Human hepatocytes and cytochrome P450-selective inhibitors predict variability in human drug exposure more accurately than human recombinant P450s

Background and PurposeDrugs metabolically eliminated by several enzymes are less vulnerable to variable compound exposure in patients due to drug-drug interactions (DDI) or if a polymorphic enzyme is involved in their elimination. Therefore, it is vital in drug discovery to accurately and efficiently estimate and optimize the metabolic elimination profile. Experimental ApproachCYP3A and/or CYP2D6 substrates with well described variability in vivo in humans due to CYP3A DDI and CYP2D6 polymorphism were selected for assessment of fraction metabolized by each enzyme (fm(CYP)) in two in vitro systems: (i) human recombinant P450s (hrP450s) and (ii) human hepatocytes combined with selective P450 inhibitors. Increases in compound exposure in poor versus extensive CYP2D6 metabolizers and by the strong CYP3A inhibitor ketoconazole were mathematically modelled and predicted changes in exposure were compared with in vivo data. Key ResultsPredicted changes in exposure were within twofold of reported in vivo values using fm(CYP) estimated in human hepatocytes and there was a strong linear correlation between predicted and observed changes in exposure (r(2)=0.83 for CYP3A, r(2)=0.82 for CYP2D6). Predictions using fm(CYP) in hrP450s were not as accurate (r(2)=0.55 for CYP3A, r(2)=0.20 for CYP2D6). Conclusions and ImplicationsThe results suggest that variability in human drug exposure due to DDI and enzyme polymorphism can be accurately predicted using fm(CYP) from human hepatocytes and CYP-selective inhibitors. This approach can be efficiently applied in drug discovery to aid optimization of candidate drugs with a favourable metabolic elimination profile and limited variability in patients.