The Breakthrough Devices Program replaces the Expedited Access Pathway and Priority Review for medical devices. The FDA considers devices granted designation under the Expedited Access Pathway to be part of the Breakthrough Devices Program.
Devices subject to premarket approval applications (PMAs), premarket notification (510(k)) or requests for De Novo designation are eligible for breakthrough device designation if both of the following criteria are met:
Criteria | Description | Refer to Guidance |
---|
First Criterion | The device provides for more effective treatment or diagnosis of life-threatening or irreversibly debilitating human disease or conditions | Section III.B.1 |
Second Criterion | The device also meets at least one of the following: |
|
- Represents Breakthrough Technology
| Section III.B.2.a |
- No Approved or Cleared Alternatives Exist
| Section III.B.2.b |
- Offers Significant Advantages over Existing Approved or Cleared Alternatives
| Section III.B.2.c |
- Device Availability is in the Best Interest of Patients
| Section III.B.2.d |
Artificial intelligence treated as a medical device:https://www.fda.gov/medical-devices/software-medical-device-samd/artificial-intelligence-and-machine-learning-software-medical-deviceArtificial intelligence and machine learning technologies have the potential to transform health care by deriving new and important insights from the vast amount of data generated during the delivery of health care every day. Medical device manufacturers are using these technologies to innovate their products to better assist health care providers and improve patient care.
The FDA’s Center for Devices and Radiological Health (CDRH) is considering a total product lifecycle-based regulatory framework for these technologies that would allow for modifications to be made from real-world learning and adaptation, while ensuring that the safety and effectiveness of the software as a medical device are maintained.
How Is the FDA Considering Regulation of Artificial Intelligence and Machine Learning Medical Devices?
Traditionally, the FDA reviews medical devices through an appropriate premarket pathway, such aspremarket clearance (510(k)),De Novo classification, orpremarket approval. The FDA may also review and clear modifications to medical devices, including software as a medical device, depending on the significance or risk posed to patients of that modification.Learn the current FDA guidance for risk-based approach for 510(k) software modifications.
The FDA’s traditional paradigm of medical device regulation was not designed for adaptive artificial intelligence and machine learning technologies. Under the FDA’s current approach to software modifications, the FDA anticipates that many of these artificial intelligence and machine learning-driven software changes to a device may need a premarket review.
On April 2, 2019, the FDA published a discussion paper “Proposed Regulatory Framework for Modifications to Artificial Intelligence/Machine Learning (AI/ML)-Based Software as a Medical Device (SaMD) - Discussion Paper and Request for Feedback” that describes the FDA’s foundation for a potential approach to premarket review for artificial intelligence and machine learning-driven software modifications.
The ideas described in the discussion paper leverage practices from our current premarket programs and rely onIMDRF’srisk categorization principles, the FDA’s benefit-risk framework, risk management principles described in thesoftware modifications guidance, and the organization-based total product lifecycle approach (also envisioned in theDigital Health Software Precertification (Pre-Cert) Program).
In the framework described in the discussion paper, the FDA envisions a “predetermined change control plan” in premarket submissions. This plan would include the types of anticipated modifications—referred to as the “Software as a Medical Device Pre-Specifications”—and the associated methodology being used to implement those changes in a controlled manner that manages risks to patients —referred to as the “Algorithm Change Protocol.”
In this potential approach, the FDA would expect a commitment from manufacturers on transparency and real-world performance monitoring for artificial intelligence and machine learning-based software as a medical device, as well as periodic updates to the FDA on what changes were implemented as part of the approved pre-specifications and the algorithm change protocol.
Such a regulatory framework could enable the FDA and manufacturers to evaluate and monitor a software product from its premarket development to postmarket performance. This approach could allow for the FDA’s regulatory oversight to embrace the iterative improvement power of artificial intelligence and machine learning-based software as a medical device, while assuring patient safety.
As part of the AI/ML Action Plan, the FDA is highlighting its intention to develop an update to the proposed regulatory framework presented in the AI/ML-based SaMD discussion paper, including through the issuance of a draft guidance on the predetermined change control plan.
Medical device approval process:
https://www.qualio.com/blog/fda-medical-device-approval-processHow Long Does the FDA Medical Device Approval Process Take?
The FDA approval process can take between one week and eight months, depending on whether you self-register, submit a 510(k) application, or submit a Premarket Approval (PMA) application. Bringing a medical device to market is not a fast process. Studies reveal it takesthree to seven years in total from concept to approval, compared to an average of 12 years for drugs. However, this figure is an inclusive measure of the entire device lifecycle, including research & development and testing.
It’s never too early to begin preparing for an FDA submission. The most effective way to predict speed-to-market is to evaluate the level of risk associated with your medical device and determine if it is a Class 1, 2, or 3 device. There are three possible pathways to market approval:
- Self-registration
- 510(k) submissions
- Premarket Approval
To understand device classification, we recommend:What are the Differences in the FDA Medical Device Categories?
Class 1 Devices
Most Class 1 devices are exempt from the 510(k) clearance pathway, per the agency. The majority of devices that are already approved for sale fall under Class 1 and present the lowest risk to patients. Class 1 devices include non-invasive items such as tongue depressors, oxygen masks, and electric toothbrushes.
Learn more inDoes an FDA Class 1 Medical Device List Exist?
While a small percentage of Class 1 devices require a 510(k) submission, the majority can be self-registered with the agency. This is a three-step process, explained in-depthon the FDA website.
- Pay the registration fee.
- Electronically submit listing and registration info.
- Receive an email of acceptance from the FDA.
These steps cannot be completed simultaneously. Generally, it takes “several days” for aDevice User Facility Registration feeto be accepted by the agency before you can electronically submit your registration. The agency’s FAQ does not address the average length of time between electronic registration submission and acceptance.
While the self-registration process for Class 1 devices isn’t instantaneous, it’s by far the fastest path to market and shouldn’t involve any long wait times. You may be able to complete device registration in one week.
Class 2 Devices
43% of medical device applications fall under Class 2. This moderate-risk category includes devices such as contact lenses, syringes, and catheters. According to the agency, the majority of Class 2 medical devices require a510(k) application, in which the manufacturer demonstrates a device’s safety and efficacy through substantial equivalence to another currently approved device.
How to Shorten the FDA Medical Device Approval Process
Device class and approval pathway have a huge impact on the average length to wait for the FDA medical device approval process to complete. But is there anything you can control to speed up time-to-market? Your average wait can depend on how well you write your submission for any Class of device, and how well you “tick all the boxes” for your product by demonstrating substantial equivalence or proving safety and efficacy.
Remember, the FDA is collaborative if you let them be a partner. They want to bring innovative, safe devices to market quickly, and they’ve made themselves more accessible to speed up approvals. If you take the old school approach of doing the bare minimum based on your assumptions, you’ll get stuck. As soon as you break the FDA’s trust in your intentions, they’ll throw the book at you. Be open, collaborative, and take advantage of their newer “interactive” review approach.
It’s never too early to begin preparing for successful submission. This starts with a comprehensive quality management system and effective document management practices. This groundwork is essential to quickly create an effective application for any FDA approval pathway.
Alcohol breathalyser class:https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfPCD/classification.cfm?ID=DJZ
Covid breathalyser example of FDA Class 1 device
https://www.medicaldevice-network.com/features/coronavirus-timeline/
Integumen recognised that in collaboration with Modern Water, Avacta and Aptamer Group, its real-time detection and alert system could be adapted to detect the level of infection of Coronavirus in a breath sample. Adapting the wastewater test,
Microtox PD, the company has designed, built and tested a prototype, Microtox BT, which can analyse the breath and detect the spike protein of SARS-CoV-2 in real-time for those with a high viral load.
Microtox BT has undergone internal testing and will now transition to the University of Aberdeen containment level 3 laboratory, to undergo tests directly on the virus followed by a joint trial of up to 5,000 participants in parallel with third parties using reverse transcription polymerase chain reaction (“rtPCR”) and antigen tests. Results are anticipated before the end of the year and
Microtox BT is expected to be a Class 1 medical device.