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Research ArticleArticle

Application of the Extended Clearance Classification System (ECCS) in Drug Discovery and Development: Selection of Appropriate In Vitro Tools and Clearance Prediction

Kenichi Umehara, Carina Cantrill, Matthias Beat Wittwer, Elisa Di Lenarda, Florian Klammers, Aynur Ekiciler, Neil Parrott, Stephen Fowler and Mohammed Ullah
Drug Metabolism and Disposition October 2020, 48 (10) 849-860; DOI: https://doi.org/10.1124/dmd.120.000133
Kenichi Umehara
Pharmaceutical Sciences, Roche Pharmaceutical Research and Early Development, Roche Innovation Center, Basel, Switzerland
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Carina Cantrill
Pharmaceutical Sciences, Roche Pharmaceutical Research and Early Development, Roche Innovation Center, Basel, Switzerland
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Matthias Beat Wittwer
Pharmaceutical Sciences, Roche Pharmaceutical Research and Early Development, Roche Innovation Center, Basel, Switzerland
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Elisa Di Lenarda
Pharmaceutical Sciences, Roche Pharmaceutical Research and Early Development, Roche Innovation Center, Basel, Switzerland
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Florian Klammers
Pharmaceutical Sciences, Roche Pharmaceutical Research and Early Development, Roche Innovation Center, Basel, Switzerland
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Aynur Ekiciler
Pharmaceutical Sciences, Roche Pharmaceutical Research and Early Development, Roche Innovation Center, Basel, Switzerland
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Neil Parrott
Pharmaceutical Sciences, Roche Pharmaceutical Research and Early Development, Roche Innovation Center, Basel, Switzerland
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Stephen Fowler
Pharmaceutical Sciences, Roche Pharmaceutical Research and Early Development, Roche Innovation Center, Basel, Switzerland
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Mohammed Ullah
Pharmaceutical Sciences, Roche Pharmaceutical Research and Early Development, Roche Innovation Center, Basel, Switzerland
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Abstract

In vitro to in vivo extrapolation (IVIVE) to predict human hepatic clearance, including metabolism and transport, requires extensive experimental resources. In addition, there may be technical challenges to measure low clearance values. Therefore, prospective identification of rate-determining step(s) in hepatic clearance through application of the Extended Clearance Classification System (ECCS) could be beneficial for optimal compound characterization. IVIVE for hepatic intrinsic clearance (CLint,h) prediction is conducted for a set of 36 marketed drugs with low-to-high in vivo clearance, which are substrates of metabolic enzymes and active uptake transporters in the liver. The compounds were assigned to the ECCS classes, and CLint,h, estimated with HepatoPac (a micropatterned hepatocyte coculture system), was compared with values calculated based on suspended hepatocyte incubates. An apparent permeability threshold (apical to basal) of 50 nm/s in LLC-PK1 cells proved optimal for ECCS classification. A reasonable performance of the IVIVE for compounds across multiple classes using HepatoPac was achieved (with 2–3-fold error), except for substrates of uptake transporters (class 3b), for which scaling of uptake clearance using plated hepatocytes is more appropriate. Irrespective of the ECCS assignment, metabolic clearance can be estimated well using HepatoPac. The validation and approach elaborated in the present study can result in proposed decision trees for the selection of the optimal in vitro assays guided by ECCS class assignment, to support compound optimization and candidate selection.

SIGNIFICANCE STATEMENT Characterization of the rate-determining step(s) in hepatic elimination could be on the critical path of compound optimization during drug discovery. This study demonstrated that HepatoPac and plated hepatocytes are suitable tools for the estimation of metabolic and active uptake clearance, respectively, for a larger set of marketed drugs, supporting a comprehensive strategy to select optimal in vitro tools and to achieve Extended Clearance Classification System–dependent in vitro to in vivo extrapolation for human clearance prediction.

Footnotes

    • Received May 29, 2020.
    • Accepted July 20, 2020.
  • This research was supported by Roche Pharmaceutical Research and Early Development.

  • https://doi.org/10.1124/dmd.120.000133.

  • ↵Embedded ImageThis article has supplemental material available at dmd.aspetjournals.org.

  • Copyright © 2020 by The American Society for Pharmacology and Experimental Therapeutics
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Drug Metabolism and Disposition: 48 (10)
Drug Metabolism and Disposition
Vol. 48, Issue 10
1 Oct 2020
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Research ArticleArticle

In Vitro Assays for CLh Prediction with ECCS-Based IVIVE

Kenichi Umehara, Carina Cantrill, Matthias Beat Wittwer, Elisa Di Lenarda, Florian Klammers, Aynur Ekiciler, Neil Parrott, Stephen Fowler and Mohammed Ullah
Drug Metabolism and Disposition October 1, 2020, 48 (10) 849-860; DOI: https://doi.org/10.1124/dmd.120.000133

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Research ArticleArticle

In Vitro Assays for CLh Prediction with ECCS-Based IVIVE

Kenichi Umehara, Carina Cantrill, Matthias Beat Wittwer, Elisa Di Lenarda, Florian Klammers, Aynur Ekiciler, Neil Parrott, Stephen Fowler and Mohammed Ullah
Drug Metabolism and Disposition October 1, 2020, 48 (10) 849-860; DOI: https://doi.org/10.1124/dmd.120.000133
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