Build 'RareMatch'—a $25K/year SaaS platform combining federated genomic data with AI-driven trial matching. The platform would: 1) Deploy secure, federated learning (PySyft) to aggregate genomic data from hospitals (e.g., 'Patient #XYZ: BRCA2 mutation—matching trial found'); 2) Provide a 'Trial Matching Dashboard' showing real-time eligibility (e.g., 'Trial #ABC: 95% match—clinical site within 50 miles'); 3) Integrate with EHR systems (e.g., Epic) and trial networks (e.g., NCI) to auto-enroll patients; 4) Offer a 'Survival Impact Score' showing potential treatment benefits (e.g., 'Projected 2-year survival increase: 15%').

Oncologists lack tools to match rare cancer patients with clinical trials due to fragmented genomic data. Current trial enrollment is slow (6-12 months per patient), and 80% of rare cancer patients miss out on precision therapies.