title: Use of intrinsic clearance for prediction of human hepatic clearance.
abstract: BACKGROUND
  The use of intrinsic metabolic stability/clearance and other in vitro pharmacokinetic data for the selection of drug candidates for clinical evaluation during discovery lead optimization has become one of the primary focuses of research organizations involved in new drug discovery. Using intrinsic clearance determined from human liver microsomal preparations and/or hepatocyte to predict human clearance has become more acceptable.
  
  
  METHODS
  This review focuses on the current methods for determining intrinsic clearance and scaling to predict human hepatic clearance, and novel physiologically-based models for improvement of human hepatic clearance prediction. Published microsomal metabolic stability data and in-house hepatocyte clearance data were compared with published in vivo human hepatic clearance data. Various scaling models and the effect of protein binding were examined.
  
  
  RESULTS
  Use of a novel microfluidic model and other physiologically-based models are presented. Microsomal metabolic clearance requires correction for protein binding and in vitro microsomal binding in order to better predict in vivo hepatic clearance of compounds that are mainly eliminated by hepatic metabolism.
  
  
  CONCLUSIONS
  Metabolic clearance obtained using hepatocytes may work well in combination with the well-stirred model. Novel models incorporating flow and protein binding in the system may be the most complete models for prediction of human in vivo metabolism.
authors.affiliation: Hurel Corporation, Bervely Hills, CA 91201, USA.
authors.forename: Piyun
authors.initials: P
authors.lastname: Chao
authors.forename: Annette S
authors.initials: AS
authors.lastname: Uss
authors.forename: K C
authors.initials: KC
authors.lastname: Cheng
mesh_terms: D000818:Animals; D004353:Drug Evaluation, Preclinical; D022781:Hepatocytes / Q000378:metabolism*; D006801:Humans; D008099:Liver / Q000378:metabolism*; D008657:Metabolic Clearance Rate; D044085:Microfluidics; D008862:Microsomes, Liver / Q000378:metabolism*; D008954:Models, Biological; D004364:Pharmaceutical Preparations / Q000378:metabolism*; D010599:Pharmacokinetics; D011485:Protein Binding
chemical_list: D004364:Pharmaceutical Preparations