Presentation of a modified dispersion model (MDM) for hepatic drug extraction and a new methodology for the prediction of the rate-limiting step in hepatic metabolic clearance

Verapamil hepatic clearance in four preclinical rat models: towards activity-based scaling

The current study was designed to cross-validate rat liver microsomes (RLM), suspended rat hepatocytes (SRH) and the isolated perfused rat liver (IPRL) model against in vivo pharmacokinetic data, using verapamil as a model drug. Michaelis-Menten constants (Km), for the metabolic disappearance kinetics of verapamil in RLM and SRH (freshly isolated and cryopreserved), were determined and corrected for non-specific binding. The 'unbound' Km determined with RLM (2.8 µM) was divided by the 'unbound' Km determined with fresh and cryopreserved SRH (3.9 µM and 2.1 µM, respectively) to calculate the ratio of intracellular to extracellular unbound concentration (Kpu,u). Kpu,u was significantly different between freshly isolated (0.71) and cryopreserved (1.31) SRH, but intracellular capacity for verapamil metabolism was maintained after cryopreservation (200 vs. 191 µl/min/million cells). Direct comparison of intrinsic clearance values (Clint) in RLM versus SRH, yielded an activity-based scaling factor (SF) of 0.28-0.30 mg microsomal protein/million cells (MPPMC). Merging the IPRL-derived Clint with the MPPMC and SRH data, resulted in scaling factors for MPPGL (80 and 43 mg microsomal protein/g liver) and HPGL (269 and 153 million cells/g liver), respectively. Likewise, the hepatic blood flow (61 ml/min/kg b.wt) was calculated using IPRL Clint and the in vivo Cl. The scaling factors determined here are consistent with previously reported CYP450-content based scaling factors. Overall, the results show that integrated interpretation of data obtained with multiple preclinical tools (i.e. RLM, SRH, IPRL) can contribute to more reliable estimates for scaling factors and ultimately to improved in vivo clearance predictions based on in vitro experimentation.

Practical permeability-based hepatic clearance classification system (HepCCS) in drug discovery

Background: The use of liver microsomes and hepatocytes to predict total in vivo clearance is standard practice in the pharmaceutical industry; however, metabolic stability data alone cannot always predict in vivo clearance accurately. Results: Apparent permeability generated from Mardin–Darby canine kidney cells and rat hepatocyte uptake for 33 discovery compounds were obtained. Conclusion: When there is underprediction of in vivo clearance, compounds with low apparent permeability (less than 3 × 10-6 cm/s) all exhibited hepatic uptake. A systematic approach in the form of a classification system (hepatic clearance classification system) and decision tree that will help drug discovery scientists understand in vitro–in vivo clearance prediction disconnect early is proposed.