Build a Consumer AI Cancer Treatment-Matching Platform

1. 1

   Build the diagnosis-to-options matching engine

   The core is an AI that takes a patient's diagnosis and characteristics and instantly maps them to available advanced therapies and open clinical trials, producing a personalized options list. As context, Leal Health has generated millions of treatment matches with this approach. Accurate, up-to-date matching against therapies and trial eligibility is the product's foundation.

2. 2

   Keep the options list bias-free

   The value to patients is a neutral, pharma-bias-free list of options rather than a promotion of any sponsor's product, so guarding neutrality is central to trust. Design the matching and any funding relationships so they do not skew recommendations. Perceived bias would destroy the platform's credibility.

3. 3

   Staff clinical follow-up

   A consumer platform in oncology cannot be pure software; patients need clinical personnel (nurses, navigators) to help interpret options and next steps. This human support is part of the offering and a real operating cost. It also raises the standard of care and trust the platform must meet.

4. 4

   Choose a funding model carefully

   These platforms are often funded by pharma partnerships, clinical-trial sponsors, or services fees rather than charging patients, and each source carries potential bias concerns. Pick a model that keeps the patient's interest primary and is transparent. Funding design is an ethical as well as a commercial decision.

5. 5

   Earn patient trust and privacy compliance

   Handling diagnosis and health data means HIPAA and privacy obligations, and consumer trust depends on clear data practices and genuine neutrality. Build privacy and consent in from the start. Trust is the platform's real moat with patients.

6. 6

   Address the trial-enrollment gap

   By surfacing open trials to patients, the platform helps address the reality that only 5 to 7 percent of adult cancer patients enroll in trials, connecting demand to capacity. This links to a broader opportunity captured in the trial-matching and enrollment-bottleneck cards. Position the platform within that larger system.

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Best for: Patient-facing health-tech founders and clinical-navigation teams

Not for: Anyone willing to let a funding model compromise neutrality, and anyone who wants a pure software play without clinical follow-up. Trust and human support are the product. Nothing here is medical advice.