Time: 8:00am PDT, 11:00am EDT, 4:00pm BST, 5:00pm CEST
Duration: 60 minutes
There are many tasks in pharma, from discovery to medical, development to commercialization, that rely heavily on having and using the right data. Finding and extracting the right data, however, is no easy task, and must be done against the backdrop of the ever-increasing volume of data being generated. Add to this, the challenges of document-based or unstructured data, where information is not consistently written or referenced, and meta data is poor or incomplete.
In this webinar, you will hear about how we tackle some of these challenges by applying natural language processing to high value, large scale data sources and making them available to users to find, extract and use the specific information they need. We will share examples of these data sources being used to solve real problems and demonstrate some of the tools we use to instantly access, navigate and start analyzing these data.
You will learn about:
Which data sources you can readily get value from with text mining and search
Challenges with specific sources that are commonly experienced by users
The difference between using native search tools and natural language processing.
Enhanced search and visualization tools in action
Who should attend?
This webinar is suitable for teams that use and needs better experiences with key data sources such as FDA Drug Labels, ct.gov, Medline, Patents and more. This is relevant for teams in drug discovery, translational science, safety, regulatory affairs, HEOR, medical affairs and MSL leaders and managers.