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Information-Derived Mechanistic Hypotheses for Structural Cardiotoxicity

Svensson, F; Zoufir, A; Mahmoud, S; Afzal, AM; Smit, I; Giblin, KA; Clements, PJ; ... Bender, A; + view all (2018) Information-Derived Mechanistic Hypotheses for Structural Cardiotoxicity. Chemical Research in Toxicology , 31 (11) pp. 1119-1127. 10.1021/acs.chemrestox.8b00159. Green open access

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Abstract

Adverse events resulting from drug therapy can be a cause of drug withdrawal, reduced and or restricted clinical use, as well as a major economic burden for society. To increase the safety of new drugs, there is a need to better understand the mechanisms causing the adverse events. One way to derive new mechanistic hypotheses is by linking data on drug adverse events with the drugs’ biological targets. In this study, we have used data mining techniques and mutual information statistical approaches to find associations between reported adverse events collected from the FDA Adverse Event Reporting System and assay outcomes from ToxCast, with the aim to generate mechanistic hypotheses related to structural cardiotoxicity (morphological damage to cardiomyocytes and/or loss of viability). Our workflow identified 22 adverse event-assay outcome associations. From these associations, 10 implicated targets could be substantiated with evidence from previous studies reported in the literature. For two of the identified targets, we also describe a more detailed mechanism, forming putative adverse outcome pathways associated with structural cardiotoxicity. Our study also highlights the difficulties deriving these type of associations from the very limited amount of data available.

Type: Article
Title: Information-Derived Mechanistic Hypotheses for Structural Cardiotoxicity
Location: United States
Open access status: An open access version is available from UCL Discovery
DOI: 10.1021/acs.chemrestox.8b00159
Publisher version: http://dx.doi.org/10.1021/acs.chemrestox.8b00159
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Department of Neuromuscular Diseases
URI: https://discovery.ucl.ac.uk/id/eprint/10060165
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