Confidence Assessment of Predicting Clinical Drug Interactions of Mechanism-based CYP3A Inhibitors Using Simcyp Time-based Approach and a Static Mathematic Model

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.