AI/ML SaMD and FDA's 2021 Action Plan: What Medical Device Companies Must Know Before Submission

The Regulatory Reality of AI/ML Software as a Medical Device

If your company is developing an AI- or machine learning-powered Software as a Medical Device (SaMD), you are operating in one of the most scrutinized and rapidly evolving corners of FDA oversight. The agency's Artificial Intelligence/Machine Learning (AI/ML)-Based Software as a Medical Device Action Plan, published in January 2021, is not a distant policy document — it is an active framework shaping how FDA reviewers evaluate your submissions today. Understanding its five core pillars is not optional; it is a prerequisite for a credible regulatory strategy.

What FDA's 2021 AI/ML Action Plan Actually Requires

FDA's action plan built directly on the agency's 2019 proposed regulatory framework for AI/ML-based SaMD, which itself referenced the International Medical Device Regulators Forum (IMDRF) SaMD framework. The 2021 document identified five areas of focused action that continue to define expectations across 510(k), De Novo, and PMA pathways:

• Good Machine Learning Practice (GMLP): FDA has been developing GMLP principles in collaboration with Health Canada and the UK's MHRA. These principles — finalized in a joint October 2021 publication — establish baseline expectations around data management, model training, performance evaluation, and post-market monitoring. Reviewers increasingly expect sponsors to demonstrate alignment with GMLP in their software documentation.
• Predetermined Change Control Plans (PCCPs): This is the centerpiece of the action plan and the single concept most misunderstood by startup founders. Because adaptive AI/ML algorithms change over time, FDA introduced the PCCP as a mechanism to prospectively describe the types of modifications a device may undergo, the methodology for implementing those changes, and the performance evaluation protocols that will govern them. FDA finalized guidance on PCCPs in December 2023. If your AI/ML device has any adaptive or continuously learning components, your submission must include a well-structured PCCP or you will face avoidable RTA (Refusal to Accept) or deficiency letters.
• Algorithm Transparency and Labeling: FDA expects AI/ML SaMD submissions to include clear disclosure of the algorithm's intended use, the data it was trained on, known limitations, and performance characteristics across relevant patient subgroups. This ties directly to 21 CFR Part 801 labeling requirements and FDA's broader push for algorithmic transparency. Generic performance summaries are insufficient — stratified performance data by age, sex, race, and clinical setting is increasingly expected for moderate-to-high risk devices.
• Real-World Performance Monitoring: Under 21 CFR Part 820 and the Quality System Regulation (now aligned with ISO 13485 under the amended Quality Management System Regulation finalized in 2024), post-market surveillance obligations apply to SaMD. For AI/ML devices, FDA expects your post-market surveillance plan to include mechanisms for detecting model drift, distribution shift, and performance degradation in real-world deployment. This is not aspirational — it is enforceable.
• Equity and Bias Considerations: FDA's action plan explicitly addressed the risk of algorithmic bias, particularly for devices trained on non-representative datasets. Submissions for AI/ML SaMD involving diagnostic or treatment decision support should include a bias assessment protocol and, where applicable, mitigation strategies embedded in the PCCP.

Matching Your AI/ML Device to the Right Submission Pathway

Not every AI/ML SaMD requires a PMA. FDA's risk-based classification framework under 21 CFR Parts 862–892 still governs, and the key question is whether your device meets a predicate for 510(k) clearance, whether De Novo classification is appropriate, or whether the novelty and risk level demand a PMA. For many early-stage companies, the De Novo pathway under 21 CFR Part 860.257 is underutilized. If your AI/ML SaMD has no valid predicate but presents low-to-moderate risk, De Novo can establish a new classification and a pathway for future 510(k) submissions — including your own.

One critical distinction: FDA's 2021 guidance on Clinical Decision Support (CDS) Software — finalized under Section 520(o) of the FD&C Act as amended by the 21st Century Cures Act — defines which software functions are exempt from device regulation versus those that remain subject to FDA oversight. Misclassifying your AI/ML tool as non-device CDS is one of the most common and costly regulatory errors we see at ADB Consulting & CRO Inc.

Practical Steps Before You Submit

Regulatory preparedness for AI/ML SaMD is not something you bolt on before submission. It must be architected into your development process. At minimum, your team should address the following before engaging FDA:

• Define your Software Level of Concern under FDA's 2023 Software as a Medical Device guidance and ensure your software documentation package aligns with IEC 62304 lifecycle requirements.
• Draft a PCCP that is specific, bounded, and tied to defined performance thresholds — vague PCCPs are routinely flagged in interactive review.
• Conduct a pre-submission (Q-Sub) meeting under FDA's Pre-Submission Program to align on your proposed study design, performance benchmarks, and classification rationale before you invest in pivotal validation studies.
• Ensure your Quality Management System — whether ISO 13485-certified or not — has documented procedures for AI/ML-specific risks including training data governance, version control, and post-market performance monitoring.

The Regulatory Window Is Narrowing

FDA is moving toward a more defined regulatory framework for AI/ML SaMD, and the agency has signaled through recent 510(k) decisions and warning letters that informal tolerance for underdeveloped AI submissions is eroding. Sponsors who engage early, document rigorously, and build a credible PCCP are consistently better positioned for timely clearance.

At ADB Consulting & CRO Inc., we work directly with medical device startups and established companies to build submission-ready AI/ML SaMD regulatory strategies — from pre-submission meetings through clearance and post-market compliance. Whether you are entering your first FDA interaction or responding to a deficiency letter, we bring the technical depth and regulatory experience to move your program forward.

Book a free discovery call with Andre Butler today at adbccro.com. In 30 minutes, we can assess your regulatory pathway, identify submission gaps, and give you a clear picture of what it takes to bring your AI/ML device to market.