Pharmacovigilance With AI: Signal Detection Beyond the FAERS Spreadsheet
- 0:00 Why Spreadsheets Plateau Early
- 8:00 Where AI Actually Fits
- 18:00 Methods Behind Modern Detection
Practical shifts you can apply this week
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Identify the signal detection tasks where AI adds value beyond spreadsheet-based
See which PV tasks benefit from AI first, and where manual review still earns its keep.
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Compare disproportionality, machine learning, and large language model approache
Choose methods by use case, not buzzwords, with clearer tradeoffs across speed, fit, and validation.
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Evaluate AI outputs for bias, drift, explainability, and regulatory defensibilit
Pressure-test model results before they shape signal triage, escalation, or inspection conversations.
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Design a human-in-the-loop workflow for AI-assisted signal triage and escalation
Map who reviews what, when humans intervene, and how evidence moves from score to decision.
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Draft a practical pilot plan with data, metrics, controls, and stakeholder owner
Leave with a narrow 90-day pilot frame your safety, QA, and data teams can actually run.
What we'll cover
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0:00
Why Spreadsheets Plateau Early
Where manual review breaks first: volume, fragmentation, reviewer variability, and late prioritisation.
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8:00
Where AI Actually Fits
A task map from intake to escalation, with clear boundaries between ranking support and human judgment.
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18:00
Methods Behind Modern Detection
Disproportionality, supervised models, NLP, and LLMs, plus where each helps and where it does not.
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30:00
Signals Need More Than Scores
Why model outputs need clinical context, data quality checks, and a defensible review path.
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40:00
Governance That Survives Audit
Validation, versioning, change control, and documentation that stays legible under inspection.
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47:00
Failure Modes You Will Meet
Bad labels, drift, leakage, and automation bias. Less sci-fi, more Tuesday afternoon.
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54:00
Blueprint For A First Pilot
Pick one narrow use case, define success metrics, set QA gates, and assign owners for a 90-day test.
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58:00
Recap And Live Q&A
Review key decisions, next steps, and attendee questions before you choose your first pilot.
Questions people ask before registering
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It is built for working professionals in pharmacovigilance, drug safety, QA, regulatory, and adjacent data or analytics roles. If you help review, govern, or improve signal detection, it will feel familiar.
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No. We explain the methods in plain language and keep the focus on PV decisions, controls, and workflow design rather than math for its own sake.
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Yes, a replay will be available to registered attendees. You can watch the full session later and revisit the pilot framework at your own pace.
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Yes. A core section covers bias, drift, explainability, validation, versioning, change control, and how to make model use defensible during inspection.
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Yes. The close centers on a narrow 90-day pilot plan with data, metrics, controls, QA gates, and named reviewers. The goal is one testable workflow, not a grand manifesto.
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No CE credit is listed for this webinar. If a certificate of attendance is provided, registered attendees will receive details after the session.