Atienzar, Franck, Blomme, Eric, Chen, Minjun, Hewit , Philip, Kenna, Gerry, Labbe, Gilles, LeCluyse, Edward, Moulin, Frederic, Pognan, Francois, Roth, Adrian, Suter-Dick, Laura, Ukairo, Okechukwu, Weaver, Richard, Will, Yvonne and Dambach, Donna (2016) Key challenges and opportunities associated with the use of in vitro models to detect human DILI: integrated risk assessment and mitigation plans. BioMed Research International, 2016 (-). pp. 1-20. ISSN 10.1155

Abstract

Drug-induced liver injury (DILI) is a major cause of late-stage clinical drug attrition, market withdrawal, black-box warning and acute liver failure. Consequently, it has been an area of focus for toxicologists and clinicians in both academia and the pharmaceutical industry for several decades. In spite of considerable efforts, limited improvements in DILI prediction have been made and efforts to improve existing preclinical models or develop new test systems remain a high priority. While prediction of intrinsic DILI has improved, identifying compounds with a risk for idiosyncratic DILI (iDILI) remains extremely challenging because of the lack of a clear mechanistic understanding and the multifactorial pathogenesis of idiosyncratic drug reactions. In addition, well defined clinical diagnostic criteria and risk factors are missing. This manuscript provides an overview of the current state of DILI preclinical models with provides an emphasis overview on the key challenges associated with data interpretation, practical considerations, model limitations, and the need for an integrated risk assessment. A perspective of the promise of future technology development that may improve DILI prediction is also discussed. As demonstrated through selected initiatives to address other types of toxicities such as QT prolongation or genetic toxicity, opportunities exist however for improvement, especially through better concerted efforts at harmonization of current, emerging and novel in vitro systems or through the establishment of strategies for implementation of preclinical DILI models across the pharmaceutical industry. An example of a precompetitive effort to address this current gap, the Innovative Medicine Initiative (IMI- sponsored Mechanism-based Integrated Prediction of DILI (MIP-DILI), is provided to illustrate the benefits that harmonization and knowledge sharing can generate for pharmaceutical R&D and patients.

Disclaimer: The opinions expressed by the authors do not reflect the opinions or policies of their respective institutions. Any statements in this article should not be considered present or future policy of any regulatory agency.

Item Type:	Article
Date Deposited:	09 Nov 2016 00:45
Last Modified:	09 Nov 2016 00:45
URI:	https://oak.novartis.com/id/eprint/29364