The Big Question  

What if we could end the rare disease diagnostic odyssey?

The Problem  

Collectively, rare diseases are far from rare — more than 10,000 unique conditions affect over 350 million people worldwide, including one in ten Americans. The lengthy diagnostic “odyssey” endured by patients with a rare disease lasts six years on average but can extend for decades. Diagnostic delays stem from multiple factors, including overlapping symptoms, low disease incidence, and limited specialist expertise. It's estimated that half of all individuals with a rare disease remain undiagnosed or misdiagnosed, leading to inappropriate care, irreversible disease progression, and rising medical costs.  

The Solution 

The Rare Disease AI/ML for Precision Integrated Diagnostics (RAPID) program aims to transform the diagnosis of rare and ultra-rare diseases by developing highly accurate AI-based detection models. RAPID seeks to develop provider-facing tools that prioritize data interoperability and integration into existing clinical workflows, ensuring scalability across health care organizations. RAPID will also design cost effective, direct-to-patient systems that can be remotely deployed to help individuals and their families detect rare diseases at home or in non-clinical settings and route them toward appropriate medical support. To catalyze model development, RAPID aims to integrate data from a fragmented landscape, building the largest curated dataset of longitudinal rare disease patient data that is optimized for training and benchmarking advanced diagnostic algorithms. If successful, RAPID will expand access to rare disease expertise and help patients and health care providers reach an accurate diagnosis in a fraction of the time it takes today.  

Why ARPA-H 

RAPID leverages ARPA-H's ability to catalyze innovation in underserved areas like rare disease diagnosis.