Resources
Use Cases:
Revolutionizing Rare Disease Intelligence Generation with AI Powered Analysis
Access the PDF Use Case.
At a Glance
Challenges
- Multiple, low-volume data sources to combine and analyze: Closed communities, HCP transcripts, surveys can make comprehensive analysis difficult
- Topic and sentiment clarity: Difficulty in quickly identifying key discussion topics, unmet needs, and sentiment across diverse data types
Brief
- 80% Efficiency Gain: Rapidly structured and analyzed diverse data, drastically reducing time spent on manual processing
- Integrated intelligence: Delivered a comprehensive view across all data sources, with flexibility to focus on specific populations like HCP specialties
- Proactive trend monitoring: Allowed tracking of conversations and emerging trends, especially during key events like drug launches
Customer Objective
A rare disease focused Healthcare Advertising Agency needed to provide on demand Patient and HCP intelligence to their Clients in a fast and effective way. They faced challenges in quickly and comprehensively understanding the key topics of discussion, areas of unmet need and general sentiment of conversations. The Agency possessed a low volume of data from multiple data types, including data from a closed community, transcript data from HCP interviews, and market research surveys all of which needed to be processed and analyzed in a timely manner.
Brief
The brief given to Talking Medicines was to apply Advanced Data Science & AI to analyze the Agency’s data (from closed communities, HCP transcripts and surveys) to provide information about the key topics of conversation in Patient and HCP populations and the general sentiment of these conversations in a fast, effective and repeatable manner.
Solution
By leveraging Drug-GPT, the Agency was able to:
- Rapidly structure unstructured information from various sources, resulting in a comprehensive view of sentiment and topics over time
- Gain an 80% time efficiency improvement
- Review data intelligence for all data collectively, as different data types, or as subpopulations of interest (HCP specialty)
Furthermore, the Agency was able to re-run the models at strategically important times, such as post-drug launch, to monitor conversations and emerging trends.
