Verified:GitHub

scientific-pharmacovigilance

Analyze adverse event data using PRR, ROR, IC, and EBGM metrics.

3|1|Updated Feb 11, 2026

Search Tags:#temporal-analysis #pharmacovigilance #signal detection #faers #demographic-analysis #disproportionality #meddra

Ready to run

npx skills add https://github.com/nahisaho/satori --skill scientific-pharmacovigilance

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: scientific-pharmacovigilance
Source: https://github.com/nahisaho/satori/tree/main/src/.github/skills/scientific-pharmacovigilance
Command: npx skills add https://github.com/nahisaho/satori --skill scientific-pharmacovigilance

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Identify and evaluate post-marketing safety signals from adverse event data to support pharmacovigilance decisions.

Core Features & Use Cases

Data integration and preprocessing of FAERS-like adverse event data using MedDRA mappings to enable consistent signal detection.
Disproportionality analysis and temporal/demographic stratification to reveal safety patterns across drugs and populations.
Safety signal reporting and risk assessment workflows including EBGM, IC, PRR, and ROR calculations with consolidated summaries.

Quick Start

Analyze FAERS data to identify safety signals for a drug by performing PRR, ROR, IC, and EBGM disproportionality analyses and generate a safety signal report.

Frequently Asked Questions about scientific-pharmacovigilance

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I identify post-market safety signals from FAERS adverse event data?▼

To identify post-market safety signals from FAERS adverse event data, you need to perform disproportionality analysis using PRR, ROR, IC, and EBGM calculations. This process evaluates statistical deviations to detect drug-associated risks. Applying MedDRA mappings ensures consistent terminology across your safety signal detection workflow.

What is disproportionality analysis in pharmacovigilance and how does it work?▼

Disproportionality analysis in pharmacovigilance works by calculating metrics such as PRR, ROR, IC, and EBGM to compare observed adverse event frequencies with expected baseline rates. This statistical method detects safety signals by revealing disproportionate drug-event associations within large datasets like FAERS.

How do I stratify pharmacovigilance safety patterns across time and demographics?▼

To stratify pharmacovigilance safety patterns across time and demographics, apply temporal and demographic analysis techniques to your FAERS data. This approach reveals specific safety patterns across different patient populations and timeframes, supporting structured risk assessment workflows.

Does this pharmacovigilance signal detection approach require MedDRA mapping?▼

Yes, MedDRA mapping is required for consistent pharmacovigilance signal detection. Integrating FAERS-like adverse event data with MedDRA hierarchies standardizes medical terminology, which is essential for accurate disproportionality analysis and structured safety signal reporting.

What is the best way to generate structured safety signal reports from adverse event data?▼

The best way to generate structured safety signal reports from adverse event data is to execute consolidated disproportionality analyses using PRR, ROR, IC, and EBGM. This approach integrates temporal and demographic stratification to produce comprehensive risk assessment summaries.