ABSTRACT:To understand the rate-limiting process of oral drug absorption, not only total bioavailability (F) but also intestinal (F a ⅐ F g ) and hepatic (F h ) availability after oral administration should be evaluated. Usually, F a ⅐ F g of drug is calculated from pharmacokinetic parameters after intravenous and oral administration. This approach is influenced markedly by the estimated value of F h , which varies with the hepatic blood flow used in the calculations. In this study, portal vein-cannulated rats were used to calculate the F a ⅐ F g of drugs from a single oral dosing experiment without data from intravenous injection. Portal vein-cannulated rats were prepared by a new operative method that enables stable portal vein blood flow. This surgery had no effects on hepatic blood flow and metabolic activity. Our method for calculating F a ⅐ F g was validated by determining both portal and systemic plasma concentration profiles of various drugs possessing different pharmacokinetic properties after oral administration to the portal vein-cannulated rats. Simulation of portal and systemic plasma concentrations by physiologically based pharmacokinetic modeling indicated that the balance of the absorption rate constant (k a ) and elimination rate constant (k e ) resulted in different patterns in portal and systemic plasma concentration-time profiles. This study is expected to provide a new experimental animal model that enables identification of the factors that limit oral bioavailability and to provide pharmacokinetic information on the oral absorption process of drugs during drug discovery.
Drug-drug interactions (DDIs) via cytochrome P450 (P450) induction are one clinical problem leading to increased risk of adverse effects and the need for dosage adjustments and additional therapeutic monitoring. In silico models for predicting P450 induction are useful for avoiding DDI risk. In this study, we have established regression models for CYP3A4 and CYP2B6 induction in human hepatocytes using several physicochemical parameters for a set of azole compounds with different P450 induction as characteristics as model compounds. To obtain a well-correlated regression model, the compounds for CYP3A4 or CYP2B6 induction were independently selected from the tested azole compounds using principal component analysis with fold-induction data. Both of the multiple linear regression models obtained for CYP3A4 and CYP2B6 induction are represented by different sets of physicochemical parameters. The adjusted coefficients of determination for these models were of 0.8 and 0.9, respectively. The fold-induction of the validation compounds, another set of 12 azole-containing compounds, were predicted within twofold limits for both CYP3A4 and CYP2B6. The concordance for the prediction of CYP3A4 induction was 87% with another validation set, 23 marketed drugs. However, the prediction of CYP2B6 induction tended to be overestimated for these marketed drugs. The regression models show that lipophilicity mostly contributes to CYP3A4 induction, whereas not only the lipophilicity but also the molecular polarity is important for CYP2B6 induction. Our regression models, especially that for CYP3A4 induction, might provide useful methods to avoid potent CYP3A4 or CYP2B6 inducers during the lead optimization stage without performing induction assays in human hepatocytes.
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