Quantitative prediction of in vivo drug-drug interactions from in vitro data based on physiological pharmacokinetics: use of maximum unbound concentration of inhibitor at the inlet to the liver.
OBJECTIVE
To assess the degree to which the maximum unbound concentration of inhibitor at the inlet to the liver (I(inlet,u,max), used in the prediction of drug-drug interactions, overestimates the unbound concentration in the liver.


METHODS
The estimated value of I(inlet,u,max) was compared with the unbound concentrations in systemic blood, liver, and inlet to the liver, obtained in a simulation study based on a physiological flow model. As an example, a tolbutamide/sulfaphenazole interaction was predicted taking the plasma concentration profile of the inhibitor into consideration.


RESULTS
The value of I(inlet,u,max) differed from the concentration in each compartment, depending on the intrinsic metabolic clearance in the liver, first-order absorption rate constant, non-hepatic clearance and liver-to-blood concentration ratio (Kp) of the inhibitor. The AUC of tolbutamide was predicted to increase 4-fold when co-administered with sulfaphenazole, which agreed well with in vivo observations and was comparable with the predictions based on a fixed value of I(inlet,u,max). The blood concentration of tolbutamide was predicted to increase when it was co-administered with as little as 1/100 of the clinical dose of sulfaphenazole.


CONCLUSIONS
Although I(inlet,u,max) overestimated the unbound concentration in the liver, the tolbutamide/sulfaphenazole interaction could be successfully predicted by using a fixed value of I(inlet,u,max) indicating that the unbound concentration of sulfaphenazole in the liver after its clinical dose is by far larger than the concentration to inhibit CYP2C9-mediated metabolism and that care should be taken when it is co-administered with drugs that are substrates of CYP2C9.
Kanamitsu
S
S
Graduate School of Pharmaceutical Sciences, University of Tokyo, Japan.
Ito
K
K
Sugiyama
Y
Y
D000818:Animals; D000890:Anti-Infective Agents / Q000493:pharmacokinetics*; D001189:Aryl Hydrocarbon Hydroxylases; D065729:Cytochrome P-450 CYP2C9; D065607:Cytochrome P-450 Enzyme Inhibitors; D004305:Dose-Response Relationship, Drug; D004347:Drug Interactions; D006801:Humans; D007004:Hypoglycemic Agents / Q000493:pharmacokinetics*; D008099:Liver / Q000187:drug effects* / Q000201:enzymology; D008954:Models, Biological; D011237:Predictive Value of Tests; D039181:Steroid 16-alpha-Hydroxylase; D013250:Steroid Hydroxylases / Q000037:antagonists & inhibitors; D013426:Sulfaphenazole / Q000493:pharmacokinetics*; D014044:Tolbutamide / Q000493:pharmacokinetics*
D000890:Anti-Infective Agents; D065607:Cytochrome P-450 Enzyme Inhibitors; D007004:Hypoglycemic Agents; D013426:Sulfaphenazole; D014044:Tolbutamide; D013250:Steroid Hydroxylases; C450260:CYP2C9 protein, human; D065729:Cytochrome P-450 CYP2C9; D001189:Aryl Hydrocarbon Hydroxylases; D039181:Steroid 16-alpha-Hydroxylase