Literature DB >> 20368327

Confidence assessment of the Simcyp time-based approach and a static mathematical model in predicting clinical drug-drug interactions for mechanism-based CYP3A inhibitors.

Ying-Hong Wang1.   

Abstract

Accurate prediction of the extent of mechanism-based CYP3A inhibition is critical in determining the timing of clinical drug interaction studies in drug development. To evaluate the prediction accuracy of the static and Simcyp time-based approaches, 54 clinical drug interactions involving mechanism-based CYP3A inhibitors were predicted using both methods. The Simcyp time-based approach generated better prediction when 0.03 h(-1) was used as the hepatic CYP3A enzyme degradation rate constant (k(deg)) value. Of the predictions 87 and 55% had an error less than 2 and 0.5, respectively, relative to the observed values, compared with 57 and 20%, respectively, when the Simcyp default k(deg) value of 0.0077 h(-1) was used. Accuracy improvement using the k(deg) value of 0.03 over 0.0077 h(-1) was most evident for trials with observed magnitude of interaction greater than 2-fold; predictions with an error less than 0.5 relative to clinical observations increased from 8 to 48%. For the static approach, 76 and 35% of the predictions had an error less than 2 and 0.5, respectively. Both methods generated good predictions for weak and moderate inhibitors. The prediction accuracy could be affected by our knowledge of disposition of a substrate compound, in vitro inactivation parameter estimates, and the ability of Simcyp to accurately simulate the pharmacokinetics of inhibitors. Nonetheless, both the Simcyp and static approaches are useful tools for assessing the drug-drug interaction potential of a mechanism-based CYP3A inhibitor, especially when human pharmacokinetics of the inhibitor is known and 0.03 h(-1) is used as the hepatic CYP3A k(deg) value.

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Year:  2010        PMID: 20368327     DOI: 10.1124/dmd.110.032177

Source DB:  PubMed          Journal:  Drug Metab Dispos        ISSN: 0090-9556            Impact factor:   3.922


  23 in total

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10.  Evaluating In Vitro-In Vivo Extrapolation of Toxicokinetics.

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