Clinical Trial Adverse Event Analysis & Safety Reporting
Extract, classify, and report clinical trial adverse events with regulatory compliance
What You Can Do
You can systematically extract adverse events from unstructured clinical trial data, automatically classify them by severity and causality, and generate regulatory-compliant safety reports. The skill validates data quality, identifies safety signals, and maintains complete audit trails for FDA/EMA submissions. It accelerates the safety surveillance process while ensuring no critical events are missed.
Features
Identifies adverse events from narrative case reports, lab results, and clinical notes with high recall and precision using medical terminology recognition.
Applies standardized algorithms to classify events by severity (mild/moderate/severe/life-threatening), seriousness, and relatedness to study drug using regulatory guidelines.
Ensures all extracted data meets FDA, EMA, and ICH-GCP requirements with built-in checks for completeness, consistency, and reportability criteria.
Produces formatted safety reports compatible with regulatory submissions including narrative summaries, tables, and MedDRA coding recommendations.
Identifies emerging safety patterns, unusual event clusters, and temporal trends that may indicate new safety risks requiring escalation.
Flags missing data, inconsistencies, and incomplete case narratives that require follow-up, with severity prioritization for data managers.
Documents all extraction decisions, classifications, and modifications with timestamps and rationales for regulatory inspections and audits.
Example Output
Example 1: Extracted Event Classification
{
"eventId": "AE-2026-0847",
"patient": "Trial-0042",
"description": "Elevated liver transaminases detected on study day 45",
"meddraCode": "10047349",
"severity": "MODERATE",
"seriousness": true,
"relatedness": "POSSIBLE",
"action": "DOSE_REDUCTION",
"outcome": "RECOVERING",
"reportingFlag": "EXPEDITED_10_DAY",
"confidenceScore": 0.94
}
Example 2: Safety Report Summary
| MedDRA Preferred Term | N Events | Serious | Related | Grade 3-4 |
|---|---|---|---|---|
| Elevated Transaminases | 8 | 3 | 6 | 2 |
| Headache | 24 | 0 | 12 | 0 |
| Nausea | 19 | 0 | 14 | 1 |
| Rash | 5 | 0 | 4 | 0 |
Example 3: Signal Detection Alert
- ⚠️ Emerging Signal — Elevated liver enzymes + rash combination: 2 cases (1.3% incidence vs 0.2% background). Safety Committee notification required within 24 hours.
What's Included
- Event Extraction Engine: Medical NLP model trained on clinical trial narratives to identify adverse events from text, with MedDRA coding suggestions.
- Classification Framework: Regulatory-aligned decision trees for severity assessment, seriousness evaluation, and causality attribution using ICH-GCP standards.
- Report Templates: Pre-formatted safety report templates for FDA Form 1639, EMA REC, and IND safety reports with automatic data population.
- Quality Assurance Module: Automated validation checks for data completeness, consistency, and compliance with regulatory requirements and protocol specifications.
- Audit Logging System: Complete change history tracking all extractions, classifications, and modifications with user attribution and timestamps for regulatory compliance.
Who It's For
- Clinical Trial Safety Officers
- Pharmacovigilance Specialists
- Regulatory Affairs Managers
- Medical Monitors
- Clinical Research Coordinators
Best For
- Safety surveillance during active clinical trials
- FDA/EMA regulatory safety submissions
- Adverse event case reconciliation and quality control
- Safety signal detection and trend analysis
- Expedited safety reporting preparation
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