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Published on: June 21, 2018
Drug-Drug Interactions and Combination Therapy Strategies of Amiodarone With Digoxin, Rivaroxaban, and Phenytoin
Youjun Chen1,2, Zhiwei Liu1,2, Yiming Li1,2
1Anhui Provincial Center for Drug Clinical Evaluation, Yijishan Hospital of Wannan Medical College, Wuhu, Anhui, China.
Background:
Amiodarone (AMI) is a potent inhibitor of Cytochrome P450 (CYP) 2C9 and P-glycoprotein (P-gp), as well as a weak inhibitor of CYP3A4. Concomitant administration of AMI with digoxin (DIG), rivaroxaban (RIV), or phenytoin (PHT) can significantly increase the exposure of the victim drugs. Elevated RIV exposure raises the risk of bleeding, whereas DIG and PHT have narrow therapeutic windows, potentially leading to severe toxicity when co-administered with AMI.
Purpose:
Physiologically based pharmacokinetic (PBPK) modeling was employed to simulate, validate, and predict the impact of drug-drug interactions (DDIs) between AMI and DIG, RIV, or PHT on the pharmacokinetics (PK) of victim drugs. The findings aim to provide evidence-based recommendations for optimizing combination therapy regimens.
Methods:
PBPK models for AMI, RIV, and PHT were developed using PK-Sim, while the DIG model was adopted from previously published literature. DDI scenarios were simulated to assess exposure levels. Model performance was evaluated by comparing predicted plasma concentration-time (PCT) profiles and PK parameter values with clinical trial data from healthy subjects in previously published PK studies. Finally, dosing regimens for combination therapy were adjusted based on changes in exposure levels.
Results:
According to model simulations, when the perpetrator drug AMI was co-administered with DIG, RIV, or PHT following label-recommended dosing regimens, the steady-state exposure of the victim drugs increased by 79%, 38%, and 59%, respectively. Compared to monotherapy, reducing the doses of DIG, RIV, and PHT by 40%, 25%, and 45%, respectively, achieved similar steady-state concentrations.
Conclusions:
We have successfully developed PBPK models for AMI, RIV, and PHT. These models effectively simulate the DDIs that occur when AMI is co-administered with DIG, RIV, or PHT, thereby providing guidance for dosing regimens in clinical combination therapies.
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