This is the third of our video posts on 10 questions that can help lawyers contribute to the digital health ideation process. Today’s video explores the question: who will provide the data used in the offering?
This is the second of our video posts on 10 questions that can help lawyers contribute to the digital health ideation process. Today’s video explores the question: who will provide the various components of the offering?
Our clients increasingly apply agile product and business development methodologies when they are developing digital health solutions. “Ideation” is the part of that process and involves the rapid identification and creation of ideas for digital health solutions, which are then prototyped and tested. Covington has created a Top 10 Questions for Ideation of Digital Health…
Last week, Senators Amy Klobuchar (D-MN) and Lisa Murkowski (R-AK) introduced the Protecting Personal Health Data Act (S. 1842), which would provide new privacy and security rules from the Department of Health and Human Services (“HHS”) for technologies that collect personal health data, such as wearable fitness trackers, social-media sites focused on health…
On Friday, April 19, 2019, the Office for Civil Rights of the U.S. Department of Health and Human Services (HHS) explained in an FAQ the circumstances under which electronic health record (EHR) systems may be subject to the Health Insurance Portability and Accountability Act of 1996 (HIPAA) liability for an app’s impermissible use or disclosure…
On April 2, 2019, FDA released a discussion paper entitled “Regulatory Framework for Modifications to Artificial Intelligence/Machine Learning (AI/ML)-Based Software as a Medical Device (SaMD)” (the “AI Framework”). The AI Framework is the Agency’s first policy document describing a potential regulatory approach for medical devices that use artificial intelligence (“AI”) and machine learning (“ML”). The AI Framework does not establish new requirements or an official policy, but rather was released by FDA to seek early input prior to the development of a draft guidance. FDA acknowledges that the approach “may require additional statutory authority to implement fully.”
In an accompanying press release, former FDA Commissioner Scott Gottlieb outlined the need for a “more tailored” regulatory paradigm for algorithms that learn and adapt in the real world. FDA’s medical device regulation scheme was not designed for dynamic machine learning algorithms, as the Agency traditionally encounters products that are static at the time of FDA review. The AI Framework is FDA’s attempt to develop “an appropriate framework that allows the software to evolve in ways to improve its performance while ensuring that changes meet [FDA’s] gold standard for safety and effectiveness throughout the product’s lifecycle.”…
Continue Reading FDA Outlines Proposed Framework for Regulating Artificial Intelligence Software
On December 7, FDA published the much-anticipated “Framework for FDA’s Real-World Evidence Program” for drugs and biological products (the “Framework”). In a statement announcing the Framework, Commissioner Gottlieb recognized the opportunities and challenges of using real-world data (“RWD”) and real-world evidence (“RWE”) to enhance regulatory decision-making and noted that leveraging this information is “a top strategic priority for the FDA.” FDA opened a docket for public comments on the Framework through February 5, 2019.
The Framework focuses in particular on the use of RWE to support regulatory decisions about effectiveness. The agency outlines three considerations that will guide its overall RWE Program and inform the agency’s assessment of individual drug applications. The Framework also offers background on the agency’s previous use and current initiatives with respect to RWE and related topics, such as innovative clinical trial designs. This blog post provides an overview of FDA’s proposal and highlights a few initial takeaways noted by Covington’s Digital Health team.…
As previewed by Commissioner Gottlieb several months ago (see our earlier post here), FDA published a notice in the Federal Register on November 20, 2018, to propose a new framework for “prescription drug-use-related software.” The Agency defines this digital health category widely as software disseminated by a prescription drug sponsor for use with the sponsor’s prescription drug(s). Last spring, the Commissioner stated that FDA would be seeking input “on how to support the development of digital health tools that are included as part of approved drugs.” The goal in establishing the framework, Gottlieb stated, would be “to develop an efficient pathway for the review and approval of digital health tools as part of drug review, so that these tools reach their full potential to help us treat illness and disease, and encourage synergies between software and therapeutics that meet FDA’s gold standard for safety and effectiveness.”
This policy development is significant, not only because it is one of CDER’s first policy statements on digital health associated with pharmaceuticals (see a few of our earlier posts about pharma-related digital health here and here), but also because it implicates a broad range of information that could be made available by prescription drug sponsors through software used with their products. We encourage prescription drug sponsors with any interest in providing digital health solutions, including through collaborations, to review the Federal Register notice and consider submitting comments to FDA.
Here are a few key takeaways from FDA’s notice:
- Under the proposed framework, software with the same drug-related functionalities will be subject to different regulatory approaches by FDA, depending on the developer of the software. FDA will apply the proposed framework to prescription drug-user-related software developed by or on behalf of pharmaceutical manufacturers, and a different approach to drug-related software developed “independently” by third-party software developers and other entities that are not prescription drug sponsors.
- It is unclear from the notice how the proposed framework, including the evidentiary standards described in the Federal Register notice, will align with other FDA initiatives such as the use of real-world evidence for drug development and the pre-certification program (see our earlier post here).
- An important question for prescription drug sponsors in particular is whether the proposed framework will encourage continued digital health innovation, including through collaborations, or whether FDA’s proposal will create challenges that may discourage advances in this area.
Designing data-driven products and services in compliance with privacy requirements can be a challenging process. Technological innovation enables novel uses of personal data, and companies designing new data-driven products must navigate new, untested, and sometimes unclear requirements of privacy laws, including the General Data Protection Regulation (GDPR). These challenges are often particularly acute for companies providing products and services leveraging artificial intelligence technologies, or operating with sensitive personal data, such as digital health products and services.
Recognising some of the above challenges, the Information Commissioner’s Office (ICO) has commenced a consultation on establishing a “regulatory sandbox”. The first stage is a survey to gather market views on how such a regulatory sandbox may work (Survey). Interested organisations have until 12 October to reply.
The key feature of the regulatory sandbox is to allow companies to test ideas, services and business models without risk of enforcement and in a manner that facilitates greater engagement between industry and the ICO as new products and services are being developed.
Potential benefits of the regulatory sandbox include reducing regulatory uncertainty, enabling more products to be brought to market, and reducing the time of doing so, while ensuring appropriate protections are in place (see the FCA’s report on its regulatory sandbox here for the impact it has had on the financial services sector, including lessons learned).
The ICO indicated earlier this year that it intends to launch the regulatory sandbox in 2019 and will focus on AI applications (see here).
Further details on the scope of the Survey are summarised below.…
On 5 September, in response to the opportunities presented by data-driven innovations, apps, clinician decision support tools, electronic health care records and advances in technology such as artificial intelligence, the UK Government published a draft “Initial code of conduct for data-driven health and care technology” (Code) for consultation. The Code is designed to be supplementary to the Data Ethics Framework, published by the Department for Digital, Culture, Media and Sport on 30 August, which guides appropriate data use in the public sector. The Code demonstrates a willingness of the UK Government to support data sharing to take advantage of new technologies to improve outcomes for patients and accelerate medical breakthroughs, while balancing key privacy principles enshrined in the GDPR and emerging issues such as the validation and monitoring of algorithm-based technologies. For parties considering data-driven digital health projects, the Code provides a framework to help conceptualise a commercial strategy before engaging with legal teams.
The Code contains:
- a set of ten principles for safe and effective digital innovations; and
- five commitments from Government to ensure the health and care system is ready and able to adopt new technologies at scale,
each of which are listed further below.
While the full text of the Code will be of interest to all those operating in the digital health space, the following points are of particular note:
- the UK Government recognises the “immense promise” that data sharing has for improving the NHS and social care system as well as for developing new treatments and medical breakthroughs;
- the UK Government is committed to the safe use of data to improve outcomes of patients;
- the Code intends to provide the basis for the health and care system and suppliers of digital technology to enter into commercial terms in which the benefits of the partnerships between technology companies and health and care providers are shared fairly (see further below); and
- given the need of artificial intelligence for large datasets to function, two key challenges arise: (i) these datasets must be defined and structured in accordance with interoperable standards, and (ii) from an ethical and legal standpoint, people must be able to trust that data is used appropriately, safely and securely as the benefits of data sharing rely upon public confidence in the appropriate and effective use of data.
The Code provides sets out a number of factors consider before engaging with legal teams to help define a commercial strategy for data-driven digital health project. These factors include: considering the scope of the project, term, value, compliance obligations and responsibilities, IP, liability and risk allocation, transparency, management of potential bias in algorithms, the ability of the NHS to add value, and defining the respective roles of the parties (which will require thinking beyond traditional research collaboration models).
Considering how value is created and realised is a key aspect of any data-driven digital health project, the Code identifies a number of potential options: simple royalties, reduced payments for commercial products, equity shares in business, improved datasets – but there is also no simple of single answer. Members of Covington’s digital health group have advised on numerous data-driven collaborations in the healthcare sector. Covington recently advised UK healthcare technology company Sensyne Health plc on pioneering strategic research and data processing agreements with three NHS Trust partners. Financial returns generated by Sensyne Health are shared with its NHS Trust partners via equity ownership in Sensyne Health and a share of royalties (further details are available here).
The UK Government also intends to conduct a formal review of the regulatory framework and assessing the commercial models used in technology partnerships in order to address issues such as bias, transparency, liability and accountability.
The UK Government is currently consulting on the Code (a questionnaire on the Code is available here) and intends to publish a final version of the Code in December.…