I attended a Big Data in Pharma conference recently, and very much liked a quote from Sir Muir Gray, cited by one of the speakers: "In the nineteenth century health was transformed by clean, clear water. In the twenty-first century, health will be transformed by clean clear knowledge."
This was part of a series of discussions and round tables on how we, within the Pharma industry, can best use big data, both current and legacy data, to inform decisions for the discovery, development and delivery of new healthcare therapeutics. Data integration, breaking down the data silos to create data assets, data interoperability, use of ontologies and NLP - these were all themes presented; with the aim of enabling researchers and scientists to have a clean, clear view of all the appropriate knowledge for actionable decisions across the drug development pipeline.
A new publication describes how text analytics can provide one of the tools for that data interoperablity ecosystem, to create a clear, clean view. McEntire et al. describe a system that combines Pipeline Pilot workflow tools, Linguamatics I2E NLP linguistics and semantics, and visualization dashboards, to integrate information from key public domain sources, such as MEDLINE, OMIM, ClinicalTrials.gov, NIH grants, patents, news feeds, as well as internal content sources.