Individual skill
tooluniverse-pharmacovigilance
Drug safety and adverse event analysis — FAERS spontaneous-report mining, FDA black-box warnings, signal detection (PRR, ROR, IC), risk factors by demographic/comorbidity, label change tracking, and SIDER curated label-derived side-effect frequencies. Use for post-market safety surveillance, AE signal investigation, drug-AE association strength scoring, "what side effects does drug X have" questions, and pharmacovigilance reports.
skills/tooluniverse-pharmacovigilance/SKILL.md
Source commit 5598a9fc97e32964fe9b703818e7d0747142f179
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- Last checked
- Nov 9, 2026
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- 1,779
- Repository last updated
- Nov 8, 2026
- License
- Apache-2.0
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
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CHECKLIST.mddoc · 6,128 bytesEXAMPLES.mddoc · 15,683 bytesREPORT_TEMPLATES.mddoc · 8,302 bytesSIGNAL_ANALYSIS.mddoc · 6,328 bytesSIGNAL_DETECTION.mddoc · 2,950 bytesSKILL.mdcore · 19,467 bytesSKILL.mdcore · 19,467 bytesSKILL.mdcore · 19,467 bytesTOOLS_REFERENCE.mddoc · 15,712 bytes
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## COMPUTE, DON'T DESCRIBE
When analysis requires computation (statistics, data processing, scoring, enrichment), write and run Python code via Bash. Don't describe what you would do — execute it and report actual results. Use ToolUniverse tools to retrieve data, then Python (pandas, scipy, statsmodels, matplotlib) to analyze it.
# Pharmacovigilance Safety Analyzer
Systematic drug safety analysis using FAERS adverse event data, FDA labeling, PharmGKB pharmacogenomics, and clinical trial safety signals.
**KEY PRINCIPLES**:
1. **Report-first approach** - Create report file FIRST, update progressively
2. **Signal quantification** - Use disproportionality measures (PRR, ROR)
3. **Severity stratification** - Prioritize serious/fatal events
4. **Multi-source triangulation** - FAERS, labels, trials, literature
5. **Pharmacogenomic context** - Include genetic risk factors
6. **Actionable output** - Risk-benefit summary with recommendations