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

2019; Nature Portfolio; Volume: 19; Issue: 2 Linguagem: Inglês

10.1038/s41573-019-0048-x

1474-1784

Richard Weaver, Eric A.G. Blomme, Amy E. Chadwick, Ian M. Copple, Helga H.J. Gerets, Christopher E. Goldring, André Guillouzo, Philip Hewitt, Magnus Ingelman‐Sundberg, Klaus Gjervig Jensen, Satu Juhila, Ursula Klingmüller, Gilles Labbe, Michael J. Liguori, Cerys Lovatt, Paul Morgan, Dean J. Naisbitt, Raymond Pieters, Jan Snoeys, Bob van de Water, Dominic P. Williams, B. Kevin Park,

Computational Drug Discovery Methods

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. Current preclinical models poorly predict the potential of a new drug candidate to cause drug-induced liver injury (DILI) in humans. Here, Park and colleagues discuss current understanding of the mechanisms mediating DILI and, through an academic–industry collaboration, propose a roadmap for the development of predictive preclinical models of human DILI.