EP 194: Ontologies, diagnostics, and genomics for all with Melissa Haendel of UNC Chapel Hill

Summary: 

This week on The Genetics Podcast, Patrick is joined by Melissa Haendel, Director of Translational Informatics and Precision Health and Professor at the University of North Carolina at Chapel Hill, and Phenotypic Lead at Alamya Health. They discuss the limitations of electronic health records for rare disease diagnostics, how patient self-reporting can enhance diagnosis, expanding access to genomic testing in underserved settings, and the challenges and promise of national-scale health data infrastructure. 

Show Notes: 

0:00 Intro to The Genetics Podcast

00:59 Welcome to Melissa

02:05 Melissa’s career path, beginning with finding her first professorship on Craigslist

04:24 The fundamentals of ontology and how it can help identify common molecular mechanisms across different rare diseases

06:29 Why key rare disease details are missing from electronic health records (EHRs) and how ontologies and AI can help

11:33 How patient self-reporting using layperson phenotypic terms was associated with strong diagnostic performance

15:27 Why recognizing multi-system patterns is key for diagnosing rare conditions and how tools like pattern-based screening are improving outcomes

17:41 How Alamya Health is expanding access to genomic diagnostics by building local lab infrastructure in underserved communities

22:03 How Alamya’s single-test, AI-powered approach helps solve complex cases in underserved settings

24:18 Rethinking the true cost of delayed diagnosis, from wasted testing to the societal and family burden

26:10 What it takes to do national-scale health data research in the U.S. and a vision of real-world data as a public utility

33:37 Opening up access to national EHR data for research through health data networks

36:15 The gap between real-world data and clinical research and why improving data quality benefits both care and science

38:34 A major upcoming milestone in bringing unified rare disease codes into US healthcare with the Mondo ontology

41:22 Closing remarks 

Find out more

• TIS Lab (https://tislab.org/), Alamya Health (https://www.alamyahealth.com/)

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