artificial intelligence

In April 2019, the US Food and Drug Administration (FDA) issued a white paper, “Proposed Regulatory Framework for Modifications to Artificial Intelligence/Machine Learning (AI/ML)-Based Software as a Medical Device,” announcing steps to consider a new regulatory framework to promote the development of safe and effective medical devices that use advanced AI algorithms. AI, and specifically ML, are “techniques used to design and train software algorithms to learn from and act on data.” FDA’s proposed approach would allow modifications to algorithms to be made from real-world learning and adaptation that accommodates the iterative nature of AI products while ensuring FDA’s standards for safety and effectiveness are maintained.

Under the existing framework, a premarket submission (i.e., a 510(k)) would be required if the AI/ML software modification significantly affects device performance or the device’s safety and effectiveness; the modification is to the device’s intended use; or the modification introduces a major change to the software as a medical device (SaMD) algorithm. In the case of a PMA-approved SaMD, a PMA supplement would be required for changes that affect safety or effectiveness. FDA noted that adaptive AI/ML technologies require a new total product lifecycle (TPLC) regulatory approach and focuses on three types of modifications to AI/ML-based SaMD:


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As part of the 21st Century Cures Act, Congress gave the US Food and Drug Administration (FDA) the authority to establish a Breakthrough Devices Program intended to expedite the development and prioritize the review of certain medical devices that provide for more effective treatment or diagnosis of life-threatening or irreversibly debilitating disease or conditions. In December 2018, FDA issued a guidance document describing policies FDA intends to use to implement the Program.

There are two criteria for inclusion in the Breakthrough Device Program:

  1. The device must provide for a more effective treatment or diagnosis of a life-threatening or irreversibly debilitating human disease or condition; and
  2. The device must (i) represent breakthrough technology, (ii) have no approved or cleared alternatives, (iii) offer significant advantages over existing approved or cleared alternatives, or (iv) demonstrate that its availability is in the best interest of patients.


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Investment in artificial intelligence (AI) and digital health technologies has increased exponentially over the last few years. In the United Kingdom, the excitement and interest in this space has been supported by NHS policies, including proposals in the NHS Long Term Plan, which set out ambitious aims for the acceleration and adoption of digital health and AI, particularly in primary care, outpatients and wearable devices.

Although these developments are encouraging to developers, there is still no clear framework for reimbursement or tariffs for digital health tools and AI.

At the same time, the plethora of new technologies has led to increased calls for regulation and oversight, particularly around data quality and evaluation. Many of these concerns may be addressed by the new Medical Device Regulation (MDR) and other regulatory developments. In fact, there is some risk that while regulatory landscape is moving quickly, the pricing environment is still a way behind.

In May 2020, the new MDR will change the law and process of certification for medical software. The new law includes significant changes for digital health technologies which are medical devices. In March 2019, the National Institute for Health and Care Excellence (NICE) also published a new evidence standards framework for digital health technologies. The Care Quality Commission (CQC) already regulates online provision of health care, and there are calls for wider and greater regulation. The government has also published a code on the use of data in AI.

Digital Health Technologies and the MDR

The new MDR will mean a significant change to the regulatory framework for medical devices in the European Union.

As with the previous law, the MDR regulates devices through a classification system.

The new regime introduces new rules for medical software that falls within the definition of device. This will mean significant changes for companies that develop or offer medical software solutions, especially if their current certification has been “up-classed” under the MDR.

Key Takeaways for Investors in Digital Health Tools

Companies and investors in digital health should:

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Join McDermott next Wednesday for a live webinar on the unique considerations in developing and procuring AI solutions for digital health applications from the perspective of various stakeholders. We will discuss the legal issues and strategies surrounding:

  • Research and data mapping essential to the development and validation of AI technologies
  • Protecting and maintaining intellectual property

Fortune’s April 2018 cover story, “Tech’s Next Big Wave: Big Data Meets Biology,” conveys loudly and clearly that technological innovation is transforming the health care continuum—changing the way care is delivered, as well as how patients manage their ongoing health—and as patient demand for health innovation increases, more companies seem eager to hop on

Designed to provide business leaders and their key advisors with the knowledge and insight they need to grow and sustain successful digital health initiatives, we are pleased to present The Law of Digital Health, a new book edited and authored by McDermott’s team of distinguished digital health lawyers, and published by AHLA.

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As digital health innovation continues to move at light speed, both new and incumbent stakeholders find themselves on a new frontier—one that challenges traditional health care delivery and payment frameworks, in addition to changing the landscape for product research, development and commercialization. Modernization of the existing legal framework has not kept pace with the rate of digital health innovation, leaving no shortage of obstacles, misalignment and ambiguity for those in the wake.

What did we learn in 2017 and what’s to come on the digital health frontier in the year ahead? From advances and investments in artificial intelligence (AI) and machine learning (ML) to the increasingly complex conversion of health care innovation and policy, McDermott’s Digital Health Year in Review details the key developments that shaped digital health in 2017, along with planning considerations and predictions for the health care and life science industries in 2018. 
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Stephen Bernstein, global chair of McDermott’s Health Industry Advisory Practice Group, sat down with This Week in Health Innovation at the J.P. Morgan Healthcare Conference in San Francisco.

Stephen and Dr. Andre Berger, CEO of National ACO, discussed the role of advancing technologies in enhancing collaboration between key players in digital health—including doctors, heath plans,

Although the incorporation of technology into human endeavours—commercial, political and personal—is a normal component of technological innovation, the advent of artificial intelligence technology is producing significant challenges we have not felt or understood with earlier innovations. For many years, for example, there has been speculation, research and public debate about the impact of the internet,