OpalMedica, a Manchester-based medical technology startup, has announced research presented at the European Conference on Rare Diseases (ECRD) 2026 highlighting the potential for machine learning to support earlier identification of rare and underdiagnosed diseases in primary care.
The research explored the use of automated machine learning approaches to identify patterns associated with rare diseases from routine healthcare data, with the aim of helping clinicians recognise when further investigation may be warranted.
Earlier identification remains one of the greatest challenges facing people living with rare diseases, with many patients experiencing years of appointments, referrals and misdiagnoses before receiving an explanation for their symptoms.
OpalMedica is developing Clinical Flags, a patent-pending clinical decision support tool designed to analyse coded and free-text patient records during routine consultations and alert clinicians when symptom patterns may suggest an underlying rare condition.
The company is currently progressing plans for NHS validation studies and welcomes discussions with healthcare organisations, researchers, patient organisations and industry partners interested in collaborating on future research and implementation initiatives.
Founder and CEO Sara Elgott said:
"Every rare disease patient has a story of missed opportunities before diagnosis. We believe technology can help clinicians identify those patients earlier and ensure they are directed to the right investigations and specialist care sooner."
For collaboration enquiries, please contact [sara@opalmedica.co.uk](mailto:sara@opalmedica.co.uk).
