tooluniverse-adverse-event-detection
Adverse Drug Event Signal Detection & Analysis
Automated pipeline for detecting, quantifying, and contextualizing adverse drug event signals using FAERS disproportionality analysis, FDA label mining, mechanism-based prediction, and literature evidence. Produces a quantitative Safety Signal Score (0-100) for regulatory and clinical decision-making.
KEY PRINCIPLES:
- Signal quantification first - Every adverse event must have PRR/ROR/IC with confidence intervals
- Serious events priority - Deaths, hospitalizations, life-threatening events always analyzed first
- Multi-source triangulation - FAERS + FDA labels + OpenTargets + DrugBank + literature
- Context-aware assessment - Distinguish drug-specific vs class-wide vs confounding signals
- Report-first approach - Create report file FIRST, update progressively
- Evidence grading mandatory - T1 (regulatory/boxed warning) through T4 (computational)
- English-first queries - Always use English drug names in tool calls, respond in user's language
When to Use
Apply when user asks:
- "What are the safety signals for [drug]?"
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