How FDA’s Digital Health Center of Excellence Is Shaping 2026 MedTech Innovation

Key Pitfalls & Best Practices for AI/ML-Enabled SaMD / SiMD Under Current FDA Thinking

Introduction

The FDA’s Digital Health Center of Excellence (DHCoE) is rapidly tightening expectations for AI/ML, SaMD, and software quality systems. Over the next year, these updates will directly influence how developers build, validate, and maintain digital health technologies. For MedTech teams, the message is clear: stronger documentation, clearer risk controls, and mature software lifecycle practices are becoming essential… not optional.

Below is a breakdown of the major DHCoE initiatives influencing 2026 MedTech innovation and what they mean for software teams navigating regulatory expectations.

FDA’s Evolving AI/ML Framework:

What Developers Must Prepare for in 2026

Over the last two years, the Digital Health Center of Excellence has expanded its focus on AI/ML-enabled medical devices, with several key trends emerging.

Stronger expectations for transparency, documentation, and traceability

FDA is reinforcing that AI/ML models must be:

• Trained on well-characterized, representative datasets

• Documented with full data lineage and model development history

• Verified and validated under risk-based, traceable methods

• Supported by explainability commensurate with device risk

This shift aligns with Good Machine Learning Practices (GMLP) and signals FDA’s move away from accepting “black box” systems. Developers should expect deeper methodological scrutiny in premarket reviews.

Why this matters for MedTech teams

Teams lacking structured software lifecycle processes and AI-specific risk controls will see longer review cycles and more requests for information. Mature documentation and QMS integration will become strategic advantages.

Predetermined Change Control Plans (PCCPs) Become Central to AI/ML Regulatory Success

DHCoE continues to develop and refine expectations for Predetermined Change Control Plans, a mechanism that allows certain algorithm updates without repeated submissions.

The latest updates emphasize:

• Detailed modification protocols
• Defined metrics for performance monitoring
• Real-world evidence integration
• Risk-based validation for postmarket updates

Why PCCPs matter in 2026

PCCPs offer speed and flexibility, but only for teams prepared to meet the documentation and monitoring burden.

• Manufacturers must demonstrate:
• Which parameters can change
• How updates are validated
• How drift or degradation is detected
• How performance is monitored over time
  

Without strong QMS foundations, PCCPs can be difficult to execute effectively.

SaMD Lifecycle Expectations Continue to Mature

The Digital Health Center of Excellence is pushing for greater rigor across the entire SaMD lifecycle.

  a. Deeper documentation expectations

FDA reviewers increasingly expect:

• Clear architectural documentation tied to risk controls
• Complete verification and validation evidence, including stress and edge-case testing
• Demonstrable cybersecurity-by-design
• Human factors evaluations for digital workflows

  b. Stronger alignment with global standards

SaMD submissions are expected to follow:

• IEC 62304 – software lifecycle
• ISO 14971 – risk management
• IEC 82304-1/1-1 – health software safety and security
• Emerging international approaches for AI/ML oversight

This trend supports global harmonization and reduces ambiguity across markets.

  c. Higher expectations for postmarket performance

FDA is emphasizing:

• Continuous monitoring
• Complaint analysis
• Cybersecurity incident readiness
• Real-world performance assessments

4. DHCoE Transparency and Regulatory Clarity Efforts Accelerate

To support digital health developers, DHCoE has expanded several tools and programs:

• Updated databases and device classification resources for clearer pathway planning
• New regulatory science papers and workshops on AI/ML, real-world data, and cybersecurity
• More structured Q-Submission interactions
• Increased clarity around QMSR expectations for software-first manufacturers

These resources signify FDA’s long-term commitment to providing clearer, more predictable pathways for digital innovation.

What All of This Means for 2026 MedTech Innovation

Across all DHCoE initiatives, the message is consistent:

FDA expects greater software maturity, more rigorous documentation and deeper lifecycle control from digital health manufacturers

Teams investing in:

• Software lifecycle processes
• AI/ML documentation frameworks
• Real-world performance monitoring
• Cybersecurity controls
• Integrated risk management
• Robust QMS architecture

…will navigate 2026 with fewer surprises and faster review cycles.

Teams who continue treating quality as a regulatory checkbox will face slower approvals, remediation risk, and costly delays.

How Rook Quality Systems Helps Digital Health and AI/ML Teams Prepare for FDA Expectations

As DHCoE continues to define the future of digital health, the teams that win will be those who invest in scalable, compliant systems now… not after FDA asks for them.

If you’re building AI/ML or SaMD products and want to ensure your development, documentation, or submission strategy aligns with the FDA’s 2026 expectations, our team is here to help.

Contact Rook Quality Systems Today!