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Gena Health, rare cancer care platform

A safety-first AI foundation for rare cancer care

Gena Health operates a specialised rare cancer care platform serving patients with orphan diseases and complex oncological conditions. Moterra delivered a Rapid AI Assessment for a conversational, evidence-based patient and clinician experience - where medical accuracy, safety and compliance were the non-negotiables.

Client Gena Health Sector Healthcare technology - rare cancer care Scale HIPAA-compliant platform for patients, oncologists and care coordinators Solution AI Consulting - Rapid AI Assessment
What they got
Three models tested On medical reasoning Claude 4 Sonnet, Nova Pro and Nova Lite compared on medical accuracy, clinical reasoning, safety features and patient-communication quality against real rare cancer scenarios.
Working sandbox From day one Conversational patient education, clinical trials matching and care-coordinator decision support prototyped inside Moterra Business AI Suite.
Healthcare-grade RAG HIPAA, safety, clinical trust Amazon Bedrock with OpenSearch vector search, Orphanet and clinical-trials integration, HIPAA-aligned handling, and mandatory clinician oversight on every output.
01

The situation

Gena Health serves patients with rare cancers - a population facing significant barriers accessing specialised medical information, complex treatment protocols and clinical trials. Existing static information delivery falls short of what these patients and their care coordinators actually need: personalised, evidence-based, safe answers, available around the clock, with a clinician always in the loop.

02

What they needed

An evidence-based view with patient safety as the non-negotiable starting point.

Which foundation model actually performs on medical reasoning and rare cancer scenarios?How do we deliver accurate, empathetic conversational experiences while keeping clinicians in control?What does a HIPAA-aligned RAG architecture look like on AWS, integrating Orphanet, clinical trials data and internal knowledge?How do we build in the safety, disclaimers and audit trails that patients, clinicians and regulators expect?
03

What Moterra delivered

A Rapid AI Assessment scoped to Gena Health’s context, with safety treated as a design constraint rather than a review step.

Stakeholder and readiness workEngagement with product, clinical and compliance leaders, plus an organisational AI readiness review.
Use case prioritisationConversational patient education, clinical trials matching, care-pathway guidance and clinician decision support.
Comparative model benchmarkingOn medical reasoning tasks, with particular attention to accuracy, safety features, uncertainty expression and communication quality.
Data readiness reviewAcross Orphanet, clinical trials repositories, genomic resources and internal patient education content.
Healthcare-grade RAG architectureAmazon Bedrock, OpenSearch vector search, HIPAA-aligned data handling and audit-trail compliance on AWS.
Risk matrix with human-in-the-loopClinical safety, model hallucination, regulatory adherence and clinician adoption - with mandatory clinician review across every use case.

Throughout the engagement, Gena Health had access to Moterra Business AI Suite as a working sandbox, used to prototype and validate the core use cases against representative clinical data.

04

The outcome

Gena Health’s leadership got a safety-first AI plan - model choice grounded in medical accuracy and safety, a HIPAA-aligned RAG architecture, a phased path to production, and a governance model built on clinician oversight - the kind of foundation patients, oncologists and regulators expect for rare cancer care.

Uncertainty as a feature

In most sectors, a model expressing uncertainty is a weakness. In rare cancer care it is a safety requirement - which is why it was a benchmark criterion, not a footnote.

Next step

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