The Møller Centre, Cambridge UK

Stories from the Clinical Coal-Face: Practical uses of Text Mining, in Life Sciences and Healthcare

March 31 2017

What are the challenges facing life sciences and healthcare organisations, where text analytics can play a part?  This is one of the key questions that I ask myself and others regularly. There is so much buzz at the minute around big data, real world data, healthcare informatics, wearables; but what is really working, and what is just hype?

One of the ways we get input on this question is, of course, meeting our customers and hearing about their successes. Linguamatics hosts two user group meetings every year, and our European Spring Text Mining Conference is coming up rapidly. Held over 3 days in April, the conference provides scientists and clinicians interested in text mining to come for hands-on training workshops, round table discussions, and a day of talks from both Linguamatics staff and our customers.

This year, our customer speakers encompass a wide range of use cases, spanning the pipeline of discovery, development, and delivery of therapeutics:

  • Daniel Stoffler and Raul Rodriguez-Esteban from Roche will be talking about the development of an automated system that uses text-mining to pull out relevant context around chemicals, genes and diseases from scientific literature, and cluster compounds around the targets that they affect and diseases to which they are linked.
  • Moving into the regulatory sphere, Jon Sanford & Will Hayes from Mundipharma will be presenting on the use of I2E to extract key data elements relevant for IDMP compliance, and how this fits into a broader master data management strategy for regulatory affairs and beyond.
  • Looking into applications of NLP for real world data, James Loudon-Griffiths, AstraZeneca, has been working on comparing clinical trial reports of nausea from FDA drug labels to patient reported outcomes from PatientsLikeMe.
  • Moving into clinical applications of text mining, Samir Courdy from the Huntsman Cancer Institute will reveal the work he and his team are carrying out to develop automated workflows, using I2E, to tag all relevant clinical information from surgical pathology and radiology reports and physicians notes, to enable improved patient outcomes and clinical research.
  • And, Helen Pitman, Cancer Research UK, will be presenting on using NLP for structured data extraction from free text pathology reports for lung cancer patients, as part of the CR-UK Stratified Medicine Programme (SMP).

As you can see, a wealth of different applications of text mining!  And of course, there will be talks from Linguamatics experts to give you the latest updates on I2E, AMP for real-time failsafe processing, the fit with big data, NLP and machine learning, and more.

If you would like to hear more, please do sign up. And of course, if you can’t attend but would like to hear more, please do drop me a note.