Safety & Pharmacovigilance
Safety organizations face a structural challenge: case volumes are growing 8-12% annually, regulatory timelines are compressing, and qualified PV professionals remain scarce. Traditional responses—more headcount, more outsourcing—scale cost linearly with volume. Intelligent automation offers a different path: AI-assisted throughput that preserves medical judgment while breaking the cost-volume curve.
Key Shifts
Watch: AI Agents for Safety & Pharmacovigilance
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Regulatory Context
Regulatory Context
Key regulations, frameworks, and standards that govern this domain.
Use Cases
Explore AI-powered use cases transforming safety & pharmacovigilance operations.
Use Cases
Explore how AI agents transform key processes across maturity levels.
Automated Case Intake
AI extracts AE data from structured and unstructured sources including forms, PDFs, emails, and transcripts.
AI-Assisted Narrative Generation
AI supports triage, routing, and narrative preparation for case processing.
Signal Detection Enhancement
AI augments traditional methods with pattern recognition and real-world data analysis.
Expedited Reporting Intelligence
AI tracks timelines, readiness, and documentation for expedited reporting requirements.
Third-Party & Partner PV Oversight
AI monitors partner compliance, case reconciliation, and performance indicators.
Deep Dive
AI-Assisted Case Processing & Narrative Generation
The target end state is an AI-assisted, medically governed case processing capability that increases throughput while preserving human judgment. This capability is not an autonomous case processor. It is a decision-support system designed to accelerate intake, structure timelines, draft narratives, and flag compliance gaps—while leaving medical review and final approval firmly with qualified PV professionals.
Data Inputs
- Safety database (ICSR records, metadata, status)
- Source documents: CIOMS forms, literature, emails, transcripts
- Controlled vocabularies: MedDRA, WHO-DD
- Reporting rules: country-specific timelines and criteria
- Historical cases: prior narratives, decisions, outcomes
- Partner data: inbound cases from CROs or affiliates
Governance
- Case processors review and refine AI-generated content
- Medical reviewers approve seriousness, causality, narratives
- AI suggestions are transparent and editable
- All edits, approvals, decisions logged for inspection
- Hallucination mitigation: source-grounded generation
- Prompt governance: controlled templates, prohibited content
Expected Outcomes
Quantified improvements organizations can expect when deploying AI agents in this domain.
reduction in narrative drafting time through AI-assisted generation and template reuse
improved case throughput without added headcount, preserving medical judgment
enhanced consistency across case narratives, reducing reviewer variability
reduction in late expedited submissions through proactive tracking and alerts
Human-in-the-Loop Governance
Every AI agent operates under strict governance controls with human oversight at critical decision points.
Governance Gates
Every AI action passes through defined governance checkpoints. Humans remain the ultimate decision-makers at every critical juncture.
Case processors review and refine AI-generated content
Medical reviewers approve seriousness, causality, narratives
AI suggestions are transparent and editable
All edits, approvals, decisions logged for inspection
Hallucination mitigation: source-grounded generation
Prompt governance: controlled templates, prohibited content
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See how AI agents can transform your safety & pharmacovigilance workflows with purpose-built automation and intelligent oversight.