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Toward predictive models for drug-induced liver injury in humans: are we there yet?

Chen, Minjun and Bisgin, Halil and Tong, Lillian and Hong, Huixiao and Fang, Hong and Borlak, Jürgen and Tong, Weida (2014) Toward predictive models for drug-induced liver injury in humans: are we there yet? Biomarkers in Medicine, 8 (2). pp. 201-213. ISSN 1752-0363. https://resolver.caltech.edu/CaltechAUTHORS:20140317-081042154

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Abstract

Drug-induced liver injury (DILI) is a frequent cause for the termination of drug development programs and a leading reason of drug withdrawal from the marketplace. Unfortunately, the current preclinical testing strategies, including the regulatory-required animal toxicity studies or simple in vitro tests, are insufficiently powered to predict DILI in patients reliably. Notably, the limited predictive power of such testing strategies is mostly attributed to the complex nature of DILI, a poor understanding of its mechanism, a scarcity of human hepatotoxicity data and inadequate bioinformatics capabilities. With the advent of high-content screening assays, toxicogenomics and bioinformatics, multiple end points can be studied simultaneously to improve prediction of clinically relevant DILIs. This review focuses on the current state of efforts in developing predictive models from diverse data sources for potential use in detecting human hepatotoxicity, and also aims to provide perspectives on how to further improve DILI prediction.


Item Type:Article
Related URLs:
URLURL TypeDescription
http://dx.doi.org/10.2217/bmm.13.146DOIArticle
http://www.futuremedicine.com/doi/abs/10.2217/bmm.13.146?url_ver=Z39.88-2003&rfr_id=ori:rid:crossref.org&rfr_dat=cr_pub%3dwww.ncbi.nlm.nih.govPublisherArticle
Additional Information:© 2014 Future Medicine Ltd. Accessed 25 October 2013. This work is licensed under the Creative Commons Attribution-NonCommercial 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/ licenses/by-nc-nd/3.0/ The authors would like to thank R Perkins for his comments and English editing. Financial & competing interests disclosure J Borlak receives funding from the German Federal Ministry of Education and Research as part of the Virtual Liver Network initiative (grant number 031 6154). J Borlak is recipient of an ORISE stipend of the US FDA, which is gratefully acknowledged. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed. No writing assistance was utilized in the production of this manuscript.
Funders:
Funding AgencyGrant Number
German Federal Ministry of Education and Research031 6154
Subject Keywords:biomarker, drug label, drug safety, drug-induced liver injury, predictive model
Issue or Number:2
Record Number:CaltechAUTHORS:20140317-081042154
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20140317-081042154
Official Citation:Toward predictive models for drug-induced liver injury in humans: are we there yet? Minjun Chen, Halil Bisgin, Lillian Tong, Huixiao Hong, Hong Fang, Jürgen Borlak, and Weida Tong Biomarkers in Medicine 2014 8:2, 201-213
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:44342
Collection:CaltechAUTHORS
Deposited By: Ruth Sustaita
Deposited On:18 Mar 2014 04:52
Last Modified:03 Oct 2019 06:16

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