PT  - JOURNAL ARTICLE
AU  - Dermot F. McGinnity
AU  - Nigel J. Waters
AU  - James Tucker
AU  - Robert J. Riley
TI  - Integrated in Vitro Analysis for the in Vivo Prediction of Cytochrome P450-Mediated Drug-Drug Interactions
AID  - 10.1124/dmd.108.020446
DP  - 2008 Jun 01
TA  - Drug Metabolism and Disposition
PG  - 1126--1134
VI  - 36
IP  - 6
4099  - http://dmd.aspetjournals.org/content/36/6/1126.short
4100  - http://dmd.aspetjournals.org/content/36/6/1126.full
SO  - Drug Metab Dispos2008 Jun 01; 36
AB  - Unbound IC50 (IC50,u) values of 15 drugs were determined in eight recombinantly expressed human cytochromes P450 (P450s) and human hepatocytes, and the data were used to simulate clinical area under the plasma concentration-time curve changes (δAUC) on coadministration with prototypic CYP2D6 substrates. Significant differences in IC50,u values between enzyme sources were observed for quinidine (0.02 μM in recombinant CYP2D6 versus 0.5 μM in hepatocytes) and propafenone (0.02 versus 4.1 μM). The relative contribution of individual P450s toward the oxidative metabolism of clinical probes desipramine, imipramine, tolterodine, propranolol, and metoprolol was estimated via determinations of intrinsic clearance using recombinant P450s (rP450s). Simulated δAUC were compared with those observed in vivo via the ratios of unbound inhibitor concentration at the entrance to the liver to inhibition constants determined against rP450s ([I]in,u/Ki) and incorporating parallel substrate elimination pathways. For this dataset, there were 20% false negatives (observed δAUC ≥ 2, predicted δAUC < 2), 77% correct predictions, and 3% false positives. Thus, the [I]in,u/Ki approach appears relatively successful at estimating the degree of clinical interactions and can be incorporated into drug discovery strategies. Using a Simcyp ADME (absorption, metabolism, distribution, elimination) simulator (Simcyp Ltd., Sheffield, UK), there were 3% false negatives, 94% correct simulations, and 3% false positives. False-negative predictions were rationalized as a result of mechanism-based inhibition, production of inhibitory metabolites, and/or hepatic uptake. Integrating inhibition and reaction phenotyping data from automated rP450 screens have shown applicability to predict the occurrence and degree of in vivo drug-drug interactions, and such data may identify the clinical consequences for candidate drugs as both “perpetrators” and “victims” of P450-mediated interactions. The American Society for Pharmacology and Experimental Therapeutics