Literature DB >> 30610004

Use of Segregated Hepatocyte Scaling Factors and Cross-Species Relationships to Resolve Clearance Dependence in the Prediction of Human Hepatic Clearance.

D Hallifax1, J B Houston2.   

Abstract

Human and rat hepatocytes have a strong tendency to underpredict hepatic intrinsic clearance (CLint) and the extent of underprediction increases with increasing observed CLint In this study, application of the log average rat hepatocyte-rat in vivo empirical scaling factor (ESF) of 4.2 to human hepatocyte prediction successfully removed bias but did not improve precision. An analogous method using individual drug rat ESFs only achieved marginal improvement in accuracy but not precision. A novel approach to resolve clearance-dependent prediction, involving rat ESFs calculated for particular (order of magnitude) ranges of observed CLint (log average range, 0.12-2.1) improved human prediction precision but only modestly reduced bias. However, rat in vivo CLint was several-fold greater than human in vivo CLint and this was reflected in greater rat hepatocyte and microsome CLint, suggesting that rat metabolic enzymes are more efficient than their human counterparts, by several-fold. By applying the segregated rat ESFs followed by the human/rat CLint ratio, which was consistent regardless of CLint (log average 3.5), both accuracy and precision were improved, providing both a means of mitigating clearance dependence and reaffirming the potential role of rat hepatocytes for prediction of human metabolic CLint These cross-species observations indicate that underprediction from human in vitro systems may be predominantly consequential of an intrinsic property of the in vitro system rather than individual drug properties.
Copyright © 2019 by The American Society for Pharmacology and Experimental Therapeutics.

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Year:  2019        PMID: 30610004     DOI: 10.1124/dmd.118.085191

Source DB:  PubMed          Journal:  Drug Metab Dispos        ISSN: 0090-9556            Impact factor:   3.922


  5 in total

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Authors:  David A Tess; Sangwoo Ryu; Li Di
Journal:  Pharm Res       Date:  2022-03-07       Impact factor: 4.200

Review 2.  Current Approaches for Predicting Human PK for Small Molecule Development Candidates: Findings from the IQ Human PK Prediction Working Group Survey.

Authors:  Carl Petersson; Xin Zhou; Joerg Berghausen; David Cebrian; Michael Davies; Kevin DeMent; Peter Eddershaw; Arian Emami Riedmaier; Alix F Leblanc; Nenad Manveski; Punit Marathe; Panteleimon D Mavroudis; Robin McDougall; Neil Parrott; Andreas Reichel; Charles Rotter; David Tess; Laurie P Volak; Guangqing Xiao; Zheng Yang; James Baker
Journal:  AAPS J       Date:  2022-07-19       Impact factor: 3.603

3.  Investigating the Theoretical Basis for In Vitro-In Vivo Extrapolation (IVIVE) in Predicting Drug Metabolic Clearance and Proposing Future Experimental Pathways.

Authors:  Leslie Z Benet; Jasleen K Sodhi
Journal:  AAPS J       Date:  2020-09-10       Impact factor: 4.009

4.  Multi-Well Array Culture of Primary Human Hepatocyte Spheroids for Clearance Extrapolation of Slowly Metabolized Compounds.

Authors:  Lena C Preiss; Volker M Lauschke; Katrin Georgi; Carl Petersson
Journal:  AAPS J       Date:  2022-03-11       Impact factor: 4.009

5.  Recent developments in in vitro and in vivo models for improved translation of preclinical pharmacokinetics and pharmacodynamics data.

Authors:  Jaydeep Yadav; Mehdi El Hassani; Jasleen Sodhi; Volker M Lauschke; Jessica H Hartman; Laura E Russell
Journal:  Drug Metab Rev       Date:  2021-05-25       Impact factor: 6.984

  5 in total

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