AI & FDA Compliance

Are you confident the AI tools you’re using in your regulated environment are compliant?

Integrating AI into a QMS: FDA Compliance Considerations

The FDA has made it clear: any software that influences product quality, record integrity, or quality system decision-making must be validated, controlled, and predictable. This includes AI and machine learning (ML) tools.

Under 21 CFR Part 11 and 21 CFR Part 820, companies are required to: Validate all software impacting • quality or records.

  • Maintain traceability of all actions, including AI-generated outputs.
  • Implement change control and revalidation for any software updates.
    But here’s the challenge: Machine learning tools are non-deterministic — they learn and change. This makes it nearly impossible to meet FDA validation requirements unless tightly controlled.
    Without freezing the model or having an FDA-reviewed Predetermined Change Control Plan (PCCP), directly embedding AI into a validated QMS (like EPICOR or MasterControl) puts you at risk for inspection findings — including 483 observations or worse.
FDA Stance On LLM Validation
  • 21 CFR 11.10(a) – Requires validated, predictable system performance.
  • 21 CFR 820.70(i) – Requires validation of software in production and quality systems.
    FDA’s AI/ML SaMD Framework (2019) – Recommends “locked” models or robust change control.
  • FDA AI/ML Action Plan (2021) – Requires real-time model monitoring and safety oversight.
  • • Final FDA Guidance (Jan 2025) – Confirms PCCPs are mandatory for adaptive models.

Bottom line: If your AI is making or influencing decisions inside your validated QMS and isn’t frozen or governed by a PCCP, your system is likely non-compliant.

RBLB’s Compliant AI Strategy

At Right Brain Left Brain Consulting (RBLB), we’ve built a compliant-by-design AI model that sidesteps these regulatory pitfalls.

Our Safer AI Architecture:
  • External Processing: Our AI tools operate outside your validated QMS, so they don’t compromise its integrity.
  • Human-in-the-Loop Review: All outputs are manually reviewed before entry into validated systems, maintaining traceability and quality decision-making control.
  • Controlled Uploads: Validated interfaces ensure data is uploaded to your QMS in a fully auditable, documented way.
  • Model Transparency: Each model is frozen prior to deployment and version-controlled, with optional revalidation protocols.
  • We believe compliance shouldn’t be an afterthought — and that includes AI.
Why This Matters

AI can revolutionize productivity, quality, and decision-making — but not at the expense of regulatory risk. Our approach lets you:

  • Use AI where it makes sense — without threatening your validated systems.
  • Pass audits confidently, even under the FDA’s newest AI/ML guidance.
  • Avoid unnecessary remediation, citations, or operational disruption.
    Our promise: We build AI solutions with compliance, continuity, and culture in mind — because innovation should never come at the cost of inspection readiness.

Want to Know More?

If you’re considering AI tools for quality, procurement, compliance, or operations and want to ensure they align with FDA regulations, we can help. We also offer workshops to help your team understand: •FDA expectations for AI/ML in regulated environments • How to safely integrate AI into non-validated workflows • When and how to validate AI tools without overcomplicating.

Let’s build innovation the right way!

FAQ

No. But they’ve clearly stated that any evolving model must be governed by a PCCP or locked
down. This sets a high bar for embedding AI directly in validated environments.

Yes — but it’s much more flexible. Our method stays compliant while maximizing the benefits of AI.

No — we reserve our proprietary methodologies for clients. But we’ll always be transparent
about compliance and best practices.

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