Software & SaMD

Most AI medical device companies misunderstand PCCPs

March 13, 2026
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By Dr. Ebot Eyong

A Predetermined Change Control Plan (PCCP) is not regulatory flexibility. It is a pre-authorized change under strict control. This article explains why PCCPs require clear change definitions, statistical thresholds, bias monitoring, drift detection, rollback procedures, and documented impact assessments.

A Predetermined Change Control Plan (PCCP) is not regulatory flexibility.

It is a pre-authorized change under strict control.

As FDA scrutiny increases.

Here’s what leaders need to know:

  • A PCCP must clearly define which changes are allowed
  • Statistical performance thresholds must be predefined
  • Bias monitoring cannot be optional
  • Drift detection must be built into governance
  • Rollback procedures are mandatory
  • Impact assessments must be documented for every update

If your PCCP is vague, FDA will issue deficiencies.

If your PCCP is overly narrow, you gain no flexibility.

The balance requires:

  • AI governance maturity
  • ISO 14971 integration
  • Strong statistical design
  • Regulatory foresight
  • Cross-functional execution

Done correctly, a PCCP becomes a competitive advantage.

Done poorly, it increases regulatory risk.

AI innovation without a structured regulatory architecture is exposed.

At E&E Medicals & Consulting, we help manufacturers design FDA-ready PCCPs that scale globally and align with EU AI Act and MDR expectations.

If you're building AI-enabled devices, governance isn’t optional - it’s strategic.

— Dr. Ebot Eyong
Global AI Regulatory Strategy

For more information, visit https://eemedicals.com/

Explore More Publications

Continue exploring Dr. Ebot Eyong’s professional insights on healthcare regulation, FDA submissions, AI-enabled medical devices, quality systems, and global compliance strategy.

Software & SaMD

FDA Draft Guidance on AI-Enabled Device Software: Key Takeaways for Industry

September 2, 2025
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By Dr. Ebot Eyong

On January 6, 2025, the FDA released draft guidance on development, lifecycle management, and marketing submissions for AI-enabled device software. This article explains key lifecycle expectations, submission considerations, manufacturer implications, and regulatory pitfalls.

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CMC & FDA Submissions

Top 10 Premarket Authorization Challenges for Medical Device Manufacturers Navigating Regulatory Complexity from Concept to Market Approval

July 9, 2026
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By Dr. Eyong Ebot

Discover the top 10 premarket authorization challenges facing medical device manufacturers and learn practical strategies to accelerate FDA 510(k), De Novo, and PMA approvals.

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EU Regulatory Strategy

EU Proposal to Revise MDR and IVDR: Implications for Innovation, Documentation, and Software Oversight

February 17, 2026
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By Dr. Ebot Eyong

The European Commission has proposed a targeted revision of the Medical Device Regulation and In Vitro Diagnostic Regulation aimed at supporting innovation while reducing unnecessary administrative burden. This article explores the impact on technical documentation, manufacturers, implementation challenges, and software oversight.

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Real-World Evidence

FDA Update on Real-World Evidence: Implications for AI-Enabled Medical Devices

May 2, 2025
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By Dr. Ebot Eyong

The U.S. Food and Drug Administration has updated its Real-World Evidence policies to allow greater use of large, well-curated data sources in medical device marketing submissions. This article explains how RWE may support safety and effectiveness for AI-enabled medical devices.

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