{"id":13706,"date":"2024-03-12T12:42:04","date_gmt":"2024-03-12T12:42:04","guid":{"rendered":"https:\/\/ubc.com\/?post_type=insights&p=13706"},"modified":"2025-05-15T19:46:33","modified_gmt":"2025-05-15T19:46:33","slug":"ubc-participates-in-rare-disease-day-at-nih-2024","status":"publish","type":"insights","link":"https:\/\/ubc.com\/insights\/ubc-participates-in-rare-disease-day-at-nih-2024\/","title":{"rendered":"UBC Participates in Rare Disease Day\u00ae at NIH 2024"},"content":{"rendered":"\n

As part of the global observance of Rare Disease Day the National Center for Advancing Translational Sciences (NCATS) and the NIH Clinical Center sponsored Rare Disease Day at NIH 2024<\/a>. The annual event brought together patients, patient advocates, caregivers, health care providers, researchers, trainees, students, industry representatives, and government staff to raise awareness about rare disease, the people they affect, and NIH collaborations that address scientific challenges and advance research for new treatments. UBC\u2019s Director of Patient and Physician Services, Marita Lynott, had the opportunity to attend the event held on 29 February 2024 in Bethesda, MD and shared her perspective on the impact and value of the content discussed. <\/p>\n\n\n\n

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It was inspiring to be a participant at Rare Disease Day at NIH 2024. The event serves as a beacon of hope, igniting passion and fostering collaboration among researchers, patients, and advocates dedicated to rare disease research. With over 300 million people worldwide living with a rare disease, most of which are children, the need to understand and diagnose these illnesses remains a priority. To date there are over 7,000 identified rare diseases but fewer than 500 have approved treatments.  <\/p>\n\n\n\n

Of all the topics covered throughout the day, the Artificial Intelligence (AI) and Its Potential Role in Rare Diseases session was of particular interest to me. Experts shared how AI can play a role in disease diagnosis, shortening the time to diagnosis, and accelerate paths to treatment. By ensuring input data is AI-ready, it can generate models to:<\/p>\n\n\n\n