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.

AI & Digital Health

AI Validation Requirements for FDA Submissions: What Companies Must Know Now!!

May 11, 2024
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By Dr. Ebot Eyong

AI is reshaping medical devices, but regulatory hurdles remain. Validation is vital for FDA approval, especially with the complexities of machine learning. This article outlines key requirements including data quality, performance testing, clinical validation, transparency, risk management, lifecycle management, and real-world monitoring.

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Quality Systems

The FDA's 2025 Draft Guidance is titled "Quality Management System Information for Certain Premarket Submission Reviews

January 2, 2026
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By Dr. Ebot Eyong

This draft guidance describes a streamlined process for FDA reviewers to evaluate a manufacturer's QMS during premarket review, replacing the disconnected, siloed approach with a proactive use of QMS information to achieve a smoother and more effective review.

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EU Regulatory Strategy

Case Study: EU MDR Transition Strategy - Remediation

August 13, 2026
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by Dr. Ebot Eyong

How E&E Medicals Guided a Medical Device Manufacturer Through the Transition from the Medical Device Directive (MDD) to the European Medical Device Regulation (EU MDR 2017/745)

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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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