%0 Journal Article %1 Kratochwil2017 %A Kratochwil, Nicole A. %A Meille, Christophe %A Fowler, Stephen %A Klammers, Florian %A Ekiciler, Aynur %A Molitor, Birgit %A Simon, Sandrine %A Walter, Isabelle %A McGinnis, Claudia %A Walther, Johanna %A Leonard, Brian %A Triyatni, Miriam %A Javanbakht, Hassan %A Funk, Christoph %A Schuler, Franz %A Lavé, Thierry %A Parrott, Neil J. %D 2017 %J The AAPS Journal %K imported %R 10.1208/s12248-016-0019-7 %T Metabolic Profiling of Human Long-Term Liver Models and Hepatic Clearance Predictions from In Vitro Data Using Nonlinear Mixed-Effects Modeling %X © 2016, The Author(s). 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 (H$\mu$REL™ 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™, H$\mu$REL™, 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., \textgreater 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.

@article{Kratochwil2017, abstract = {{\textcopyright} 2016, The Author(s). 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{\textregistered}), the hepatic stem cell line HepaRG™, and human hepatocyte co-cultures (H$\mu$REL™ and HepatoPac{\textregistered}) 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™, H$\mu$REL™, and HepatoPac{\textregistered} 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{\textregistered} and HepG2, the metabolic activity was more than tenfold lower. The micropatterned HepatoPac{\textregistered} 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., {\textgreater} 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.}, added-at = {2019-06-17T23:34:05.000+0200}, author = {Kratochwil, Nicole A. and Meille, Christophe and Fowler, Stephen and Klammers, Florian and Ekiciler, Aynur and Molitor, Birgit and Simon, Sandrine and Walter, Isabelle and McGinnis, Claudia and Walther, Johanna and Leonard, Brian and Triyatni, Miriam and Javanbakht, Hassan and Funk, Christoph and Schuler, Franz and Lav{\'{e}}, Thierry and Parrott, Neil J.}, biburl = {https://www.bibsonomy.org/bibtex/28e1143944ead20f12e3655f0140acc4d/fcdi}, doi = {10.1208/s12248-016-0019-7}, interhash = {f9c4f9265698ebe16b6ca0e168e927bc}, intrahash = {8e1143944ead20f12e3655f0140acc4d}, journal = {The AAPS Journal}, keywords = {imported}, timestamp = {2019-06-18T22:58:44.000+0200}, title = {{Metabolic Profiling of Human Long-Term Liver Models and Hepatic Clearance Predictions from In Vitro Data Using Nonlinear Mixed-Effects Modeling}}, year = 2017 }