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Advanced preclinical models for evaluation of drug-induced liver injury – consensus statement by the European Drug-Induced Liver Injury Network [PRO-EURO-DILI-NET]

Authors :
European Cooperation in Science and Technology
Biotechnology and Biological Sciences Research Council (UK)
Engineering and Physical Sciences Research Council (UK)
Fundação para a Ciência e a Tecnologia (Portugal)
The Scientific and Technological Research Council of Turkey
Instituto de Salud Carlos III
European Commission
Generalitat de Catalunya
Ministry of Education, Youth and Sports (Czech Republic)
Ministerio de Economía y Competitividad (España)
Agencia Estatal de Investigación (España)
Ministerio de Ciencia, Innovación y Universidades (España)
University of Southern California
National Institute on Alcohol Abuse and Alcoholism (US)
National Institutes of Health (US)
Fundación BBVA
Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (España)
Fundació La Marató de TV3
Research Council of Norway
Fernández-Checa, José C.
Bagnaninchi, Pierre
Ye, Hui
Sancho-Bru, Pau
Falcón-Pérez, Juan M.
Royo, Félix
García-Ruiz, Carmen
Konu, Ozlen
Miranda, Joana
Lunov, Oleg
Dejneka, Alexandr
Elfick, Alistair
McDonald, Alison
Sullivan, Gareth J.
Aithal, Guruprasad P.
Lucena, M. Isabel
Andrade, Raúl J.
Fromenty, Bernard
Kranendonk, Michel
Cubero, Francisco Javier
Nelson, Leonard J.
European Cooperation in Science and Technology
Biotechnology and Biological Sciences Research Council (UK)
Engineering and Physical Sciences Research Council (UK)
Fundação para a Ciência e a Tecnologia (Portugal)
The Scientific and Technological Research Council of Turkey
Instituto de Salud Carlos III
European Commission
Generalitat de Catalunya
Ministry of Education, Youth and Sports (Czech Republic)
Ministerio de Economía y Competitividad (España)
Agencia Estatal de Investigación (España)
Ministerio de Ciencia, Innovación y Universidades (España)
University of Southern California
National Institute on Alcohol Abuse and Alcoholism (US)
National Institutes of Health (US)
Fundación BBVA
Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (España)
Fundació La Marató de TV3
Research Council of Norway
Fernández-Checa, José C.
Bagnaninchi, Pierre
Ye, Hui
Sancho-Bru, Pau
Falcón-Pérez, Juan M.
Royo, Félix
García-Ruiz, Carmen
Konu, Ozlen
Miranda, Joana
Lunov, Oleg
Dejneka, Alexandr
Elfick, Alistair
McDonald, Alison
Sullivan, Gareth J.
Aithal, Guruprasad P.
Lucena, M. Isabel
Andrade, Raúl J.
Fromenty, Bernard
Kranendonk, Michel
Cubero, Francisco Javier
Nelson, Leonard J.
Publication Year :
2021

Abstract

Drug-induced liver injury (DILI) is a major cause of acute liver failure (ALF) and one of the leading indications for liver transplantation in Western societies. Given the wide use of both prescribed and over the counter drugs, DILI has become a major health issue for which there is a pressing need to find novel and effective therapies. Although significant progress has been made in understanding the molecular mechanisms underlying DILI, our incomplete knowledge of its pathogenesis and inability to predict DILI is largely due to both discordance between human and animal DILI in preclinical drug development and a lack of models that faithfully recapitulate complex pathophysiological features of human DILI. This is exemplified by the hepatotoxicity of acetaminophen (APAP) overdose, a major cause of ALF because of its extensive worldwide use as an analgesic. Despite intensive efforts utilising current animal and in vitro models, the mechanisms involved in the hepatotoxicity of APAP are still not fully understood. In this expert Consensus Statement, which is endorsed by the European Drug-Induced Liver Injury Network, we aim to facilitate and outline clinically impactful discoveries by detailing the requirements for more realistic human-based systems to assess hepatotoxicity and guide future drug safety testing. We present novel insights and discuss major players in APAP pathophysiology, and describe emerging in vitro and in vivo pre-clinical models, as well as advanced imaging and in silico technologies, which may improve prediction of clinical outcomes of DILI.

Details

Database :
OAIster
Publication Type :
Electronic Resource
Accession number :
edsoai.on1306016255
Document Type :
Electronic Resource