October 8th, 12pm EDT
Conducting real-world research in rheumatology is challenging. Patients often present with multiple comorbidities, disease measures are inconsistently captured in routine care, and traditional data sources don’t always reflect full patient journeys across specialties. In this webinar, OM1 experts will share how AI-enabled, multi-source real-world data can help overcome these barriers and deliver more robust, generalizable insights. Drawing on recent research and case studies, including a large real-world study of rheumatoid arthritis patients, we’ll highlight how novel endpoints such as estimated Clinical Disease Activity Index (CDAI) and advanced analytics are closing evidence gaps and reshaping the future of rheumatology research.
Key Highlights:
- Learn emerging techniques in using AI to power research through case examples
- Understand how LLM extraction is applied to clinical notes and improves data quality
- Explore endpoint estimation for critical outcomes such as CDAI, BASDAI, Hurley
- Hear how subtyping is revealing new forms of disease and can identify patients more likely to progress from psoriasis to psoriatic arthritis
Why Attend?
This is a fantastic opportunity to learn more about the treatment landscape in this complex disease. Attendees can participate in a live Q&A session at the end of the presentation or submit questions in advance of the event.
Join us for an informative session that will provide fascinating insights into how RWE can overcome these challenging questions in rheumatology. Register now to secure your spot!
Speakers:
- Chandrasekar “Chandra” Gopalakrishnan, MD
Senior Principal Epidemiologist, OM1 - Carl Marci, MD
Chief Clinical Officer, OM1