Amiodarone and desethylamiodarone elimination kinetics following withdrawal of long‐term amiodarone maintenance therapy

Marchiset, D; Bruno, René; Djiane, P; Cano, J. P.; Benichou, M; Serradimigni, A

doi:10.1002/bdd.2510060211

Cited by 18 publications

(13 citation statements)

References 8 publications

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“…Bupropion metabolites (threohydrobupropion and erythrohydrobupropion) are present at 3.5-to 6-fold higher levels compared with the parent (Reese et al, 2008), and thus warrant further analysis by the criteria proposed herein (100% of the parent AUC). N-Desethylamiodarone would also be covered because the AUC ratio between N-desethylamiodarone and amiodarone is 1.5 (Marchiset et al, 1985). The same is true for the N-desmethyl metabolite of sertraline, which is;3-fold higher in AUC than sertraline (Patel et al, 2009).…”

Section: Consideration Of Clinically Relevant Levels and Inhibition Pmentioning

confidence: 85%

A Perspective on the Contribution of Metabolites to Drug-Drug Interaction Potential: The Need to Consider Both Circulating Levels and Inhibition Potency

Tweedie

2012

Drug Metab Dispos

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The 2012 drug-drug interaction (DDI) guidance from the European Medicines Agency (EMA) and the draft DDI guidance from the Food and Drug Administration (FDA) have proposed that metabolites present at >25% of the parent area under the time-concentration curve (AUC) (EMA and FDA) and >10% of the total drug-related exposure (EMA) should be investigated in vitro for their DDI potential. This commentary attempts to rationalize the clinically relevant levels of metabolite(s) that contribute to DDI by considering not only the abundance but also inhibition potency, physicochemical properties, and structural alerts of the metabolite. A decision tree is proposed for levels of metabolites that could trigger in vitro DDI assessment. When the parent is an inhibitor of cytochrome P450s (P450s), clinical DDI studies will assess the in vivo DDI effect of the combination of parent and metabolite(s).When the parent is not a P450 inhibitor, it is important to assess the inhibition potential of abundant metabolites in vitro. The proposal is to apply a default cutoff value of metabolite level which is 100% of the parent AUC. It is important to note that exceptions can occur, and different metabolite levels may be considered depending on the physiochemical properties of metabolites (e.g., increased lipophilicity) and whether the metabolite contains structural alerts for DDI (e.g., mechanism-based inhibition). A key objective of this commentary is to stimulate discussions among the scientific community on this important topic, so that appropriate in vitro metabolism studies are conducted on metabolites, to ensure the safety of drugs in development balanced with the desire to avoid creating unnecessary studies that will add little to no value in ensuring patient safety.

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Section: Consideration Of Clinically Relevant Levels and Inhibition Pmentioning

confidence: 85%

A Perspective on the Contribution of Metabolites to Drug-Drug Interaction Potential: The Need to Consider Both Circulating Levels and Inhibition Potency

Tweedie

2012

Drug Metab Dispos

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“…6 After long-term oral therapy, amiodarone has a true elimination half-life of up to 60 days. [7][8][9] Slow distribution to tissue results in a requirement of very long loading periods, up to several months, before reaching steady-state tissue concentrations. Large loading doses of oral therapy, typically 800 to 1600 mg/d in 3 to 4 divided doses, can accelerate the onset of activity.…”

Section: Pharmacokineticsmentioning

confidence: 99%

Evidence-Based Analysis of Amiodarone Efficacy and Safety

1999

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“…Although many clinical pharmacokinetic (PK) studies for AMIO were reported during the 1980s (Kannan et al, 1982;Bonati et al, 1983;Holt et al, 1983), the conventional PK model has not been successful in describing the disposition kinetics of AMIO and its metabolite (Weiss, 1999). Highly variable PK parameters, such as the large volume of distribution (10-65 l/kg) (Latini et al, 1984) and long terminal half-life (16 hours to 58 days after single dose, .50 days following cessation of long-term treatment) (Latini et al, 1984;Marchiset et al, 1985), have been reported. Therefore, one of the main challenges in assessing the DDI caused by AMIO is to be able to model the PK profile of both AMIO and its metabolite, MDEA, with particular emphasis on the accumulation of AMIO and MDEA in plasma and the liver.…”

Section: Introductionmentioning

confidence: 99%

Physiologically Based Pharmacokinetic Modeling to Predict Drug-Drug Interactions Involving Inhibitory Metabolite: A Case Study of Amiodarone

Chen¹,

Mao²,

Hop³

2014

Drug Metab Dispos

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Evaluation of drug-drug interaction (DDI) involving circulating inhibitory metabolites of perpetrator drugs has recently drawn more attention from regulatory agencies and pharmaceutical companies. Here, using amiodarone (AMIO) as an example, we demonstrate the use of physiologically based pharmacokinetic (PBPK) modeling to assess how a potential inhibitory metabolite can contribute to clinically significant DDIs. Amiodarone was reported to increase the exposure of simvastatin, dextromethorphan, and warfarin by 1.2-to 2-fold, which was not expected based on its weak inhibition observed in vitro. The major circulating metabolite, mono-desethyl-amiodarone (MDEA), was later identified to have a more potent inhibitory effect. Using a combined "bottom-up" and "top-down" approach, a PBPK model was built to successfully simulate the pharmacokinetic profile of AMIO and MDEA, particularly their accumulation in plasma and liver after a long-term treatment. The clinical AMIO DDIs were predicted using the verified PBPK model with incorporation of cytochrome P450 inhibition from both AMIO and MDEA. The closest prediction was obtained for CYP3A (simvastatin) DDI when the competitive inhibition from both AMIO and MDEA was considered, for CYP2D6 (dextromethorphan) DDI when the competitive inhibition from AMIO and the competitive plus time-dependent inhibition from MDEA were incorporated, and for CYP2C9 (warfarin) DDI when the competitive plus time-dependent inhibition from AMIO and the competitive inhibition from MDEA were considered. The PBPK model with the ability to simulate DDI by considering dynamic change and accumulation of inhibitor (parent and metabolite) concentration in plasma and liver provides advantages in understanding the possible mechanism of clinical DDIs involving inhibitory metabolites.

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Amiodarone and desethylamiodarone elimination kinetics following withdrawal of long‐term amiodarone maintenance therapy

Cited by 18 publications

References 8 publications

A Perspective on the Contribution of Metabolites to Drug-Drug Interaction Potential: The Need to Consider Both Circulating Levels and Inhibition Potency

A Perspective on the Contribution of Metabolites to Drug-Drug Interaction Potential: The Need to Consider Both Circulating Levels and Inhibition Potency

Evidence-Based Analysis of Amiodarone Efficacy and Safety

Physiologically Based Pharmacokinetic Modeling to Predict Drug-Drug Interactions Involving Inhibitory Metabolite: A Case Study of Amiodarone

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