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BioMed Research International
Volume 2016 (2016), Article ID 9737920, 20 pages
Review Article

Key Challenges and Opportunities Associated with the Use of In Vitro Models to Detect Human DILI: Integrated Risk Assessment and Mitigation Plans

1UCB BioPharma SPRL, Chemin du Foriest, R9 Building, 1420 Braine-l’Alleud, Belgium
2AbbVie, 1 North Waukegan Road, North Chicago, IL 60064, USA
3Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration (FDA), Jefferson, AR 72079, USA
4Merck KGaA, Frankfurter Strasse 250, 64293 Darmstadt, Germany
5Drug Safety Consultant, Macclesfield, Cheshire SK11, UK
6Sanofi, Bâtiment C. Bernard, 13 Quai Jules Guesdes, Zone B, BP14, 94403 Vitry-sur-Seine Cedex, France
7U.S. Food and Drug Administration, Center for Drug Evaluation and Research, Silver Spring, MD 20993, USA
8Novartis Pharma AG, Klybeckstrasse 141, 4057 Basel, Switzerland
9Hoffmann La-Roche Inc., 4000 Basel, Switzerland
10School of Life Sciences, University of Applied Sciences Northwestern Switzerland, Gründenstrasse 40, 4132 Muttenz, Switzerland
11Ipsen Biosciences Inc., 650 E Kendall Street, Cambridge, MA 02142, USA
12Institut de Recherches Internationales Servier (IRIS), 50 rue Carnot, 92284 Suresnes Cedex, France
13Pfizer R&D, Drug Safety Research and Development, Eastern Point Road, Groton, CT 06340, USA
14Genentech, 1 DNA Way, South San Francisco, CA 94080, USA

Received 29 April 2016; Accepted 22 June 2016

Academic Editor: Hwa-Liang Leo

Copyright © 2016 Franck A. Atienzar et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Drug-induced liver injury (DILI) is a major cause of late-stage clinical drug attrition, market withdrawal, black-box warnings, and acute liver failure. Consequently, it has been an area of focus for toxicologists and clinicians for several decades. In spite of considerable efforts, limited improvements in DILI prediction have been made and efforts to improve existing preclinical models or develop new test systems remain a high priority. While prediction of intrinsic DILI has improved, identifying compounds with a risk for idiosyncratic DILI (iDILI) remains extremely challenging because of the lack of a clear mechanistic understanding and the multifactorial pathogenesis of idiosyncratic drug reactions. Well-defined clinical diagnostic criteria and risk factors are also missing. This paper summarizes key data interpretation challenges, practical considerations, model limitations, and the need for an integrated risk assessment. As demonstrated through selected initiatives to address other types of toxicities, opportunities exist however for improvement, especially through better concerted efforts at harmonization of current, emerging and novel in vitro systems or through the establishment of strategies for implementation of preclinical DILI models across the pharmaceutical industry. Perspectives on the incorporation of newer technologies and the value of precompetitive consortia to identify useful practices are also discussed.