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马国锦
马国锦

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AE Sentinel – AI-powered adverse event monitoring for clinical trials

 I just open-sourced AE Sentinel, an AI-powered pharmacovigilance platform that automates adverse event monitoring in clinical trials.

🔗 GitHub: https://github.com/mgj10086/AEPD-Sentinel


What it does

Module Description
🏷️ AE Coding Auto MedDRA coding with keyword-based synonym matching
📋 SAE Reports CIOMS-I report generation (PDF/DOCX/JSON)
⚠️ Deviation Detection 7 built-in rules, auto-triggered from AE processing
📊 Signal Mining Organ-class aggregation, Fisher's exact test simulation
✅ Compliance GCP compliance auditing
📚 Knowledge Base RAG-powered semantic search (ChromaDB)
🔐 Audit Trail HMAC hash chain, tamper-evident
🔔 Notifications Real-time alerts for deviations/SAEs

Tech Stack

  • Backend: Python 3.9+ / FastAPI / Uvicorn
  • Frontend: Vue 3 / Pinia / Element Plus / ECharts
  • Database: MySQL (production) / SQLite (dev) — auto-switch via env
  • Vector DB: ChromaDB (persistent, semantic search)
  • Auth: JWT (HS256) + role-based access (Admin / PV Specialist / CRA)
  • Container: Multi-stage Docker build (Node → Python + Nginx)

Architecture

Three-layer separation:

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