New IVIVE method for the prediction of total human clearance and relative elimination pathway contributions from in vitro hepatocyte and microsome data

Abstract

Total human clearance is a key determinant for the pharmacokinetic behavior of drug candidates. Our group recently introduced the Extended Clearance Model (ECM) as an accurate in vitro-in vivo extrapolation (IVIVE) method for the prediction of hepatic clearance. Yet, knowledge about relative elimination pathway contributions is needed in order to predict the total human clearance of drug candidates. In the present work, a training set of 18 drug compounds was used to describe the affiliations between in vitro sinusoidal uptake clearance and the fractional contributions of hepatic (metabolic and biliary) or renal clearance to overall in vivo elimination. By means of these quantitative relationships and using a validation set of 10 diverse drug molecules covering different (sub)classes of the Extended Clearance Concept Classification System (ECCCS), the relative contributions of elimination pathways were calculated and demonstrated to well correlate with human reference data. Likewise, ECM- and pathway-based predictions of total clearances from both data sets demonstrated a strong correlation with the observed clinical values with 26 out of 28 compounds within a three-fold deviation. Hence, total human clearance and relative contributions of elimination pathways were successfully predicted by the presented method using solely hepatocyte and microsome in vitro data.

Keywords: Aliskiren (PubChem CID: 5493444); Atorvastatin (PubChem CID: 60823); Clearance prediction; Cyclosporine A (PubChem CID: 5284373); Digoxin (PubChem CID: 2724385); Extended Clearance Concept Classification System (ECCCS); Hepatic uptake; In vitro–in vivo extrapolation (IVIVE); Ketoconazole (PubChem CID: 47576); Pitavastatin (PubChem CID: 5282452); Pravastatin (PubChem CID: 54687); Quinidine (PubChem CID: 441074); Simvastatin acid (PubChem CID: 64718); Valsartan (PubChem CID: 60846).