation
- Drug Discovery and Development
Background:
- Quantitative prediction of drug exposure changes due to CYP3A induction is lacking.
- Previous work showed ability to predict AUC ratio (AUCR) for some CYP3A substrates.
Purpose of the Study:
- Investigate predictability of AUCR and Cmax ratio (CmaxR) for CYP3A substrates.
- Evaluate prediction accuracy in 54 additional clinical studies.
Main Methods:
- Determined fraction metabolized by CYP3A (fm), intestinal bioavailability (Fg), and hepatic intrinsic clearance (CLint) using in vitro and clinical data.
- Calculated observed AUCR and CmaxR from clinical studies.
- Assessed prediction accuracy against observed values.
Main Results:
- 65-69% of predicted AUCR and 65-67% of predicted CmaxR were within 2-fold of observed values.
- Variability in fm and Fg showed minimal impact on prediction output.
- Successful quantitative prediction of clinical drug-drug interaction ratios was achieved.
Conclusions:
- Clinical AUCR and CmaxR of CYP3A substrates can be quantitatively predicted from preclinical data.
- This predictive capability aids in early-stage drug development and risk assessment.
- Enables better understanding of CYP3A induction-mediated drug-drug interactions.
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