The PCCP Inflection Point: What FDA Clearance Data Tells Us About AI/SaMD in 2025

By Sentir Health · 06/14/2026

Something significant happened in the FDA's clearance pipeline starting in 2023. If you work in AI-enabled medical devices, you've probably felt it without seeing the numbers clearly.

We built the Sentir PCCP Tracker to make those numbers visible. Here's what the data shows.

143 PCCP authorizations. 64 are AI/SaMD.

As of June 2026, the FDA has authorized 143 devices with Predetermined Change Control Plans. Nearly half of them, 64, are AI/SaMD. And 23 PCCP authorizations were added in the last 90 days alone — nearly 40% of them AI/SaMD.

That last number is the one worth sitting with. This market isn't about to ramp. It already is.

Why the timeline looks the way it does

If you look at PCCP authorizations by quarter, the chart is almost flat from 2019 through 2022, with a handful of blips in early 2020, all non-AI devices. Then 2023 happens and the bars start climbing.

This isn't a data artifact. It reflects the actual regulatory timeline.

The concept of a PCCP isn't new. FDA described mechanisms for pre-authorizing certain device changes as far back as 2017, and the statutory authority itself arrived in December 2022, when FDORA added Section 515C to the Food, Drug, and Cosmetic Act. A small number of non-AI device submissions used PCCP-like frameworks around 2020, but those were isolated cases, mostly traditional SaMD with narrow, well-understood change types.

For AI/SaMD, the activation came later. In April 2023, FDA published its draft guidance on PCCPs for AI/ML-enabled device software functions. That was the first document that gave AI device makers a concrete template for what a PCCP submission should look like, what it needed to include, and how FDA would evaluate it. Companies that had been watching the space started building PCCPs into their pipelines almost immediately after.

The final guidance dropped in December 2024, and it landed with more clarity than the draft. The title was broadened from ML-specific language to AI-enabled device software functions more broadly, reflecting that most of what FDA was actually reviewing was machine learning but that the framework needed to cover the full AI category. By that point the quarterly authorization numbers were already climbing, and they haven't slowed down since.

By 2025, the bars on the chart reached nearly 28 authorizations in a single quarter across all device types, with AI/SaMD making up a growing share of that total.

Having a PCCP and being able to execute it are different things

Here's the part that doesn't get talked about enough.

A PCCP isn't just a document you include in your 510(k) and move on. Under the December 2024 final guidance, every authorized PCCP must include a Modification Protocol that covers four specific elements: data management practices, re-training practices, performance evaluation protocols, and update procedures. FDA expects pre-defined acceptance criteria for each planned modification type, and your quality system needs to support the full implementation lifecycle.

That's a real operational commitment. And the moment you actually exercise your PCCP, a specific and uncomfortable question comes into focus.

When you retrain your model, or make any other change authorized under your PCCP, you need to demonstrate that the modification met your pre-specified performance criteria. FDA doesn't require you to monitor continuously or file interim reports along the way — but when you exercise the PCCP, the burden is on you to produce that demonstration on demand. And that surfaces an uncomfortable question: how do you show your model wasn't already degrading before the change? If performance drift is what prompted the retrain in the first place, your baseline matters enormously — and a baseline isn't something you can reconstruct after the fact. The evidence either exists by the time you need it, or it doesn't.

The guidance is clear that deviations from an authorized PCCP, including failure to meet pre-specified performance criteria, could significantly affect the safety or effectiveness of the device. It's also clear that all PCCP implementation must occur within the manufacturer's quality system, and with FDA's QMSR rule aligning 21 CFR Part 820 with ISO 13485 taking effect in February 2026, the documentation and traceability discipline around those records is under renewed scrutiny.

The argument for continuous monitoring isn't that FDA explicitly mandates it by name. It's that your Modification Protocol requires pre-defined acceptance criteria and re-training practices, and without longitudinal performance data you have no systematic way to demonstrate you met those criteria before and after the change. You'd be reconstructing a history you don't have, at exactly the moment when documentation matters most.

What this means practically

Let's be honest about the current state. Almost every company that cleared a device with a PCCP is doing some form of post-market monitoring already. They have scripts, dashboards, spreadsheets, a notebook someone runs each month. The problem isn't the absence of monitoring. It's that ad hoc monitoring doesn't survive contact with reality.

The engineer who built the monitoring pipeline leaves, and the institutional knowledge of how it works leaves with them. A quarter's worth of performance evidence never gets formally documented because everyone was heads-down shipping. The acceptance criteria in the running code drift out of sync with what the authorized PCCP actually specified. FDA guidance evolves, and the monitoring setup doesn't keep pace. Then multiply all of that across multiple cleared devices, multiple model versions, and multiple PCCPs, each with its own modification protocol and its own acceptance criteria.

That's the gap. Not whether you're monitoring, but whether your monitoring is durable, auditable, and consistent enough to defend a modification submission two years from now, when the person who set it up is gone and FDA wants to see the evidence trail.

This is where Sentir steps in. Not to replace the monitoring your team is already doing, but to make it durable and independent: continuous performance capture against the acceptance criteria your PCCP actually specifies, kept as a record separate from the engineers shipping the model, with a tamper-evident audit trail that holds regardless of who comes and goes. A system of record that stays aligned with your authorized plan across every device and version you ship.

That independence matters more than it might first appear. Evidence your own team generates and documents about its own model is, structurally, self-reported. A record maintained separately, that can't be quietly backfilled or adjusted after the fact, is simply more defensible when an FDA reviewer asks how you know the device stayed within its authorized envelope.

About the PCCP Tracker

The Sentir PCCP Tracker is a free public tool that aggregates PCCP authorizations from FDA 510(k) and De Novo databases, with AI/SaMD classification based on FDA product codes and device description keyword analysis. It updates regularly and is the only purpose-built tracker for this specific regulatory mechanism.

If you work in AI-enabled medical devices as a regulatory affairs lead, QA director, or CTO, bookmark it. The market is moving faster than most people realize.

Sentir Health builds post-market monitoring compliance infrastructure for FDA-cleared AI/SaMD vendors with PCCPs. Learn more or book a call.

Methodology note: PCCP authorization counts sourced from FDA 510(k) Premarket Notification and De Novo databases. AI/SaMD classification based on FDA product codes associated with AI/ML-enabled software functions, supplemented by keyword analysis of device descriptions. All figures current as of 2026-06-14. Classification methodology available on request.