Data & ReproDrug Discovery & CheminformaticsFreedomIntelligence/OpenClaw-Medical-SkillsData & Reproduction
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tooluniverse-adverse-event-detection

Maintainer FreedomIntelligence · Last updated April 1, 2026

Detect and analyze adverse drug event signals using FDA FAERS data, drug labels, disproportionality analysis (PRR, ROR, IC), and biomedical evidence. Generates quantitative safety signal scores (0-100) with evidence grading. Use for post-market surveillance, pharmacovigilance, drug safety assessment, adverse event investigation, and regulatory decision support.

OpenClawNanoClawAnalysisReproductiontooluniverse-adverse-event-detection🏥 medical & clinicaldrug safety & chemical biologydetect

Original source

FreedomIntelligence/OpenClaw-Medical-Skills

https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/tooluniverse-adverse-event-detection

Maintainer
FreedomIntelligence
License
MIT
Last updated
April 1, 2026

Skill Snapshot

Key Details From SKILL.md

2 min

Key Notes

  • 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: 1. Signal quantification first - Every adverse event must have PRR/ROR/IC with confidence intervals 2. Serious events priority - Deaths, hospitalizations, life-threatening events always analyzed first 3. Multi-source triangulation - FAERS + FDA labels + OpenTargets + DrugBank + literature 4. Context-aware assessment - Distinguish drug-specific vs class-wide vs confounding signals 5. Report-first approach - Create report file FIRST, update progressively 6. Evidence grading mandatory - T1 (regulatory/boxed warning) through T4 (computational) 7. English-first queries - Always use English drug names in tool calls, respond in user's language.
  • chembl_result = tu.tools.OpenTargets_get_drug_chembId_by_generic_name(drugName="atorvastatin").

Source Doc

Excerpt From SKILL.md

When to Use

Apply when user asks:

  • "What are the safety signals for [drug]?"
  • "Detect adverse events for [drug]"
  • "Is [drug] associated with [adverse event]?"
  • "What are the FAERS signals for [drug]?"
  • "Compare safety of [drug A] vs [drug B] for [adverse event]"
  • "What are the serious adverse events for [drug]?"
  • "Are there emerging safety signals for [drug]?"
  • "Post-market surveillance report for [drug]"
  • "Pharmacovigilance signal detection for [drug]"
  • "What is the disproportionality analysis for [drug] and [event]?"

Differentiation from tooluniverse-pharmacovigilance: This skill focuses specifically on signal detection and quantification using disproportionality analysis (PRR, ROR, IC) with statistical rigor, produces a quantitative Safety Signal Score (0-100), and performs comparative safety analysis across drug classes. The pharmacovigilance skill provides broader safety profiling without the same depth of signal detection metrics.


Response: {data: {search: {hits: [{id: "CHEMBL1487", name: "ATORVASTATIN", description: "..."}]}}}

chembl_id = chembl_result['data']['search']['hits'][0]['id'] # "CHEMBL1487"

Step 2: Get drug mechanism of action

moa = tu.tools.OpenTargets_get_drug_mechanisms_of_action_by_chemblId(chemblId=chembl_id)

Use cases

  • Use for post-market surveillance, pharmacovigilance, drug safety assessment, adverse event investigation, and regulatory decision support.

Not for

  • Do not rely on this catalog entry alone for installation or maintenance details.

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