Most U.S. adults (68%) take dietary supplements (DS) and there is increasing evidence of drug-supplement interactions (DSIs); our ability to readily identify interactions between DS with prescription medications is currently very limited. To optimize the safe use of DS, there remains a critical and unmet need for informatics methods to detect DSIs. Our rationale is that an innovative informatics framework to discover potential DSIs from the large scale of biomedical literature will enable a new line of research for targeted DSI validation and will also significantly narrow the range of DSIs that must be further explored. Our long-term goal is to use informatics approaches to enhance DSI clinical research and translate its findings to clinical practice ultimately via clinical decision support systems. The objective of this application is to develop an informatics framework to enable the discovery of DSIs by creating a DS terminology and mining scientific evidence from the biomedical literature. Towards these objectives, we propose the following specific aims: (1) Compile a comprehensive DS terminology using online resources; and (2) Discover potential DSIs from the biomedical literature. The successful accomplishment of this project will deliver a novel informatics paradigm and resources for identifying most clinically significant DSI signals and their biological mechanisms. This information is critical to subsequent efforts aimed at improving patient safety and efficacy of therapeutic interventions. The results from this study are imperative in order to achieve the ultimate goal of reducing an individual?s risk of potential DSIs.
This research will address a critical and unmet need to conduct large-scale clinical research in drug-supplement interactions (DSIs) and improve evidence bases for healthcare practice. Our primary overarching goal is to use informatics approaches to enhance DSI clinical research and translate our findings to clinical practice ultimately via clinical decision support. The successful accomplishment of this project will deliver a novel informatics paradigm and valuable resources for identifying novel clinically significant DSI signals and their associated scientific evidence.
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