AI-driven platform matching patients to clinical trials using anonymized medical records. Features blockchain verification, automated screening, and recruitment analytics. Targets pharma companies and research hospitals with SaaS monetization.
MediMatch AI tackles the $6B clinical trial recruitment bottleneck through AI analysis of anonymized medical records. The platform accelerates patient matching by 60% while ensuring GDPR/HIPAA compliance via blockchain verification. Targeting pharmaceutical giants and research hospitals, this solution transforms how trials recruit participants in the rapidly growing $44B clinical trials market.
Core functionality
AI-powered analysis of anonymized electronic medical records (EMR) to identify clinical trial candidates. Blockchain verifies data integrity while preserving privacy. Platform includes:
- Automated eligibility screening algorithms
- Patient consent management system
- Researcher dashboards with real-time analytics
- Recruitment performance tracking
- Secure data exchange protocols
Target user and segment
Primary clients:
- Pharmaceutical companies (large-cap and biotechs)
- Clinical research organizations (CROs)
- Research hospitals and academic institutions
Secondary users: Oncology/neurology specialists seeking trial options for patients with complex conditions.
Recommended tech stack
- Frontend: React.js + Redux
- Backend: Node.js/Python microservices
- AI Engine: TensorFlow/PyTorch NLP models
- Database: PostgreSQL + MongoDB
- Blockchain: Hyperledger Fabric framework
- Infrastructure: AWS HIPAA-compliant servers
- Security: Zero-knowledge proofs for anonymization
Estimated MVP hours and costs
Development breakdown:
- Backend: 600h (€60,000)
- AI engine: 500h (€50,000)
- Blockchain: 300h (€30,000)
- UI/UX: 300h (€30,000)
- Compliance: 150h (€15,000)
Total MVP cost: €185,000 at €100/hour
Monthly operations: €8,500 for cloud/AI maintenance
SWOT-analysis
Strengths: Solves critical recruitment bottleneck, 60% faster matching, blockchain trust layer
Weaknesses: Regulatory complexity (HIPAA/GDPR), data acquisition challenges
Opportunities: $44B market growing at 5.8% CAGR, rare disease trial specialization
Threats: Incumbents (Medable, Science37) expanding matching capabilities
First 1000 customers strategy
- Enterprise sales to top 20 pharma (CAC: €15k/client)
- Conference partnerships at DIA Global/BIO International
- Co-marketing with CROs (IQVIA, Parexel)
- Physician referral program (€200/successful match)
Target: 40% conversion from free matching tier
Acquisition budget: €300k first year
Monetization
SaaS Model:
- Basic tier: €15k/trial (≤500 matches)
- Premium: €50k/trial (AI analytics + blockchain audit)
Break-even: 18 enterprise clients/year
Core team: 8 FTEs (2 AI engineers, 3 devs, compliance, sales, CEO)
Projected Y3 revenue: €4.2M
Market positioning and competitors
Primary markets: North America (€11.2B), EU5 (€7.8B)
Direct competitors: Deep6 AI (US), TrialHub (EU)
Differentiation: GDPR-compliant blockchain verification
Sales strategy: Enterprise sales + CRO partnerships
Micro-niche focus: Rare disease trials (€1.2B submarket)
