tHEORetically speaking: How AI-Powered Phenotyping Enhances the Patient Journey for Life Science Applications

episode

tHEORetically Speaking not yet transcribed

▲ 0

Transcript

This episode hasn't been transcribed yet Upvotes decide what gets transcribed next — 0 so far. Sign in to upvote

More from tHEORetically Speaking

From Data Access to Evidence Usability: Connecting Payer Policy, Real-World Data, and Clinical Context to Close the Evidence Gap 11 min · 13 Jul 2026

All episodes from tHEORetically Speaking →

Report any issue

Source

Recorded25 Apr 2024

Publisherfeeds.buzzsprout.com

Handlerec:11539535

Show notes

In this episode of tHEORetically speaking, Dr. Joseph Zabinksi, VP and Head of Commercial Strategy and AI at OM1, explains how AI-powered digital phenotyping can enhance our understanding of patients' experiences and inform access, treatment, and condition management.Real-world data provides an opportunity to understand what happens to patients, but there are limitations to the insights we can generate using traditional analysis techniques alone. At OM1, our PhenOM technology uses AI to isolate subtle signals in real-world data associated with outcomes we care about - diagnoses, treatment response, and future risks. The insights we derive integrate into our existing patient journeys to answer questions we couldn't without this technology, including who remains undiagnosed or misdiagnosed, and how patient subcohorts take different trajectories within the same broader condition.To learn more, click here.

Ask this episode

“What did the council decide on item 42?” — answered with the speaker and the moment.