Metabolic Profiling of Human Long-Term Liver Models and Hepatic Clearance Predictions from In Vitro Data Using Nonlinear Mixed-Effects Modeling

AAPS J. 2017 Mar;19(2):534-550. doi: 10.1208/s12248-016-0019-7. Epub 2017 Jan 3.

Abstract

Early prediction of human clearance is often challenging, in particular for the growing number of low-clearance compounds. Long-term in vitro models have been developed which enable sophisticated hepatic drug disposition studies and improved clearance predictions. Here, the cell line HepG2, iPSC-derived hepatocytes (iCell®), the hepatic stem cell line HepaRG™, and human hepatocyte co-cultures (HμREL™ and HepatoPac®) were compared to primary hepatocyte suspension cultures with respect to their key metabolic activities. Similar metabolic activities were found for the long-term models HepaRG™, HμREL™, and HepatoPac® and the short-term suspension cultures when averaged across all 11 enzyme markers, although differences were seen in the activities of CYP2D6 and non-CYP enzymes. For iCell® and HepG2, the metabolic activity was more than tenfold lower. The micropatterned HepatoPac® model was further evaluated with respect to clearance prediction. To assess the in vitro parameters, pharmacokinetic modeling was applied. The determination of intrinsic clearance by nonlinear mixed-effects modeling in a long-term model significantly increased the confidence in the parameter estimation and extended the sensitive range towards 3% of liver blood flow, i.e., >10-fold lower as compared to suspension cultures. For in vitro to in vivo extrapolation, the well-stirred model was used. The micropatterned model gave rise to clearance prediction in man within a twofold error for the majority of low-clearance compounds. Further research is needed to understand whether transporter activity and drug metabolism by non-CYP enzymes, such as UGTs, SULTs, AO, and FMO, is comparable to the in vivo situation in these long-term culture models.

Keywords: IVIVE; in vitro clearance; in vitro liver models; nonlinear mixed-effects modeling.

MeSH terms

  • Coculture Techniques
  • Cytochrome P-450 CYP2D6 / metabolism
  • Enzymes / metabolism
  • Hep G2 Cells
  • Hepatocytes / enzymology
  • Hepatocytes / metabolism*
  • Humans
  • Liver / enzymology
  • Liver / metabolism*
  • Models, Biological*
  • Nonlinear Dynamics
  • Pharmaceutical Preparations / metabolism
  • Pharmacokinetics*
  • Time Factors

Substances

  • Enzymes
  • Pharmaceutical Preparations
  • Cytochrome P-450 CYP2D6