Real-World Evidence Conference
Exhibitor Event/Non-CE: Case Study Spotlight
Session Chair(s)
Stephen Doogan
- Chief Product Officer
- Real Life Sciences, Inc., United States
Nardin Farid
- United States
*This course requires a Separate RSVP.
Quantifying Unmet Patient Needs with Social Media Epidemiology and Natural Language Processing (NLP)
By leveraging deep NLP frameworks and Social Media Data we can generate novel insights along the patient journey. With the SPEC-F impairment framework, we apply structure to unstructured social media narratives and remove noise to generate novel insights from previously uncaptured real-world data. In this webinar, we discuss how multiple functions within Pharma use the same platform, approaches, and insights to power their respective functional activities. We will examine a case study on amplifying the patient voice in a variety of diseases and functional areas across the drug lifecycle.
Learning Objective : Featured Topics
- Industry Challenges with RWD
- Defining “Social Media Epidemiology”
- How effective NLP supports amplification of the patient voice
- Explaining the SPEC-F Framework
- Case Study: Novel Insights From Social Media Epidemiology - Alzheimer’s Disease
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