Mining of Adverse Event Report Database Using Explanatory Hierarchy

Abstract

JADER database collects spontaneous reports of adverse effects of drugs in Japan. We analyze this data using the ATC classification hierarchy of drugs developed by WHO as the explanatory attribute. We propose a new method to extract characteristic nodes out of this hierarchy responsible for a specific adverse effect. PharmCompo database has been developed which enables the accurate counting of drug names appearing in various drug databases. ATC codes were also attached to all entries of PharmCompo. Application to anaphylaxis reaction has extracted 9 classification nodes including serotonin antagonists, first-generation cephalosporins and local anesthetics. Eighteen drugs were also indicated to lead to high anaphylaxis ratios, while their brother drugs in the same classification show low ratios. The comparison of chemical structures in the same class suggested that an amide-A-A-N fragment tends to cause the adverse effect.