Compliance Persona: Head of Pharmacovigilance Operations Autonomy: Assist · System drafts, human drives

Pharmacovigilance Case Intake

Pharmacovigilance AI for case intake reads incoming adverse event reports from mailboxes, scanned forms, partner files and literature, extracts reporter, patient, product and reaction details into structured fields, flags reports missing a validity criterion and lists possible duplicates. Case processors confirm every field, and qualified safety staff assess seriousness, expectedness and causality. The agent never submits ICSRs and never makes a medical judgement.

At a glance

Trigger: A message, document or publication that may describe a suspected adverse reaction reaches a safety intake channel. Owner: Head of Pharmacovigilance Operations. Primary output: Pre-filled case draft with source citations for every field. Consequential actions require approval.

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PharmaceuticalBiotechLife Sciences

By VDF AI Editorial Team · Last reviewed 6 October 2026

The Challenge

Why Intake Volume Puts Reporting Clocks at Risk

Case volumes grow with every new market, partner and literature source, yet each report still needs careful reading, and the regulatory clock starts on the day any employee or contractor learns of a valid case.

How VDF AI Handles It

Pre-Filled Case Drafts, Human Verification

VDF AI agents triage the intake queue, extract case details with citations to the source text, mask personal data where it is not needed and hand case processors a pre-filled draft with a validity checklist to verify.

Agent Workflow

How the Agent Network Works

  1. 01

    Triage Agent

    Sorts incoming mail, scanned forms and partner files into potential adverse event reports, product complaints, medical enquiries and unrelated messages.

  2. 02

    Extraction Agent

    Pulls reporter, patient, product, reaction and timing details into structured fields and links each value to the sentence it came from.

  3. 03

    Validity Agent

    Checks the four minimum criteria for a valid case and lists missing items so a processor can request follow-up.

  4. 04

    Duplicate Agent

    Compares each new report with existing cases on patient descriptors, product, reaction and dates, and lists candidates for a person to confirm.

  5. 05

    Privacy Agent

    Detects personal identifiers and masks them in copies used for analytics, training material or literature summaries.

Data and evidence

What Pharmacovigilance Case Intake Needs to Operate

Each pharmacovigilance case intake source has a defined purpose, freshness expectation, quality gate, and sensitivity boundary.

Intake channels such as safety mailboxes, web forms, call notes and partner files

Purpose: Give the agents every report that could start a submission clock.

Freshness: Polled continuously so day zero is never lost to an unread inbox.

Quality: Each item keeps its receipt timestamp, channel and original attachment.

Sensitivity: Treat all items as health data and limit access to the safety team.

Literature search outputs and licensed full-text articles

Purpose: Identify publications that describe a suspected reaction to a company product.

Freshness: Run at least weekly, in line with the search strategy in your procedures.

Quality: Store the search string, database, date and article identifier with every hit.

Sensitivity: Respect publisher licence terms when storing or sharing full texts.

Existing case records exported from the safety database

Purpose: Support duplicate checks and show processors related prior reports.

Freshness: Refreshed daily from the system of record.

Quality: Case identifiers and version numbers must match the safety database exactly.

Sensitivity: Export only the fields needed for duplicate detection.

Measurement plan

How to Evaluate Pharmacovigilance Case Intake

Primary measure: Valid reports reaching a processor within one business day of receipt. For one month before the pilot, record receipt-to-triage time, data entry effort per case and duplicates found after entry, by intake channel.
Illustrative model Value hypothesis and full cost
Illustrative: monthly report volume × processor minutes saved per case × loaded cost, plus reduced late-submission exposure, minus validation, review, model and infrastructure costs.

Cost inputs to include

  • Computerised system validation under your quality procedures
  • Processor time spent verifying drafts
  • Model capacity for multilingual documents
  • Integration with mailboxes and safety database exports
Validation Supporting measures and review cadence

Sample drafts weekly during the pilot and monthly after go-live, and repeat validation testing after any model or prompt change.

  • Fields accepted without correction per case draft
  • Confirmed duplicates found before data entry
Decision guide

Pharmacovigilance Case Intake: Operating Model and Implementation

When Pharmacovigilance Case Intake is appropriate

Intake is the part of drug safety where volume and deadlines collide. Under EMA’s GVP Module VI, a valid case needs an identifiable reporter, one identifiable patient, a suspected product and a suspected reaction. Serious cases go to EudraVigilance within 15 days and non-serious ones within 90, counted from day zero. In the US, 21 CFR 314.80 requires 15-day Alert reports for serious and unexpected experiences, review of information from any source including the scientific literature, and ten years of record retention.

The workflow suits teams with steady report volume, several intake channels and a quality system that can validate a new tool. It is a poor fit when report volume is tiny or when the expectation is that software will replace safety physicians.

Designing the operating workflow

  1. Capture. Every message and file is logged with its receipt time, because that time can become day zero.
  2. Triage. The agent labels items as potential adverse events, complaints or enquiries; a person reviews anything closed as not relevant.
  3. Extract. Case fields are pre-filled, each linked to its source sentence, with foreign-language reports translated alongside the original.
  4. Validate. The four minimum criteria are checked and gaps become follow-up requests.
  5. Check duplicates. Candidates are listed for a processor to confirm or reject, following the duplicate management addendum to GVP Module VI.
  6. Hand over. The processor enters the verified case in the safety database, and qualified staff complete the medical assessment.

Data, integration, and evidence

Intake stepAgent outputHuman decision
TriageCategory with the deciding passageClose or keep each item
ExtractionCited field valuesAccept or correct every field
ValidityMissing-criteria checklistValidity and follow-up
DuplicatesRanked candidate casesMerge, link or keep separate

For follow-up reports, a diff of the new and previous versions shows processors exactly what changed. On the submission side, the FDA electronic submissions page states that ICSRs sent through ESG NextGen must use E2B(R3) from 1 October 2026 (verified October 2026). That work stays in the safety database.

How VDF.AI supports this use case

VDF AI Agents run on-premises, in a private cloud or air-gapped, so case documents stay in your environment. Agents can combine catalog tools for OCR, translation and table extraction with PII detection and PII redaction for copies that leave the case record.

VDF holds no GxP or regulatory certification of its own. It is software that runs under your quality system, so validation, access control and SOPs remain yours.

More healthcare workflows are in the healthcare use cases, including literature review support, regulatory knowledge chat for pharma and coding validation.

Risk and control register

Controls Required for Pharmacovigilance Case Intake

A report is misrouted as a medical enquiry and its clock runs out unnoticed.

Control: Processors review every item the agent labels as not an adverse event before it is closed.

Accountable owner: Intake team lead

An extracted field misstates a dose, date or reaction term.

Control: Every field links to its source sentence, and processors confirm fields before data entry.

Accountable owner: Case processing lead

Personal data flows into analytics or prompts beyond what case processing requires.

Control: Detect and mask identifiers outside the case record, and run agents only inside your environment.

Accountable owner: Data protection officer

Where this workflow should not operate

  • It does not assess seriousness, expectedness, causality or signals.
  • It does not submit ICSRs or replace the validated safety database.
  • Handwritten or low-quality scans may need full manual transcription.
Controlled rollout

Pilot and Scale Criteria

Pilot on one market's spontaneous reports in parallel with normal processing, so every case is still entered and assessed by the existing team.

Prerequisites

  • Define intended use and validation scope under your computerised system procedures.
  • Connect one intake mailbox and a read-only export of existing cases.

Approval gates

  • The QPPV or delegate approves the intended use and the parallel-run results.
  • Quality assurance signs off validation evidence before the agent touches live intake.

Scale criteria

  • No valid report is missed or delayed by the agent across the parallel run.
  • Processors accept most extracted fields without correction.
Evidence

Authoritative Sources and Implementation References

These sources inform the governance and evaluation approach for Pharmacovigilance Case Intake. They do not certify a specific deployment.

  1. Guideline on good pharmacovigilance practices (GVP) Module VI: Collection, management and submission of reports of suspected adverse reactions to medicinal products (Rev 2) — European Medicines Agency, 2017
  2. 21 CFR 314.80: Postmarketing reporting of adverse drug experiences — Legal Information Institute, Cornell Law School
  3. FDA Adverse Event Monitoring System (AEMS) Electronic Submissions — U.S. Food and Drug Administration

Written by VDF AI Editorial Team. Last reviewed 6 October 2026.

FAQ

Frequently Asked Questions

Answers for Head of Pharmacovigilance Operations evaluating this workflow's data, controls, measures, and operating boundaries.

Talk to an expert
01 Can AI decide whether an adverse event is serious or caused by the drug?

It should not. Seriousness, expectedness and causality are medical judgements that belong to qualified safety staff. The agent's job is to put the relevant facts in front of them quickly: the reaction as reported, onset timing, dechallenge information and any hospitalisation, each linked to the exact sentence in the source.

02 Does a pharmacovigilance AI agent submit ICSRs to regulators?

No. Submission stays in your validated safety database and its gateway connections. The agent prepares a draft that a processor verifies before data entry. That matters more now that FDA requires E2B(R3) for postmarketing ICSRs sent through ESG NextGen from 1 October 2026 (verified October 2026), because format errors are caught at the gateway, not by the agent.

03 How does AI help with literature screening for drug safety?

EU guidance expects at least weekly searches of major reference databases, and the reporting clock for a literature case starts when the company becomes aware of a publication that meets the minimum criteria. An agent can screen new abstracts and full texts, flag articles that mention a company product with an identifiable patient and reaction, and queue them for a reviewer the same day.

04 How is patient privacy protected during AI-assisted case intake?

Run the agents inside your own environment so source documents never reach a public model service. Keep the identifiers a valid case needs, such as initials or age, in the case draft, and mask names, addresses and contact details in every copy used for analytics, training or management reporting.

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