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Скачать или смотреть AI on Guard for Drug Safety: 10 Ways a QPPV Can Turn Chaos into Order with NotebookLM and Gemini

  • Vitalii Usenko
  • 2026-01-10
  • 50
AI on Guard for Drug Safety: 10 Ways a QPPV Can Turn Chaos into Order with NotebookLM and Gemini
QPPVAIGeminiNotebookLMDrug SafetyPharmacovigilance
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Описание к видео AI on Guard for Drug Safety: 10 Ways a QPPV Can Turn Chaos into Order with NotebookLM and Gemini

The video presentation “AI on Guard for Drug Safety: 10 Ways a QPPV Can Turn Chaos into Order with NotebookLM and Gemini” outlines how Qualified Persons for Pharmacovigilance (QPPV) can leverage Google's NotebookLM and Gemini as a "digital exoskeleton" to manage the overwhelming volume of regulatory data and safety reports.

By utilizing an enterprise environment that ensures data privacy and GDPR compliance through a "no-training" guarantee, QPPVs can create a secure, closed "vault" for their proprietary documents rather than relying on open web searches. The transcript details ten specific business cases for automating routine tasks, such as performing gap analyses on new regulations, cross-referencing signal detection data, auditing call center transcripts, and simulating high-pressure inspections.

Crucially, the workflow enforces a "trust, but verify" approach, where the AI serves as a "junior officer" that cites specific sources ("grounding"), requiring the human expert to validate every claim against the original document to maintain patient safety and GxP compliance.

Timecodes:

00:00 - Greeting
00:15 - Introduction: Why Pharmacovigilance Needs an Upgrade
01:12 - Part 1: The Toolkit. NotebookLM and Gemini 3.0 Pro. A Quick Crash Course
02:51 - How to maintain strict confidentiality and GDPR compliance
04:59 - Part 2: Ten Business Cases for Implementation (From Routine to Strategy)
05:17 - Case #1: Instant Regulatory Adaptation
07:50 - Case #2: Signal Detection 360° (Data Stacking)
11:13 - Case #3: Mock Inspection (The "Angry Inspector" Simulator)
14:06 - Case #4: Safety Data Exchange Agreement and Pharmacovigilance Agreements Management (The "Legal Shield")
17:02 - Case #5: Local Literature Screening (The Time-Saver)
19:23 - Case #6: The "Living" Master File (The Pharmacovigilance System Master File)
22:01 - Case #7: Patient Support Programs Call Center Audit (Quality Control)
24:51 - Case #8: The "Label Police" (Core Company Data Sheet vs. Local Summary of product characteristics)
28:07 - Case #9: The "Narrative Architect" (Source Docs to Narrative)
30:42 - Case #10: The "Crisis Communicator" (Dear Healthcare Professional Letter Generator)
33:12 - AI and QPPV Evolution
33:37 - The "Golden Rule" of AI in GxP: Trust, but Verify (The Source Guide)
36:15 - Disclaimer & Educational Notice
37:49 - Let’s continue the discussion

Disclaimer: This presentation was developed with the assistance of AI tools for educational and illustrative purposes only, aiming to facilitate discussion on the future of technology in Pharmacovigilance rather than offering professional advice or regulatory guidance. Implementing AI within a GxP environment demands strict adherence to local laws, GDPR, and validation requirements such as 21 CFR Part 11 and EU Annex 11. AI tools must never substitute for human judgment; the Qualified Person for Pharmacovigilance (QPPV) retains full responsibility for the system's accuracy, integrity, and the ultimate oversight of patient safety

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