Insights into the US Food and Drug Administration’s (FDA) evolving regulatory framework for Artificial Intelligence, Machine Learning and Software as a Medical Device (SaMD)

It is no secret that the digital health industry is continuing to expand at an explosive rate and that companies in this field are experiencing a once in a lifetime opportunity at true disruption. The digital transformation of healthcare is real and picking up speed as an increasing number of stakeholders come to understand the benefits it can provide to all ecosystem participants. 

At the heart of attempting to manage and enable this tsunami of change and innovation while primarily focused on protecting public health by ensuring the safety, efficacy, and security of medical devices is the US Food and Drug Administration, the FDA. 

The US Food and Drug Administration is the world’s foremost health regulatory agency

The FDA is the world’s foremost health regulatory agency as its activities encompass the world’s largest market for medical devices. Cutting edge companies from all over the world creating the most transformative products seek FDA certification as a pathway to entering the US market. Go to market strategies seeking to build medtech companies of substance must include participation in the US market. The FDA also serves as a reference point to regulatory agencies in other countries that don’t have its resources and capabilities and ‘follow its lead’. 

In short, what the FDA does and how they choose to regulate new medical devices and emerging technologies is extremely important for companies in the field since at some point they will likely be seeking their approval. In this article we outline some of the ways the FDA is defining two of the most significant new technologies, Artificial Intelligence and Machine Learning, and the Software as a Medical Device (SaMD) solutions being created with them.

Regulators worldwide are developing new regulatory frameworks to address emerging technologies such as Artificial Intelligence, Machine Learning and Software as a Medical Device (SaMD)

The FDA and regulatory authorities worldwide are facing challenges establishing frameworks for classifying and certifying the torrent of new SaMD solutions being created since in many cases they encompass completely new technology. To illustrate the point in the FDA’s own words: “The FDA’s traditional paradigm of medical device regulation was not designed for adaptive artificial intelligence and machine learning technologies”. The process is evolving in real time and all stakeholders are in learning mode.

We will provide FDA definitions of some of these important technologies, in their own language, and links to useful FDA resources including a list of Artificial Intelligence and Machine Learning (AI/ML)-Enabled Medical Devices.

As stated, artificial intelligence is one of the leading technologies at the core of digital transformation in healthcare. We’ve covered artificial intelligence in healthcare in our Blog and we invite the reader to review that article for a primer on the topic. Artificial intelligence and one of its primary techniques, Machine Learning, are key building blocks for a whole new category of digital health solutions referred to as Software as a Medical Device (SaMD). Here again we are seeing an explosion in the number and types of SaMD solutions being developed to address a wide array of unmet clinical needs in new ways. 

Software as a Medical Device (SaMD)

How Are Artificial Intelligence and Machine Learning Transforming Medical Devices?
Artificial intelligence (AI) and machine learning (ML) 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. One of the greatest benefits of AI/ML in software resides in its ability to learn from real-world use and experience, and its capability to improve its performance.

What is Software as a Medical Device?
Software as a Medical Device is defined by the International Medical Device Regulators Forum (IMDRF) as “software intended to be used for one or more medical purposes that perform these purposes without being part of a hardware medical device”. The International Medical Device Regulators Forum (IMDRF)  is a voluntary group of medical device regulators from around the world who have come together to reach harmonization on medical device regulation.

What are examples of Software as a Medical Device?
Software as a Medical Device ranges from software that allows a smartphone to view images obtained from a magnetic resonance imaging (MRI) medical device for diagnostic purposes to Computer-Aided Detection (CAD) software that performs image post-processing to help detect breast cancer.

Software as a Medical Device may be interfaced with other medical devices, including hardware medical devices, and other software as a medical device software, as well as general purpose software. For example, treatment planning software that supplies information used in a linear accelerator is Software as a Medical Device.

Software with a medical purpose that operates on a general purpose computing platform, i.e., a computing platform that does not have a medical purpose, is considered Software as a Medical Device. For example, software that is intended for diagnosis of a condition using the tri-axial accelerometer that operates on the embedded processor on a consumer digital camera is considered Software as a Medical Device.

How are Regulators Addressing the Challenges with Software as a Medical Device?
Regulators across the globe recognized the need to converge on a common framework and principles for Software as a Medical Device that enables all stakeholders, including regulators, to promote safe innovation and protect patient safety, thus the IMDRF.

Chaired by the FDA, the Software as a Medical Device IMDRF working group agreed upon Software as a Medical Device:

Artificial Intelligence and Machine Learning (AI/ML) Software as a Medical Device Action Plan
The U.S. Food and Drug Administration (FDA) issued the “Artificial Intelligence/Machine Learning (AI/ML)-Based Software as a Medical Device (SaMD) Action Plan” from the Center for Devices and Radiological Health’s Digital Health Center of Excellence.

The Action Plan is a direct response to stakeholder feedback to an April 2019 discussion paper: “Proposed Regulatory Framework for Modifications to Artificial Intelligence/Machine Learning-Based Software as a Medical Device” and outlines five actions the FDA intends to take.

Download the Artificial Intelligence and Machine Learning (AI/ML) Software as a Medical Device Action Plan here.

Good Machine Learning Practice for Medical Device Development: Guiding Principles
The U.S. Food and Drug Administration (FDA), Health Canada, and the United Kingdom’s Medicines and Healthcare products Regulatory Agency (MHRA) have jointly identified 10 guiding principles that can inform the development of Good Machine Learning Practice (GMLP).

These 10 guiding principles will help promote safe, effective, and high-quality medical devices that use artificial intelligence and machine learning (AI/ML).
To view the 10 guiding principles in Good Machine Learning Practice (GMLP) click here.

List of Artificial Intelligence and Machine Learning (AI/ML) Enabled Medical Devices
Over the past decade, the FDA has reviewed and authorized a growing number of devices legally marketed (via 510(k) clearance, granted De Novo request, or approved PMA) with ML across many different fields of medicine—and expects this trend to continue.

The FDA is providing this list of AI/ML enabled medical devices marketed in the United States as a resource to the public about these devices and the FDA’s work in this area.
To view the complete list click here.

It is imperative for organizations developing the digital health solutions of tomorrow to understand the regulators, such as the FDA, Health Canada or whichever may apply in their jurisdiction, and the regulatory frameworks they will employ to assess new digital health solutions, particularly in the context of an evolving environment as regulators come to terms with how to manage emerging technologies.

We cannot state emphatically enough how important it is for firms developing medical technology in this complex environment, and medtech startups in particular due to their short runways and high cash burns, to work with regulatory affairs experts that understand this ecosystem and can help them to navigate it successfully. Even with great ideas, significant funding and superior technology, most digital health startups find themselves in over their heads when faced with the safety and efficacy requirements of a regulated industry. Don’t let it happen to your firm.


About BML Technology 

BML Technology understands digital health. At the intersection of medical technology, clinical research and patient-centric healthcare BML drives the mainstream adoption of digital technology in healthcare. Offering a full range of services to the digital health ecosystem BML manages the complex stakeholder interactions necessary to get digital health solutions to market and gain adoption.

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BML Technology

At the intersection of medical technology, clinical research and patient-centric health care, we manage the complex stakeholder interactions necessary to get digital health solutions to market and gain adoption.