Copyright ©The Author(s) 2017. Published by Baishideng Publishing Group Inc. All rights reserved.
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:
Correspondence to: Fabrizio De Ponti, MD, PhD, Department of Medical and Surgical Sciences, University of Bologna, Via Irnerio, 48, 40126 Bologna, Italy.
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
Core Tip

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.