A recent report from the health research network and real-world data platform TriNetX argues that by aggregating electronic health records, billing claims, and registry data across hundreds of healthcare sites makes it possible to study rare diseases more efficiently. Doing so could enable access to enough patient data to conduct meaningful research, which is often impossible through traditional clinical trials. We spoke to Jeff Brown, chief scientific officer of TriNetX, about how real-world data can address common challenges in rare disease research, the hurdles that need to be addressed, and how advances in AI could revolutionize rare disease research by using this data to identify patients and unlock insights.