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Nat Rev Drug Discov. 2020 Feb;19(2):131-148. doi: 10.1038/s41573-019-0048-x. Epub 2019 Nov 20.

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

Author information

1
Biopharmacy, Institute de Recherches Internationales Servier, Suresnes, France. richard.weaver@servier.com.
2
Global Preclinical Safety, Abbvie, North Chicago, IL, USA.
3
Department of Molecular and Clinical Pharmacology, MRC Centre for Drug Safety Science, University of Liverpool, Liverpool, UK.
4
Development Science, UCB BioPharma SPRL, Braine-l'Alleud, Belgium.
5
INSERM, INRA, Institut NUMECAN (Nutrition Metabolisms and Cancer), UMR_S 1241, University Rennes, Rennes, France.
6
Chemical and Preclinical Safety, Merck Healthcare KGaA, Darmstadt, Germany.
7
Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden.
8
Drug ADME Research, H. Lundbeck A/S, Valby, Denmark.
9
In Vitro Biology, Orion Pharma, Espoo, Finland.
10
Systems Biology of Signal Transduction, German Cancer Research Center, Heidelberg, Germany.
11
Investigative Toxicology, Preclinical Safety, Sanofi R&D, Paris, France.
12
Non-Clinical Safety, GlaxoSmithKline, Ware, UK.
13
Clinical Pharmacology and Safety Sciences, Biopharmaceuticals Science Unit, AstraZeneca, Cambridge, UK.
14
Immunotoxicology, Faculty of Veterinary Medicines, Institute for Risk Assessment Sciences, Utrecht University, Utrecht, Netherlands.
15
Drug Metabolism and Pharmacokinetics, Janssen Research and Development, Beerse, Belgium.
16
Division of Drug Discovery and Safety, Leiden Academic Centre for Drug Research, Leiden University, Leiden, Netherlands.
17
Department of Molecular and Clinical Pharmacology, MRC Centre for Drug Safety Science, University of Liverpool, Liverpool, UK. bkpark@liverpool.ac.uk.

Abstract

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.

PMID:
31748707
DOI:
10.1038/s41573-019-0048-x

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