TY - GEN
T1 - Profiling adverse drug events of cancer drug ingredients using normalized AERS data
AU - Wang, Liwei
AU - Liu, Hongfang
PY - 2013
Y1 - 2013
N2 - 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.
AB - 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.
KW - adverse drug events
KW - cacer drug ingredients
KW - data mining
KW - normalized AERS data
UR - http://www.scopus.com/inward/record.url?scp=84894584451&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84894584451&partnerID=8YFLogxK
U2 - 10.1109/BIBM.2013.6732599
DO - 10.1109/BIBM.2013.6732599
M3 - Conference contribution
AN - SCOPUS:84894584451
SN - 9781479913091
T3 - Proceedings - 2013 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2013
SP - 46
EP - 52
BT - Proceedings - 2013 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2013
T2 - 2013 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2013
Y2 - 18 December 2013 through 21 December 2013
ER -