Adverse reactions to drugs are a major public healthcare issue. Currently, the Food and Drug Administration (FDA) publishes quarterly reports that typically contain in the order of 200,000 adverse incidents. In such a large number of incidents, low frequency events that may be highly clinically significant but are often undetected. In this poster, we introduce a pixel cell-based visualization technique with novel relevance ordering algorithm, significance statistics computation, and semantic zooming in an x-y plan. We are able to identify important adverse events, such as the known association of the drug Avandia with myocardial infarction; as well as low frequency events such as the association of Actos with bladder cancer.