Multiple studies indicate that drug-drug interactions are a significant source of preventable adverse drug events. Factors contributing to the occurrence of preventable ADEs resulting from DDIs include a lack of knowledge of the patient's concurrent medications and inaccurate or inadequate knowledge of interactions by health care providers. FDA-approved drug product labeling is a major source of information intended to help clinicians prescribe drugs in a safe and effective manner. Unfortunately, drug product labeling has been identified as often lagging behind emerging drug knowledge; especially when it has been several years since a drug has been released to the market. In this paper we report on a novel approach that explores employing Semantic Web technology and natural language processing to identify drug mechanism information that may update or expand upon statements present in product labeling.
展开▼
