Abstract

IN-VITRO TO IN-VIVO PREDICTION OF DRUG INTERACTIONS INVOLVING CYP3A TIME-DEPENDENT INACTIVATION

Snehal Prakash Agalave*, Pranay Prabhakar Iskar and Vishal Vijay Naik

.

Abstract

Time-dependent inactivation (TDI) of cytochrome P450s (CYPs) is a leading cause of clinical drug–drug interactions (DDIs). Current methods tend to overpredict DDIs. In this study, a numerical approach was used to model complex CYP3A TDI in human-liver microsomes. The inhibitors evaluated included troleandomycin (TAO), erythromycin (ERY), verapamil (VER), and diltiazem (DTZ) along with the primary metabolites N -dimethyl erythromycin (NDE), nor verapamil (NV), and N -dimethyl diltiazem (NDD). The complexities incorporated into the models included multiple-binding kinetics, quasiirreversible inactivation, sequential metabolism, inhibitor depletion, and membrane partitioning. The resulting inactivation parameters were incorporated into static in vitro–in vivo correlation (IVIVC) models to predict clinical DDIs. For 77 clinically observed DDIs, with a hepatic-CYP3A-synthesis-rate constant of 0.000 146 min−1, the average difference between the observed and predicted DDIs was 3.17 for the standard replot method and 1.45 for the numerical method. Similar results were obtained using a synthesisrate constant of 0.000 32 min−1. These results suggest that numerical methods can successfully model complex in vitro TDI kinetics and that the resulting DDI predictions are more accurate than those obtained with the standard replot approach.

Keywords: numerical method; time-dependent inhibition; drug–drug interactions; enzyme kinetic models.