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1. Managing the challenge of drug-induced liver injury: a roadmap for the development and deployment of preclinical predictive models

Author

Raymond Pieters, Klaus Gjervig Jensen, Philip G. Hewitt, Jan Snoeys, Bob van de Water, B. Kevin Park, Ursula Klingmüller, André Guillouzo, Ian M. Copple, Dominic P. Williams, Michael J. Liguori, Cerys A. Lovatt, Paul Morgan, Satu Juhila, Eric A.G. Blomme, Magnus Ingelman-Sundberg, Dean J. Naisbitt, Gilles Labbe, Amy E. Chadwick, Christopher E. Goldring, Helga H.J. Gerets, Richard J. Weaver, Jonchère, Laurent, Mechanism-Based Integrated Systems for the Prediction of Drug-Induced Liver Injury - MIP-DILI - - EC:FP7:SP1-JTI2012-02-01 - 2017-01-31 - 115336 - VALID, University of Liverpool, Nutrition, Métabolismes et Cancer (NuMeCan), Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Merck Research Laboratories, Karolinska Institutet [Stockholm], Division Systems Biology of Signal Transduction, German Cancer Research Center (DKFZ), German Cancer Research Center - Deutsches Krebsforschungszentrum [Heidelberg] (DKFZ), SANOFI Recherche, Abbvie Inc. [North Chicago], GlaxoSmithKline, Glaxo Smith Kline, AstraZeneca, University Medical Center [Utrecht], Janssen Research & Development, Leiden University, Institut de Recherches Internationales Servier [Suresnes] (IRIS), UCB BioPharma [Braine l’Alleud, Belgium], This work was supported by the European Community (Contract MIP-DILI-115336) under the Innovative Medicines Initiative Joint Undertaking, a contribution from the European Union's Seventh Framework Programme (FP7/20072013) and European Federation of Pharmaceutical Industries and Associations (EFPIA) companies (http://www.imi.europa.eu/) and by the German Ministry of Education and Research (BMBF) within ‘Multi-Scale Modeling of Drug-Induced Liver Injury’ (MS_DILI, 031L0074A)., European Project: 115336,EC:FP7:SP1-JTI,IMI-JU-03-2010,MIP-DILI(2012), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES), and Universiteit Leiden

Subjects
0301 basic medicine, Drug, Drug-Related Side Effects and Adverse Reactions, [SDV]Life Sciences [q-bio], media_common.quotation_subject, In vitro model, 03 medical and health sciences, Preclinical research, 0302 clinical medicine, Predictive Value of Tests, Drug Discovery, Animals, Humans, Medicine, media_common, Pharmacology, Adverse effects, business.industry, [SDV.MHEP.HEG]Life Sciences [q-bio]/Human health and pathology/Hépatology and Gastroenterology, General Medicine, [SDV.MHEP.HEG] Life Sciences [q-bio]/Human health and pathology/Hépatology and Gastroenterology, 3. Good health, [SDV] Life Sciences [q-bio], Disease Models, Animal, 030104 developmental biology, Risk analysis (engineering), Software deployment, Preclinical testing, 030220 oncology & carcinogenesis, Chemical and Drug Induced Liver Injury, business
Abstract

International audience; Drug-induced liver injury (DILI) is a patient-specific, temporal, multifactorial pathophysiological process that cannot yet be recapitulated in a single in vitro model. Current preclinical testing regimes for the detection of human DILI thus remain inadequate. A systematic and concerted research effort is required to address the deficiencies in current models and to present a defined approach towards the development of new or adapted model systems for DILI prediction. This Perspective defines the current status of available models and the mechanistic understanding of DILI, and proposes our vision of a roadmap for the development of predictive preclinical models of human DILI.

Published
2019

2. A multicenter assessment of single-cell models aligned to standard measures of cell health for prediction of acute hepatotoxicity

Author

Mohamed Elmasry, Cerys A. Lovatt, Julie C. Holder, Christopher E. Goldring, Hélène Aerts, Christopher A. Schofield, Helga H.J. Gerets, Delphine Hoët, Richard J. Weaver, Eliane Alexandre, Lysiane Richert, Gilles Labbe, Esther Johann, Sébastien Anthérieu, Martina Dorau, Magnus Ingelman-Sundberg, B. Kevin Park, Neil R. Kitteringham, Robert P. Jones, Simone H. Stahl, Philip G. Hewitt, Rowena Sison-Young, and Volker M. Lauschke

Subjects
0301 basic medicine, Drug, Cytotoxicity, Health, Toxicology and Mutagenesis, media_common.quotation_subject, Cell, Acute, Pharmacology, Toxicology, 030226 pharmacology & pharmacy, Organ Toxicity and Mechanisms, 03 medical and health sciences, 0302 clinical medicine, Pharmacokinetics, In vivo, Predictive toxicology, Toxicity Tests, Acute, Humans, Medicine, Cells, Cultured, media_common, Cryopreservation, Liver injury, Toxicity, business.industry, Reproducibility of Results, Hep G2 Cells, General Medicine, medicine.disease, In vitro, 3. Good health, 030104 developmental biology, medicine.anatomical_structure, Hepatocytes, Hepatic stellate cell, Pharmaceuticals, Chemical and Drug Induced Liver Injury, business
Abstract

Assessing the potential of a new drug to cause drug-induced liver injury (DILI) is a challenge for the pharmaceutical industry. We therefore determined whether cell models currently used in safety assessment (HepG2, HepaRG, Upcyte and primary human hepatocytes in conjunction with basic but commonly used endpoints) are actually able to distinguish between novel chemical entities (NCEs) with respect to their potential to cause DILI. A panel of thirteen compounds (nine DILI implicated and four non-DILI implicated in man) were selected for our study, which was conducted, for the first time, across multiple laboratories. None of the cell models could distinguish faithfully between DILI and non-DILI compounds. Only when nominal in vitro concentrations were adjusted for in vivo exposure levels were primary human hepatocytes (PHH) found to be the most accurate cell model, closely followed by HepG2. From a practical perspective, this study revealed significant inter-laboratory variation in the response of PHH, HepG2 and Upcyte cells, but not HepaRG cells. This variation was also observed to be compound dependent. Interestingly, differences between donors (hepatocytes), clones (HepG2) and the effect of cryopreservation (HepaRG and hepatocytes) were less important than differences between the cell models per se. In summary, these results demonstrate that basic cell health endpoints will not predict hepatotoxic risk in simple hepatic cells in the absence of pharmacokinetic data and that a multicenter assessment of more sophisticated signals of molecular initiating events is required to determine whether these cells can be incorporated in early safety assessment. Electronic supplementary material The online version of this article (doi:10.1007/s00204-016-1745-4) contains supplementary material, which is available to authorized users.

Published
2016

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