LAUSR

Cytochrome P450 reaction phenotyping to determine the fraction of metabolism (fm) values for individual enzymes is a standard study in the evaluation of a new drug. However, there are technical challenges in these studies caused by shortcomings in the selectivity of P450 inhibitors and unreliable scaling procedures for recombinant P450 (rCYP) data. In this investigation, a two-step “qualitative-then-quantitative” approach to P450 reaction phenotyping is described. In the first step, each rCYP is tested qualitatively for potential to generate metabolites. In the second step, selective inhibitors for the P450s identified in step 1 are tested for their effects on metabolism using full inhibition curves. Forty-eight drugs were evaluated in step 1 and there were no examples of missing an enzyme important to in vivo clearance. Five drugs (escitalopram, fluvastatin, pioglitazone, propranolol, and risperidone) were selected for full phenotyping in step 2 to determine fm values, with findings compared with fm values estimated from single-inhibitor concentration data and rCYP with intersystem extrapolation factor corrections. The two-step approach yielded fm values for major drug-clearing enzymes that are close to those estimated from clinical data: escitalopram and CYP2C19 (0.42 versus 0.36–0.82), fluvastatin and CYP2C9 (0.76 versus 0.76), pioglitazone and CYP2C8 (0.72 versus 0.73), propranolol and CYP2D6 (0.68 versus 0.37–0.56) and risperidone and CYP2D6 (0.60 versus 0.66–0.88). Reaction phenotyping data generated in this fashion should offer better input to physiologically based pharmacokinetic models for prediction of drug-drug interaction and impact of genetic polymorphisms on drug clearance. The qualitative-then-quantitative approach is proposed as a replacement to standard reaction phenotyping strategies. SIGNIFICANCE STATEMENT Cytochrome P450 reaction phenotyping is important for projecting drug-drug interactions and interpatient variability in drug exposure. However, currently recommended practices can frequently fail to provide reliable estimates of fractional contributions to (fm) of specific P450 enzymes to drug clearance. In this report, we describe a two-step qualitative-then-quantitative reaction phenotyping approach that yields more accurate estimates of fm.