Sebra is a machine learning-driven platform designed to streamline clinical trial recruitment, improve patient engagement, and ensure regulatory compliance. By leveraging AI and NLP, Sebra efficiently identifies, qualifies, and recruits patients for clinical trials—especially those with rare diseases.
- David Oleksy – Team Lead | Backend development | Database Administrator/Architect
- Suchi Patel – Design | Wireframe Architect
- Alvin Wang – UI/UX integration | Frontend Development
- 🔍 AI-Powered Patient Matching – Uses NLP to extract eligibility criteria and match patients efficiently.
- 🔐 HIPAA-Compliant Data Security – Secure tokenization ensures patient identity protection.
- 📊 Automated FDA-Ready Documentation – Reduces manual paperwork and accelerates trial processes.
- 📡 Remote Patient Monitoring – Sends automated reminders to enhance retention and reduce dropout rates.
- 📂 NLP for Electronic Medical Records (EMRs) – Extracts insights while ensuring data privacy.
- ⚡ Scalable & Interoperable – Integrates with EHR systems (Epic, Cerner, AthenaHealth) using FHIR.
| Component | Technology |
|---|---|
| Backend | FastAPI |
| Database | PostgreSQL + Firestore |
| Storage | Google Cloud Healthcare API |
| Machine Learning | OpenAI ChatGPT API |
| NLP | OpenAI GPT-4 |
| Security | Tokenized PHI storage in Firestore |
| Task Scheduling | Celery + Redis |
| Authentication | Firebase Auth |
| Deployment | Google Cloud Run |
This project is licensed under the MIT License. See the LICENSE file for details.