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.
journal_name
Chem Res Toxicoljournal_title
Chemical research in toxicologyauthors
Svensson F,Zoufir A,Mahmoud S,Afzal AM,Smit I,Giblin KA,Clements PJ,Mettetal JT,Pointon A,Harvey JS,Greene N,Williams RV,Bender Adoi
10.1021/acs.chemrestox.8b00159subject
Has Abstractpub_date
2018-11-19 00:00:00pages
1119-1127issue
11eissn
0893-228Xissn
1520-5010journal_volume
31pub_type
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