Life Sciences

The information age in which we live is reaching a new milestone with the development and ready access to conversational artificial intelligence based on advanced transformer algorithms, or AI chatbots, including their upcoming integration into multiple Internet search engines. This development creates exciting opportunities and potentially terrifying risks in the health care space. Inevitably, people will ask AI chatbot-enabled search engines for information on diseases, conditions, medicines, or medical devices and use the response in some way to make certain medical decisions. But what happens when the AI chatbot’s response is inaccurate or even provides advice that may lead to harm if the user follows it? Can AI chatbots be regulated by the U.S. Food and Drug Administration (FDA)? What are the liability implications if a user is harmed? We provide some initial thoughts on such legal issues in this post.

There has been a lot of discussion of the Food and Drug Omnibus Reform Act of 2022 (FDORA), which was enacted on December 29, 2022 as part of the larger Consolidated Appropriations Act for 2023, but we should also take a moment to review last year’s actions and policy updates on digital health from the Food and Drug Administration (FDA). The year 2022 marked the conclusion of the five-year Software Precertification Pilot Program and the release of the final Clinical Decision Support Software guidance, among other things (both described below); however, major digital health policy updates and announcements were few and far between. In this post, we summarize the agency’s key actions in the digital health space in 2022.

The Food and Drug Administration (FDA) issued a guidance on development and emergency use authorization of diagnostic and serological tests for the monkeypox virus following the Secretary of the Department of Health and Human Service’s declaration of a public health emergency under Section 564 of the Food, Drug and Cosmetic Act on August 9, 2022. Subsequently, the Secretary declared on September 7 that in vitro diagnostics for monkeypox were needed to respond to the public health emergency, and the FDA released its guidance on the same day. The monkeypox test guidance describes the agency’s general expectations and approach for test development and validation, as well as the EUA request process.

The U.S. Food and Drug Administration (FDA) will schedule a public meeting of the Medical Devices Advisory Committee later this year to discuss study results, real-world data, and other evidence concerning the accuracy and performance of pulse oximeters. The planned meeting is consistent with the agency’s recent efforts to evaluate the need for and options to address transparency and diversity in the design and development of artificial intelligence/machine learning (AI/ML) based software devices (see our post covering FDA’s Transparency of AI/ML Enabled Medical Devices Workshop) and in clinical trial design. It is unclear whether or how the outcome of the planned meeting on pulse oximeters will affect prescription and over-the-counter (OTC) pulse oximeters currently on the market, but it is possible that the meeting could lead FDA to impose new testing or labeling requirements for pulse oximeters, and perhaps even other devices that use light-based sensors to evaluate certain biometrics.

Anyone who has spent any time around health care policymaking circles in Washington, D.C. has heard about the intense five-year cycle Congress goes through in order to reauthorize the biggest user fee programs at the Food and Drug Administration (FDA). Mintz previously published this wonderful explanation of the process complete with an estimated timeline for how this year’s reauthorization was likely to go. As a reminder, the current authorization for FDA’s various human product user fee programs – with the exception of the over-the-counter drug program that was freshly created in 2020 – will expire on September 30, 2022 with the end of the federal government’s fiscal year, unless they are renewed by Congress before that time.

As the COVID-19 public health emergency drags into its third year, we continue to keep track of efforts by the Food and Drug Administration (FDA) to combat fraud in the form of fake cures, counterfeit diagnostic tests, and other products claiming to prevent, treat, or detect infection by SARS-CoV-2 that are marketed without required FDA authorization. Our previous posts provided updates on joint and separate efforts by FDA and the U.S. Federal Trade Commission (FTC) throughout the pandemic to detect and eliminate these illegal products. In this post, we focus on FDA’s recent enforcement activities concerning COVID-19 diagnostic tests and the agency’s increasingly aggressive pursuit of entities offering counterfeit or unauthorized tests.

Public and private life science companies have multiple options available for capital-raising. Here are a few to be considered.

In 2021, approximately on quarter of all federal securities fraud class action lawsuits filed nationwide were against life sciences companies and their officers and directors. These considerations are for directors and officers of life sciences companies looking to manage disclosures and mitigate risk before a suit ever gets filed.

We previously discussed which portions of an artificial intelligence/machine-learning (“AI/ML”) platform can be patented.  Under what circumstances, however, is it best to keep at least a portion of the platform a trade secret? And what are some best practices for protecting trade secrets? In this post, we explore important considerations and essential business practices to keep in mind when working to protect the value of trade secrets specific to AI/ML platforms, as well as the pros and cons of trade secret versus patent protection.

Earlier this month, in Novartis Pharms. Corp., Inc. v. Accord Healthcare, Inc., et al., No. 2021-1070, the Federal Circuit issued a helpful decision concerning the not-often-discussed written description requirement. The panel specifically addressed whether sufficient written description can exist for claim limitations that are not explicitly or directly disclosed in the specification (including negative claim limitations). This new ruling provides patent owners with a useful guide for successfully navigating similar written description challenges in patent infringement cases. For example, Patent Owners seeking to combat written description requirement challenges should proffer expert witnesses who can clearly articulate how they understand the patent description in relation to the claims and what portions of that description support the same.

Joe Payne, CEO of Arcturus Therapeutics, discusses his company’s focus on developing next-generation mRNA vaccines and therapies, his current areas of focus as head of the company, the importance of moving forward through the pandemic, and the most frequently asked question he gets about the company.

In the weeks leading up to FDA’s October 14, 2021 Transparency of AI/ML Enabled Medical Devices Workshop (Workshop) we took a brief look at the history of FDA’s regulation of medical device software and the agency’s more recent efforts in regulating digital health. In this post, we will provide an overview of the topics discussed at the Workshop and our impressions of the agency’s likely next steps.

In our last post, we took a brief look back through history at FDA’s approach to regulating medical device software and found that there is little distinction from the agency’s approach to hardware devices. Recently, however, FDA has announced several digital health initiatives aimed at improving the agency’s resources and policies governing software and data systems (including its own internal data systems) and changing the way the agency handles pre-market reviews of and compliance activities for software as a medical device (SaMD) and SaMD manufacturers. In this post, we will review FDA’s digital health improvement highlights from the past few years and take a quick look at the agenda for the transparency of AI/ML-enabled medical devices workshop scheduled for October 14, 2021.

In anticipation of FDA’s virtual public workshop on transparency of artificial intelligence/machine learning (AI/ML)-enabled medical devices scheduled for October 14, 2021, we will be posting a series detailing the history behind FDA’s regulation of software and then reporting our impressions of FDA’s presentations and statements from various attending stakeholders following meeting. In this part, we briefly summarize FDA’s traditional approach to regulating software and how software development quickly revealed the limitations of the original regulatory framework established in the 1976 Medical Device Amendments to the Federal Food, Drug, and Cosmetic Act (FD&C Act).

In a recent IAM article, Levelling the playing field in ITC patent cases by identifying redesigns to a set deadline, we commented on best practices for ITC complainants to protect their interests against the nascent uptick of redesign submissions at the tail end of fact discovery. Although reasonable minds can differ as to whether the uptick in motion practice is coincidence or a more troubling sign that some respondents are using late redesign disclosures as a vehicle to put complainants at a disadvantage in fast-paced Section 337 proceedings, such late disclosures undoubtedly prejudice complainants’ ability to fully review and assess such disclosures for possible infringement.

In what appears to be a case of first impression, on August 23, 2021 U.S. District Judge John Z. Lee of the United States District Court for the Northern District of Illinois denied a biosimilar applicant’s motion to dismiss a patent infringement suit brought under the Biosimilar Price Competition and Innovation Act (“BPCIA”) against a foreign parent corporation that did not file or sign the relevant abbreviated Biologics License Application (“aBLA”).

This edition covers return-to-work challenges, insight on patenting AI innovations, FDA guidance on medical devices, transactional and IP activity in the life sciences, and recent Mintz work for life sciences clients.