Dataset Information

Stereoselective inhibition of CYP2C19 and CYP3A4 by fluoxetine and its metabolite: implications for risk assessment of multiple time-dependent inhibitor systems.

ABSTRACT: Recent guidance on drug-drug interaction (DDI) testing recommends evaluation of circulating metabolites. However, there is little consensus on how to quantitatively predict and/or assess the risk of in vivo DDIs by multiple time-dependent inhibitors (TDIs) including metabolites from in vitro data. Fluoxetine was chosen as the model drug to evaluate the role of TDI metabolites in DDI prediction because it is a TDI of both CYP3A4 and CYP2C19 with a circulating N-dealkylated inhibitory metabolite, norfluoxetine. In pooled human liver microsomes, both enantiomers of fluoxetine and norfluoxetine were TDIs of CYP2C19, (S)-norfluoxetine was the most potent inhibitor with time-dependent inhibition affinity constant (KI) of 7 μM, and apparent maximum time-dependent inhibition rate (k(inact,app)) of 0.059 min(-1). Only (S)-fluoxetine and (R)-norfluoxetine were TDIs of CYP3A4, with (R)-norfluoxetine being the most potent (K(I) = 8 μM, and k(inact,app) = 0.011 min(-1)). Based on in-vitro-to-in-vivo predictions, (S)-norfluoxetine plays the most important role in in vivo CYP2C19 DDIs, whereas (R)-norfluoxetine is most important in CYP3A4 DDIs. Comparison of two multiple TDI prediction models demonstrated significant differences between them in in-vitro-to-in-vitro predictions but not in in-vitro-to-in-vivo predictions. Inclusion of all four inhibitors predicted an in vivo decrease in CYP2C19 (95%) and CYP3A4 (60-62%) activity. The results of this study suggest that adequate worst-case risk assessment for in vivo DDIs by multiple TDI systems can be achieved by incorporating time-dependent inhibition by both parent and metabolite via simple addition of the in vivo time-dependent inhibition rate/cytochrome P450 degradation rate constant (λ/k(deg)) values, but quantitative DDI predictions will require a more thorough understanding of TDI mechanisms.

SUBMITTER: Lutz JD

PROVIDER: S-EPMC3834134 | biostudies-literature | 2013 Dec

REPOSITORIES: biostudies-literature

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Stereoselective inhibition of CYP2C19 and CYP3A4 by fluoxetine and its metabolite: implications for risk assessment of multiple time-dependent inhibitor systems.

Lutz Justin D JD VandenBrink Brooke M BM Babu Katipudi N KN Nelson Wendel L WL Kunze Kent L KL Isoherranen Nina N

Drug metabolism and disposition: the biological fate of chemicals 20130619 12

Recent guidance on drug-drug interaction (DDI) testing recommends evaluation of circulating metabolites. However, there is little consensus on how to quantitatively predict and/or assess the risk of in vivo DDIs by multiple time-dependent inhibitors (TDIs) including metabolites from in vitro data. Fluoxetine was chosen as the model drug to evaluate the role of TDI metabolites in DDI prediction because it is a TDI of both CYP3A4 and CYP2C19 with a circulating N-dealkylated inhibitory metabolite, ...[more]

PMID: 23785064

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Project description:PurposeTwo phase I, open-label trials in healthy subjects assessed whether co-administration with CYP3A4/CYP2C19 inhibitors, itraconazole/fluconazole (study A), or CYP3A4 inducer, rifampicin (study B), affects the exposure, safety/tolerability and pharmacokinetics of selumetinib and its metabolite N-desmethyl selumetinib.MethodsIn study A (n = 26), subjects received a single dose of selumetinib 25 mg and, after 4 days of washout, were randomized to treatment 1 (itraconazole 200 mg twice daily on days 1-11) or treatment 2 (fluconazole 400 mg on day 1 then 200 mg/day on days 2-11) plus co-administration of single-dose selumetinib 25 mg on day 8 (selumetinib staggered 4 h after itraconazole/fluconazole dose); Twenty-one days after discharge/washout, subjects received the alternate treatment. In study B (n = 22), subjects received a single dose of selumetinib 75 mg (day 1) then rifampicin 600 mg/day (days 4-14) plus a single dose of selumetinib 75 mg on day 12. Pharmacokinetic analysis and safety assessments were performed.ResultsSelumetinib co-administered with itraconazole, fluconazole (selumetinib staggered 4 h after itraconazole/fluconazole dose), or rifampicin was well tolerated. Selumetinib exposure was higher when co-administered with itraconazole or fluconazole (area under the plasma concentration-time curve (AUC) increased by 49 and 53%, respectively; maximum plasma concentration (C max) increased by 19 and 26%, respectively) but lower when co-dosed with rifampicin (AUC and C max decreased by 51 and 26%, respectively) versus selumetinib dosed alone. Co-administration with itraconazole or rifampicin decreased N-desmethyl selumetinib AUC(0-t) (11 and 55%, respectively), and C max (25 and 18%, respectively), with fluconazole, AUC(0-t) increased by 40%, but there was no effect on C max.ConclusionsCo-administration of CYP3A4/CYP2C19 inhibitors will likely increase exposure to selumetinib, while CYP3A4 inducers will likely reduce its exposure.

Project description:What is already known about this subjectThe analgesic activity of tilidine is mediated by its active metabolite, nortilidine, which easily penetrates the blood-brain barrier and binds to the µ-opioid receptor as a potent agonist. Tilidine undergoes an extensive first-pass metabolism, which has been suggested to be mediated by CYP3A4 and CYP2C19; furthermore, strong inhibition of CYP3A4 and CYP2C19 by voriconazole increased exposure of nortilidine, probably by inhibition of further metabolism. The novel CYP2C19 gene variant CYP2C19*17 causes ultrarapid drug metabolism, in contrast to the *2 and *3 variants, which result in impaired drug metabolism.What this study addsUsing a panel study with CYP2C19 ultrarapid and poor metabolizers, a major contribution of polymorphic CYP2C19 on tilidine metabolic elimination can be excluded. The potent CYP3A4 inhibitor ritonavir alters the sequential metabolism of tilidine, substantially reducing the partial metabolic clearances of tilidine to nortilidine and nortilidine to bisnortilidine, which increases the nortilidine exposure twofold. The lowest clearance in overall tilidine elimination is the N-demethylation of nortilidine to bisnortilidine. Inhibition of this step leads to accumulation of the active nortilidine.AimsTo investigate in vivo the effect of the CYP2C19 genotype on the pharmacokinetics of tilidine and the contribution of CYP3A4 and CYP2C19 to the formation of nortilidine using potent CYP3A4 inhibition by ritonavir.MethodsFourteen healthy volunteers (seven CYP2C19 poor and seven ultrarapid metabolizers) received ritonavir orally (300 mg twice daily) for 3 days or placebo, together with a single oral dose of tilidine and naloxone (100 mg and 4 mg, respectively). Blood samples and urine were collected for 72 h. Noncompartmental analysis was performed to determine pharmacokinetic parameters of tilidine, nortilidine, bisnortilidine and ritonavir.ResultsTilidine exposure increased sevenfold and terminal elimination half-life fivefold during ritonavir treatment, but no significant differences were observed between the CYP2C19 genotypes. During ritonavir treatment, nortilidine area under the concentration-time curve was on average doubled, with no differences between CYP2C19 poor metabolizers [2242 h ng ml(-1) (95% confidence interval 1811-2674) vs. 996 h ng ml(-1) (95% confidence interval 872-1119)] and ultrarapid metabolizers [2074 h ng ml(-1) (95% confidence interval 1353-2795) vs. 1059 h ng ml(-1) (95% confidence interval 789-1330)]. The plasma concentration-time curve of the secondary metabolite, bisnortilidine, showed a threefold increase of time to reach maximal observed plasma concentration; however, area under the concentration-time curve was not altered by ritonavir.ConclusionsThe sequential metabolism of tilidine is inhibited by the potent CYP3A4 inhibitor, ritonavir, independent of the CYP2C19 genotype, with a twofold increase in the exposure of the active nortilidine.

Dataset Information

Stereoselective inhibition of CYP2C19 and CYP3A4 by fluoxetine and its metabolite: implications for risk assessment of multiple time-dependent inhibitor systems.

Publications

Stereoselective inhibition of CYP2C19 and CYP3A4 by fluoxetine and its metabolite: implications for risk assessment of multiple time-dependent inhibitor systems.

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