Profiling adverse drug events of cancer drug ingredients using normalized AERS data

Liwei Wang, Hongfang Liu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

To facilitate the utilization of FDA's adverse event reporting system (AERS) for data mining, we previously normalized AERS and aggregated related data into a data set (AERS-DM). In this paper, we aim to demonstrate the data mining potential of AERS-DM by profiling cancer drug ingredients. Findings suggest that the co-relationship may exist between adverse drug events (ADEs) and mechanism of action of cancer drug ingredients, between ADEs and physiologic effect, and between ADEs and treatment intention. We speculate that such co-relationship may provide a new direction to explore the etiology of ADEs. In addition, age and sex differences in ADEs for those ingredients are revealed, among them what haven't been discovered before may be used as hypotheses for detecting drug safety signal for further investigations. In conclusion, the discoveries in this study show the potential of AERS-DM in data mining for profiling ADEs of cancer drug ingredients.

Original languageEnglish (US)
Title of host publicationProceedings - 2013 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2013
Pages46-52
Number of pages7
DOIs
StatePublished - Dec 1 2013
Event2013 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2013 - Shanghai, China
Duration: Dec 18 2013Dec 21 2013

Publication series

NameProceedings - 2013 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2013

Other

Other2013 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2013
CountryChina
CityShanghai
Period12/18/1312/21/13

Keywords

  • adverse drug events
  • cacer drug ingredients
  • data mining
  • normalized AERS data

ASJC Scopus subject areas

  • Biomedical Engineering

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  • Cite this

    Wang, L., & Liu, H. (2013). Profiling adverse drug events of cancer drug ingredients using normalized AERS data. In Proceedings - 2013 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2013 (pp. 46-52). [6732599] (Proceedings - 2013 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2013). https://doi.org/10.1109/BIBM.2013.6732599