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Interaction Between Domperidone and Ketoconazole: Toward Prediction of Consequent QTc Prolongation Using Purely In
1Simcyp Limited (a Certara Company), Blades Enterprise Centre, Sheffield, UK.
CPT: Pharmacometrics & Systems Pharmacology
|August 14, 2014
Summary
This study used pharmacokinetic (PK) and pharmacodynamic (PD) modeling to predict how domperidone (DOM) affects electrocardiograms when combined with ketoconazole (KETO), a CYP3A inhibitor.
Area of Science:
- Pharmacology
- Computational Biology
- Drug Metabolism
Background:
- Drug-drug interactions (DDIs) can alter drug efficacy and safety.
- Predicting electrocardiogram (ECG) changes, specifically QTcF interval, is crucial for cardiac safety assessment.
- Domperidone (DOM) and ketoconazole (KETO) are known to interact via CYP3A metabolism.
Purpose of the Study:
- To evaluate the predictive performance of combined mechanistic pharmacokinetic (PK) and pharmacodynamic (PD) modeling for domperidone (DOM)-induced QTcF interval changes.
- To assess the impact of ketoconazole (KETO), a CYP3A inhibitor, on DOM pharmacokinetics and pharmacodynamics.
- To utilize in vitro-in vivo extrapolation (IVIVE) coupled with physiologically based pharmacokinetic (PBPK) modeling for DDI prediction.
Main Methods:
- Physiologically based pharmacokinetic (PBPK) modeling using Simcyp software to simulate plasma concentrations of DOM and KETO.
- Integration of in vitro metabolic and inhibitory data for DOM and KETO.
- Application of the Cardiac Safety Simulator to predict QTcF interval changes based on simulated DOM concentrations and drug-induced ion channel inhibition.
Main Results:
- The combined modeling approach successfully predicted the direction and magnitude of PK and PD changes for DOM and KETO coadministration.
- Simulated DOM and KETO plasma concentrations were used to predict QTcF interval modifications.
- While the model showed good predictive power, some disparities between simulated and observed outcomes were noted.
Conclusions:
- Mechanistic PK/PD modeling and simulation, integrating IVIVE and PBPK, can effectively predict DDI-mediated pseudo-ECG modifications.
- This systems pharmacology approach aids in understanding and forecasting cardiac safety risks associated with drug combinations.
- Further refinement of the models may improve the accuracy of predicting drug-induced QTcF changes.
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