Literature DB >> 35257289

In Vitro - in Vivo Extrapolation of Hepatic Clearance in Preclinical Species.

David A Tess1, Sangwoo Ryu2, Li Di3.   

Abstract

Accurate prediction of human clearance is of critical importance in drug discovery. In this study, in vitro - in vivo extrapolation (IVIVE) of hepatic clearance was established using large sets of compounds for four preclinical species (mouse, rat, dog, and non-human primate) to enable better understanding of clearance mechanisms and human translation. In vitro intrinsic clearances were obtained using pooled liver microsomes (LMs) or hepatocytes (HEPs) and scaled to hepatic clearance using the parallel-tube and well-stirred models. Subsequently, IVIVE scaling factors (SFs) were derived to best predict in vivo clearance. The SFs for extended clearance classification system (ECCS) class 2/4 compounds, involving metabolic clearance, were generally small (≤ 2.6) using both LMs and HEPs with parallel-tube model, with the exception of the rodents (~ 2.4-4.6), suggesting in vitro reagents represent in vivo reasonably well. SFs for ECCS class 1A and 1B are generally higher than class 2/4 across the species, likely due to the contribution of transporter-mediated clearance that is under-represented with in vitro reagents. The parallel-tube model offered lower variability in clearance predictions over the well-stirred model. For compounds that likely demonstrate passive permeability-limited clearance in vitro, rat LM predicted in vivo clearance more accurately than HEP. This comprehensive analysis demonstrated reliable IVIVE can be achieved using LMs and HEPs. Evaluation of clearance IVIVE in preclinical species helps to better understand clearance mechanisms, establish more reliable IVIVE in human, and enhance our confidence in human clearance and PK prediction, while considering species differences in drug metabolizing enzymes and transporters.
© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  IVIVE; clearance; hepatocytes; liver microsomes; passive permeability-limited clearance; transporters

Mesh:

Substances:

Year:  2022        PMID: 35257289     DOI: 10.1007/s11095-022-03205-1

Source DB:  PubMed          Journal:  Pharm Res        ISSN: 0724-8741            Impact factor:   4.200


  41 in total

1.  Insights From an Integrated Physiologically Based Pharmacokinetic Model for Brain Penetration.

Authors:  Patrick E Trapa; Elena Belova; Jenny L Liras; Dennis O Scott; Stefan J Steyn
Journal:  J Pharm Sci       Date:  2016-02       Impact factor: 3.534

Review 2.  The role of drug metabolizing enzymes in clearance.

Authors:  Li Di
Journal:  Expert Opin Drug Metab Toxicol       Date:  2014-01-07       Impact factor: 4.481

3.  A perspective on the prediction of drug pharmacokinetics and disposition in drug research and development.

Authors:  Li Di; Bo Feng; Theunis C Goosen; Yurong Lai; Stefanus J Steyn; Manthena V Varma; R Scott Obach
Journal:  Drug Metab Dispos       Date:  2013-09-24       Impact factor: 3.922

4.  Volume of Distribution in Drug Design.

Authors:  Dennis A Smith; Kevin Beaumont; Tristan S Maurer; Li Di
Journal:  J Med Chem       Date:  2015-04-01       Impact factor: 7.446

5.  In Vitro-In Vivo Extrapolation of Key Transporter Activity at the Blood-Brain Barrier.

Authors:  Patrick E Trapa; Matthew D Troutman; Thomas Y Lau; Travis T Wager; Tristan S Maurer; Nandini C Patel; Mark A West; John P Umland; Anthony A Carlo; Bo Feng; Jennifer L Liras
Journal:  Drug Metab Dispos       Date:  2019-01-25       Impact factor: 3.922

6.  Clearance in Drug Design.

Authors:  Dennis A Smith; Kevin Beaumont; Tristan S Maurer; Li Di
Journal:  J Med Chem       Date:  2018-10-17       Impact factor: 7.446

7.  Mechanistic insights from comparing intrinsic clearance values between human liver microsomes and hepatocytes to guide drug design.

Authors:  Li Di; Christopher Keefer; Dennis O Scott; Timothy J Strelevitz; George Chang; Yi-An Bi; Yurong Lai; Jonathon Duckworth; Katherine Fenner; Matthew D Troutman; R Scott Obach
Journal:  Eur J Med Chem       Date:  2012-07-16       Impact factor: 6.514

8.  Relevance of Half-Life in Drug Design.

Authors:  Dennis A Smith; Kevin Beaumont; Tristan S Maurer; Li Di
Journal:  J Med Chem       Date:  2017-11-17       Impact factor: 7.446

9.  Dose Predictions for Drug Design.

Authors:  Tristan S Maurer; Dennis Smith; Kevin Beaumont; Li Di
Journal:  J Med Chem       Date:  2020-01-22       Impact factor: 7.446

10.  Mechanistic insights on clearance and inhibition discordance between liver microsomes and hepatocytes when clearance in liver microsomes is higher than in hepatocytes.

Authors:  Christopher Keefer; George Chang; Anthony Carlo; Jonathan J Novak; Michael Banker; Jackie Carey; Julie Cianfrogna; Heather Eng; Caitlin Jagla; Nathaniel Johnson; Rhys Jones; Samantha Jordan; Sarah Lazzaro; JianHua Liu; R Scott Obach; Keith Riccardi; David Tess; John Umland; Jillian Racich; Manthena Varma; Ravi Visswanathan; Li Di
Journal:  Eur J Pharm Sci       Date:  2020-09-12       Impact factor: 4.384

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