Name: Adverse Drug Event Signal Detection & Analysis
Author: FreedomIntelligence

Adverse Drug Event Signal Detection & Analysis

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.

FreedomIntelligence2,097 estrellas8 mar 2026

Ocupación
Categorías: Química Computacional

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:

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:

Strength	PRR	ROR Lower CI	IC Lower CI	Clinical Action
Strong	>= 5.0	>= 3.0	>= 2.0	Immediate investigation required
Moderate	3.0-4.9	2.0-2.9	1.0-1.9	Active monitoring recommended
Weak	2.0-2.9	1.0-1.9	0-0.9	Routine monitoring, watch for trends
No signal	< 2.0	< 1.0	< 0	Standard pharmacovigilance

Adverse Drug Event Signal Detection & Analysis

When to Use

Adverse Drug Event Signal Detection & Analysis

When to Use

Workflow Overview

Phase 0: Input Parsing & Drug Disambiguation

0.1 Resolve Drug Identity

0.2 Output for Report

Phase 1: FAERS Adverse Event Profiling

1.1 Query FAERS for Adverse Events

1.2 Get Serious Events Breakdown

1.3 MedDRA Hierarchy Rollup

1.4 Output for Report

Phase 2: Disproportionality Analysis (Signal Detection)

2.1 Calculate Signal Metrics

2.2 Signal Detection Criteria

2.3 Signal Strength Classification

2.4 Demographic Stratification of Key Signals

2.5 Output for Report

Phase 3: FDA Label Safety Information

3.1 Extract Label Sections

3.2 Handling No Results

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