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

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.