How to Drive Earlier Diagnosis in Rare Disease with AI


Rare diseases contribute a significant burden of illness due to the challenges associated with diagnosis. For the ~8,000 adult-onset or age-neutral rare diseases, patients can wait years between symptom onset and diagnosis leading to disease progression and poor outcomes. Biopharma companies struggle to efficiently engage and educate providers on rare diseases because most providers will see less than a handful of patients with a given rare disease over the course of decades of practice. Powered by large, provider identified clinical encounter data sets, machine learning models can now be used to compliantly “identify” providers who are managing patients with undiagnosed rare diseases.


  • Aswin Chandrakantan, M.D., Head of Product, Chief Medical Officer, Komodo Health
  • Neeraja Krishnaswamy-Bhagavatula, Alnylam

Sponsored by:

Komodo Health

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