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 (kinact,app) of 0.059 min−1. Only (S)-fluoxetine and (R)-norfluoxetine were TDIs of CYP3A4, with (R)-norfluoxetine being the most potent (KI = 8 μM, and kinact,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/kdeg) values, but quantitative DDI predictions will require a more thorough understanding of TDI mechanisms.
Footnotes
- Received April 30, 2013.
- Accepted June 19, 2013.
↵1 Current affiliation: Amgen, Inc., Seattle, Washington.
↵2 Current affiliation: Sri Lakshmi Barghavi Pharma, Pvt. Ltd., Pashamylaram, India.
This work was supported by the National Institutes of Health National Institute of General Medical Sciences [Grants P01 GM32165 and T32 GM007750].
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- Copyright © 2013 by The American Society for Pharmacology and Experimental Therapeutics
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