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Choose 510(k) when a legally marketed predicate supports substantial equivalence. Choose De Novo when the device is novel, has no suitable predicate, and presents low-to-moderate risk that can be controlled with general or special controls. Choose PMA when the device is high risk, generally Class III, and requires an independent demonstration of safety and effectiveness. An AI function does not create a fourth pathway: FDA reviews the complete device, its intended use, risks, technology, evidence, and planned changes through the applicable route.
At a glance: match the pathway to risk and evidence
The fastest way to frame an FDA pathway decision is to answer two questions: is there a legally marketed predicate, and what level of risk remains after appropriate controls? The answers point toward the three principal routes.
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| Pathway | When it fits | Core FDA question | Result and future effect |
|---|---|---|---|
| 510(k) | A legally marketed predicate exists and your device can be shown substantially equivalent. | Is the new device as safe and effective as the predicate, despite any technological differences? | FDA issues a substantially-equivalent determination. The cleared device does not automatically create a new device type. |
| De Novo | The device is novel, no suitable predicate exists, and the risk can be controlled at Class I or Class II levels. | Can FDA classify this new device type as Class I or II with adequate controls? | A granted request permits marketing and can establish a new device type that may serve as a predicate for later 510(k) submissions when applicable. |
| PMA | The device is high risk, generally Class III, or its risks cannot be adequately controlled by general and special controls. | Does valid scientific evidence provide reasonable assurance that this device is safe and effective for its intended use? | FDA makes an independent safety-and-effectiveness determination for the device under review. |
“AI” by itself does not move a product into PMA, nor does it guarantee access to 510(k). The intended use, patient population, output claims, degree of automation, failure modes, and residual risk matter more than the choice of algorithm.
What each pathway actually requires
510(k): comparative substantial equivalence
A 510(k) is built around comparison with a legally marketed predicate. Your submission identifies the predicate, states the proposed device’s intended use, and compares technological characteristics. FDA then decides whether the differences raise different questions of safety or effectiveness and whether the submitted evidence shows the new device is as safe and effective as the predicate.
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The predicate does not have to use artificial intelligence. FDA’s AI/ML lifecycle framework allows an AI-enabled device to use a non-AI predicate when the intended use is the same, the technological differences do not introduce different safety or effectiveness questions, and the other 510(k) requirements are met. A different technology can therefore be acceptable, but the burden is on the sponsor to explain why the difference does not create a new risk question and to support that explanation with data.
Depending on the device, FDA may expect performance evidence such as clinical testing, non-clinical bench testing, software validation, sterility, electromagnetic compatibility, and biocompatibility. Not every category applies to every product; the evidence should correspond to the device’s materials, interfaces, environment, and claims.
The device cannot be marketed on the basis of a pending submission. Marketing follows only after FDA issues a substantially-equivalent determination.
De Novo: a route for novel, controllable risk
De Novo is a risk-based classification process for certain new device types without a suitable predicate. The route is appropriate when the product is novel but its risks can be addressed with general and special controls at Class I or Class II levels. FDA can receive a De Novo request after a 510(k) receives a “not substantially equivalent” (NSE) determination, or a sponsor can request De Novo directly when it determines that no legally marketed predicate exists.
A granted De Novo request allows the device to be marketed and can establish a new device type. Later devices of that type may be able to use the De Novo device as a predicate for 510(k) submissions, provided the later products meet the substantial-equivalence standard.
De Novo is not a shortcut around evidence. The sponsor still has to give FDA enough information to understand the device’s risks and establish controls appropriate to its classification. The distinction from PMA is that the requested classification is Class I or II, not that the device is exempt from rigorous review.
PMA: independent evidence for high-risk devices
PMA is FDA’s most stringent device marketing application. It is used for Class III devices and for devices whose risks cannot be adequately controlled by general and special controls. The sponsor must provide sufficient valid scientific evidence to give reasonable assurance that the device is safe and effective for its intended use.
The PMA standard is independent rather than comparative. Evidence that another device works does not automatically establish the safety and effectiveness of your device. Your submission must support the specific device, intended use, patient population, claims, and operating conditions under review.
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“The 510(k) review standard is comparative, whereas the PMA standard relies on an independent demonstration of safety and effectiveness.” — U.S. Food and Drug Administration, Medical Device Safety and the 510(k) Clearance Process
How FDA separates the three routes
1. Start with intended use, not the model architecture
Write the intended use in operational terms before debating neural-network type or software stack. Include the condition or measurement addressed, the intended users, the patient population, the care setting, the input data, the output, and what the user is expected to do with that output. A product that highlights an image for a trained professional presents a different regulatory question from one that independently diagnoses a condition or directs treatment.
Output claims and automation level are especially important for AI. “Assists review” and “provides a measurement” describe a different role from “rules out disease” or “determines treatment.” The more the output can directly drive a high-consequence decision, the more carefully the sponsor must analyze failure modes and residual risk.
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2. Determine whether a legally marketed predicate exists
A predicate is the central gate for 510(k). It must be a legally marketed device that is appropriate for the proposed comparison. A product that merely looks similar, uses the same data type, or serves the same broad industry does not automatically qualify.
If no suitable predicate exists, consider whether the device is novel but low-to-moderate risk and controllable as Class I or II. That is the territory De Novo is designed to address. If the risk cannot be adequately controlled at those levels, PMA becomes the more likely route.
3. Analyze whether technology differences create new questions
For 510(k), list each meaningful difference from the predicate: input data, sensors, software functions, algorithm behavior, user interface, connectivity, alerts, operating environment, and dependence on human review. For each difference, ask whether it could change the probability or severity of a failure, alter how a user interprets the output, or create a new hazardous situation.
An AI model can be technologically different from a predicate without automatically failing substantial equivalence. The decisive issue is whether the difference raises different safety or effectiveness questions and whether the evidence addresses those questions.
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Evidence should test the functions that matter to the intended use. A software validation package may be central for an algorithmic function; clinical evidence may be needed when performance claims depend on patient outcomes or clinical interpretation. Bench, electromagnetic-compatibility, sterility, and biocompatibility testing may matter when the product has hardware, an invasive interface, or a patient-contacting component.
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Do not treat a high accuracy result on a development dataset as a complete safety case. FDA’s pathway standards focus on the device’s intended use and the risks associated with its actual operation, including foreseeable failures and user interaction.
Can an AI device use a non-AI predicate?
Yes, potentially. FDA’s AI/ML lifecycle guidance specifically contemplates substantial equivalence between an AI-enabled device and a non-AI-enabled predicate. Three conditions must be satisfied:
- The intended use is the same.
- The technological differences do not introduce different questions of safety or effectiveness.
- The submission meets the other 510(k) requirements, including appropriate performance evidence.
That means “the model is new” is not, by itself, a reason to abandon 510(k). It also means a non-AI predicate is not a protective label. If the AI changes the meaning of the output, expands the patient population, increases automation, or creates new failure modes, FDA may find that the comparison raises different questions.
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Build the comparison around user-facing function and risk, not marketing language. Document what the predicate does, what your software does, where the functions differ, and why those differences do or do not alter safety or effectiveness questions.
A practical pathway-selection workflow
- Freeze the proposed intended use. Record the condition or measurement, user, patient population, setting, inputs, outputs, automation level, and claims you expect to put on the labeling.
- Map hazards and failure modes. Include incorrect outputs, missed findings, false alarms, data-quality failures, out-of-distribution inputs, connectivity loss, latency, user misunderstanding, and unsafe reliance on an automated recommendation.
- Search for a legally marketed predicate. Compare intended use first, then technological characteristics and risk controls. A non-AI predicate may be usable when the AI differences do not raise different safety or effectiveness questions.
- Choose the lowest defensible route. Use 510(k) when substantial equivalence is supportable. Use De Novo when the device is novel, lacks a predicate, and can be controlled as Class I or II. Use PMA when the risk is high or cannot be adequately controlled by general and special controls.
- Build an evidence plan. Tie every planned test to a claim, hazard, or technological difference. Identify where clinical, bench, software-validation, sterility, electromagnetic-compatibility, or biocompatibility evidence is applicable.
- Plan lifecycle changes before submission. Identify which model, data, interface, or performance changes could significantly affect safety or effectiveness and how you will evaluate them.
- Confirm the submission mechanics. FDA’s 510(k) materials state that submissions generally use the electronic eSTAR template and CDRH Portal unless an exemption applies. Verify the applicable FDA instructions for the specific submission type.
What to include in a 510(k) strategy
Predicate comparison
Prepare a side-by-side comparison of intended use, indications, patient population, inputs, outputs, user interaction, algorithmic role, hardware, operating environment, and risk controls. Explain each difference rather than asserting that the products are “similar.”
AI-specific performance explanation
Describe how the model receives data, produces an output, handles missing or poor-quality inputs, and presents uncertainty or warnings to the user. Show how the validation approach reflects the intended use and foreseeable use errors. The goal is not to promote the algorithm; it is to demonstrate that the complete device performs safely and effectively for the claimed purpose.
Submission format
Use the electronic eSTAR template and CDRH Portal for a 510(k) unless an exemption applies, as stated in FDA’s 510(k) materials. Organize the technical comparison and test reports so reviewers can trace each claim and risk to supporting evidence.
When De Novo is the better answer
De Novo is appropriate when the product is genuinely new as a device type, a suitable predicate cannot be identified, and the risks can be managed at Class I or II. It can be requested directly when the sponsor determines that no legally marketed predicate exists, or after FDA issues an NSE determination on a 510(k).
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The central work is classification: define the risks, propose general and special controls, and provide enough information for FDA to conclude that those controls reduce the risks to an acceptable level for Class I or II. A granted De Novo request then has a lasting market effect because it can establish a new device type and provide a predicate for later 510(k) submissions when applicable.
Do not select De Novo merely because a 510(k) comparison is inconvenient. If the device’s residual risk is too high for Class I or II controls, De Novo is not a substitute for PMA.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.When an AI product becomes PMA-level risk
AI does not have a single “PMA threshold.” PMA becomes relevant when the device is high risk, generally Class III, or when general and special controls cannot adequately control the risks. The analysis should focus on the consequences of failure and the ability of controls and evidence to provide reasonable assurance of safety and effectiveness.
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- Dependence: Is the output a critical determinant of diagnosis or treatment rather than one input to professional judgment?
- Controllability: Can labeling, user training, workflow safeguards, performance limits, and other controls adequately reduce the risk?
- Evidence: Can the proposed evidence support the device’s own safety and effectiveness, not merely show that a related product works?
These questions do not assign a classification by themselves. They provide a disciplined way to explain why a product belongs in a comparative 510(k) analysis, a novel-device De Novo request, or an independent PMA review.
What happens if FDA says “not substantially equivalent”?
An NSE determination ends that particular 510(k) route for the submission as filed, but it does not leave the sponsor without options. Depending on the facts, the sponsor can:
- Submit another 510(k) with a different predicate analysis, revised device or claims, or additional evidence.
- Request De Novo classification if the device is novel and its risks can be controlled as Class I or II.
- Petition for reclassification.
- Submit a PMA when the device is high risk or cannot be adequately controlled by general and special controls.
The appropriate response depends on why FDA found the device not substantially equivalent. An NSE based on an inadequate comparison is a different problem from one indicating that the device raises new questions or presents risk beyond Class I or II controls.
Managing AI changes after clearance or approval
AI-enabled devices may change after the initial marketing decision. FDA’s AI/ML lifecycle framework treats modifications that could significantly affect safety or effectiveness as potentially requiring a new submission or supplement. The relevant question is not whether a change is called an “update,” but whether it can alter the device’s performance, risk profile, intended use, or user interpretation.
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Common pathway mistakes and how to correct them
“It uses AI, so it must be PMA.”
Correction: FDA reviews AI-enabled software through 510(k), De Novo, PMA, and other applicable premarket pathways. Start with intended use, predicate availability, risk, and controls.
“Any similar device is a predicate.”
Correction: A 510(k) depends on a legally marketed predicate and a supportable substantial-equivalence comparison. Similar branding, data type, or market does not establish predicate status.
“A non-AI predicate cannot support an AI device.”
Correction: It can, when intended use is the same, technological differences do not introduce different safety or effectiveness questions, and the remaining 510(k) requirements are met.
“De Novo means no clinical or technical evidence is needed.”
Correction: De Novo still requires enough information for FDA to understand the device’s risks and establish Class I or II controls.
“A predicate’s evidence proves my device is safe.”
Correction: Predicate evidence supports a comparative 510(k) argument. PMA requires an independent demonstration for the device under review, and every pathway requires evidence appropriate to the device’s own claims and risks.
“Model updates are automatically outside the original review.”
Correction: Changes that could significantly affect safety or effectiveness may require a new submission or supplement. Define the change-control and validation approach before deployment.
Illustrative pathway patterns
AI assistance with an established use
Suppose software analyzes the same type of clinical input and supports the same user decision as a legally marketed device, while adding an algorithmic function. A 510(k) analysis may be possible if the intended use remains the same, the AI difference does not create different safety or effectiveness questions, and performance testing addresses the new function.
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Suppose a product introduces a device function for which no legally marketed predicate exists, but the hazards can be addressed through defined performance requirements, user safeguards, labeling, and other general and special controls at Class I or II. De Novo may be the appropriate classification route.
High-consequence autonomous function
Suppose the device’s intended use and risk profile are high enough that general and special controls cannot provide adequate assurance. The sponsor would need to evaluate PMA, with valid scientific evidence addressing the safety and effectiveness of that specific device and intended use.
The decision in one sentence
Use 510(k) for defensible substantial equivalence, De Novo for a novel device whose risks can be controlled as Class I or II, and PMA for high-risk devices requiring an independent safety-and-effectiveness showing; treat AI as part of the device’s technology and lifecycle, not as a standalone regulatory category.
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