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World J Hepatol. Jan 8, 2017; 9(1): 30-37
Published online Jan 8, 2017. doi: 10.4254/wjh.v9.i1.30
Drug-induced liver injury: Towards early prediction and risk stratification
Emanuel Raschi, Fabrizio De Ponti
Emanuel Raschi, Fabrizio De Ponti, Department of Medical and Surgical Sciences, University of Bologna, 40126 Bologna, Italy
Author contributions: Both authors provided comments to the first draft and approved the final version of the manuscript.
Conflict-of-interest statement: The authors declare no conflicts of interest regarding this manuscript.
Open-Access: This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Correspondence to: Fabrizio De Ponti, MD, PhD, Department of Medical and Surgical Sciences, University of Bologna, Via Irnerio, 48, 40126 Bologna, Italy. fabrizio.deponti@unibo.it
Telephone: +39-051-2091805 Fax: +39-051-2091780
Received: August 2, 2016
Peer-review started: August 3, 2016
First decision: September 12, 2016
Revised: September 29, 2016
Accepted: November 27, 2016
Article in press: November 29, 2016
Published online: January 8, 2017
Processing time: 157 Days and 10.9 Hours
Abstract

Drug-induced liver injury (DILI) is a hot topic for clinicians, academia, drug companies and regulators, as shown by the steadily increasing number of publications and agents listed as causing liver damage (http://livertox.nih.gov/). As it was the case in the past decade with drug-induced QT prolongation/arrhythmia, there is an urgent unmet clinical need to develop tools for risk assessment and stratification in clinical practice and, in parallel, to improve prediction of pre-clinical models to support regulatory steps and facilitate early detection of liver-specific adverse drug events. Although drug discontinuation and therapy reconciliation still remain the mainstay in patient management to minimize occurrence of DILI, especially acute liver failure events, different multidisciplinary attempts have been proposed in 2016 to predict and assess drug-related risk in individual patients; these promising, albeit preliminary, results strongly support the need to pursue this innovative pathway.

Keywords: Hepatotoxicity; Predictivity; Risk assessment; Safety

Core tip: The interest in drug-induced liver injury (DILI) is growing, especially in 2015-2016, with pioneering studies addressing DILI annotation, i.e., risk stratification of drugs capable of causing liver damage. The latest experiences from worldwide consortia provided promising data, although there is still room for improvement before reaching an algorithm capable of discriminating hepatotoxic from non-hepatotoxic compounds, or at least of classifying high, intermediate and low risk drugs within the same therapeutic class. We should take advantage of integration of real-world data (i.e., registries, healthcare databases, spontaneous reporting systems, literature) with cheminformatics to provide a comprehensive DILI risk score.