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
Reference files
(in this directory):
PHASE_DETAILS.md
- Detailed tool calls, code examples, and output templates per phase
REPORT_TEMPLATE.md
- Full report template and completeness checklist
TOOL_REFERENCE.md
- Tool parameter reference and fallback chains
QUICK_START.md
- Quick examples and common drug names
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]"
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.
Workflow Overview
Phase 0: Input Parsing & Drug Disambiguation
Parse drug name, resolve to ChEMBL ID, DrugBank ID
Identify drug class, mechanism, and approved indications
Query FAERS for top adverse events, seriousness distribution, outcomes, demographics, and death-related events. Filter serious events by type (death, hospitalization, life-threatening). Get MedDRA hierarchy rollup.
. Aggregate class AEs. Identify class-wide vs drug-specific signals.
Tools
:
FAERS_compare_drugs
,
FAERS_count_additive_adverse_reactions
,
FAERS_count_additive_seriousness_classification
Phase 6: Drug-Drug Interactions & Risk Factors
Extract DDIs from FDA label, DrugBank, and DailyMed. Query PharmGKB for pharmacogenomic risk factors and dosing guidelines. Check FDA PGx biomarkers.
Tools
:
FDA_get_drug_interactions_by_drug_name
,
drugbank_get_drug_interactions_by_drug_name_or_id
,
DailyMed_parse_drug_interactions
,
PharmGKB_search_drugs
,
PharmGKB_get_drug_details
,
PharmGKB_get_dosing_guidelines
,
fda_pharmacogenomic_biomarkers
Phase 7: Literature Evidence
Search PubMed, OpenAlex, and EuropePMC for safety studies, case reports, and preprints.
Tools
:
PubMed_search_articles
,
openalex_search_works
,
EuropePMC_search_articles
Phase 8: Risk Assessment & Safety Signal Score
Calculate Safety Signal Score (0-100) from four components: FAERS signal strength (0-35), serious AEs (0-30), FDA label warnings (0-25), literature evidence (0-10). Grade each signal T1-T4. See
PHASE_DETAILS.md
for scoring rubric.
Phase 9: Report Synthesis
Generate comprehensive markdown report with executive summary, all phase outputs, monitoring recommendations, risk mitigation strategies, patient counseling points, and completeness checklist. See
REPORT_TEMPLATE.md
for full template.
Common Analysis Patterns
Pattern
Description
Phases
Full Safety Profile
Comprehensive report for regulatory/safety reviews
All (0-9)
Specific AE Investigation
"Does [drug] cause [event]?"
0, 2, 3, 7
Drug Class Comparison
Compare 3-5 drugs for specific AE
0, 2, 5
Emerging Signal Detection
Screen for signals not in FDA label
1, 2, 3, 7
PGx Risk Assessment
Genetic risk factors for AEs
0, 6
Pre-Approval Assessment
New drugs with limited FAERS data
4, 7
Edge Cases
No FAERS reports
Skip Phases 1-2; rely on FDA label, mechanism predictions, literature
Generic vs Brand name
Try both in FAERS; use
OpenTargets_get_drug_chembId_by_generic_name
to resolve
Drug combinations
Use
FAERS_count_additive_adverse_reactions
for aggregate class analysis
Confounding by indication
Compare AE profile to the disease being treated; note limitation in report