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How to Use AI in Drug Development Without Creating Compliance Risk

How to Use AI in Drug Development Without Creating Compliance Risk

  • 67 minutes
  • 35 slides
What we'll cover
  • 0:00 Where AI Fits Safely
  • 10:00 The Real Compliance Traps
  • 22:00 A Practical Risk Screen
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What you'll take away

Practical shifts you can apply this week

  • Identify Safe AI Tasks

    Identify drug development tasks where AI can add value without entering high-risk GxP territory.

  • Evaluate Compliance Risk

    Evaluate AI use cases for compliance risk across data, model, output, and workflow controls.

  • Compare Low And High Risk Uses

    Compare low-risk assistive uses of AI with higher-risk decision-making and record-generating uses.

  • Draft Practical Guardrails

    Draft practical guardrails for prompting, review, documentation, and vendor oversight.

  • Decide Pilot Or Stop

    Decide when an AI use case is ready to pilot, escalate, or stop.

Agenda

What we'll cover

  1. 0:00

    Where AI Fits Safely

    Start with where AI helps most: low-consequence support work, not regulated judgment.

  2. 10:00

    The Real Compliance Traps

    See how data leakage, undocumented use, and over-trust create more risk than the model itself.

  3. 22:00

    A Practical Risk Screen

    Use a simple triage to sort ideas into proceed, pilot with controls, or do not use.

  4. 32:00

    Use Cases By Development Stage

    Compare examples from discovery, clinical, regulatory, pharmacovigilance, and quality.

  5. 46:00

    Controls That Actually Work

    Cover approved tools, bounded data, human review, and documentation that people will actually use.

  6. 56:00

    Vendor And Validation Decisions

    Learn what due diligence and validation should look like when risk is low, medium, or high.

  7. 62:00

    Pilot Plan And Q&A

    Leave with a narrow first-pilot plan, stop criteria, and time for attendee questions.

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