title: An evaluation of the in vitro metabolism data for predicting the clearance and drug-drug interaction potential of CYP2C9 substrates.
abstract: In the early drug discovery process, metabolic stability and cytochrome P450 inhibition are often used as an early selection tool to identify useful compounds for further development. The reliability of the data in this process is therefore crucial. In the present study, in vitro enzyme kinetic data were used to predict the in vivo clearance and drug-drug interaction potential of four well known CYP2C9 substrates (tolbutamide, fluvastatin, ibuprofen and diclofenac) that are frequently used as benchmark substances in screening programs. Quantitative predictions of hepatic clearance using the well stirred prediction model and CL(int) calculated from enzyme kinetic measurements were not useful. Including and excluding protein binding resulted in under- and overestimation, respectively, of in vivo clearance. The only predicted in vivo clearance that fell into the range of reported measured values was for fluvastatin when protein binding was not included. In an open, randomized, seven-armed, crossover study in healthy volunteers, tolbutamide, ibuprofen, and fluvastatin were investigated as inhibitors of the metabolism of diclofenac, and vice versa. None of the combinations was found to interact with each other in vivo. The in vitro drug-drug interaction potential was investigated by K(i) determinations of the same combinations. In contrast to clearance predictions, the interaction potential in vivo was best predicted when plasma protein binding was included in the various models used. This study points to the uncertainty in calculating in vivo kinetics from in vitro enzyme kinetic data. The in vitro metabolic screening can thus be questioned as a compound selection tool without a proven in vitro-in vivo correlation.
authors.affiliation: DMPK & Bioanalytical Chemistry, AstraZeneca R&D, S-431 83 Molndal, Sweden. tommy.b.andersson@astrazeneca.com
authors.forename: Tommy B
authors.initials: TB
authors.lastname: Andersson
authors.forename: Eva
authors.initials: E
authors.lastname: Bredberg
authors.forename: Hans
authors.initials: H
authors.lastname: Ericsson
authors.forename: Helena
authors.initials: H
authors.lastname: Sjöberg
mesh_terms: D000328:Adult; D019540:Area Under Curve; D001189:Aryl Hydrocarbon Hydroxylases / Q000378:metabolism*; D002851:Chromatography, High Pressure Liquid; D002853:Chromatography, Liquid; D018592:Cross-Over Studies; D065729:Cytochrome P-450 CYP2C9; D004008:Diclofenac / Q000097:blood / Q000493:pharmacokinetics*; D004347:Drug Interactions; D005229:Fatty Acids, Monounsaturated / Q000097:blood / Q000493:pharmacokinetics*; D000077340:Fluvastatin; D006801:Humans; D007052:Ibuprofen / Q000097:blood / Q000493:pharmacokinetics*; D066298:In Vitro Techniques; D007211:Indoles / Q000097:blood / Q000493:pharmacokinetics*; D008297:Male; D013058:Mass Spectrometry; D008862:Microsomes, Liver / Q000201:enzymology / Q000378:metabolism; D008875:Middle Aged; D014044:Tolbutamide / Q000097:blood / Q000493:pharmacokinetics*
chemical_list: D005229:Fatty Acids, Monounsaturated; D007211:Indoles; D004008:Diclofenac; D000077340:Fluvastatin; D014044:Tolbutamide; C450260:CYP2C9 protein, human; D065729:Cytochrome P-450 CYP2C9; D001189:Aryl Hydrocarbon Hydroxylases; D007052:Ibuprofen