Life Sciences

In this sixth post in our series on artificial intelligence in health care, Julie Korostoff highlights the importance of securing adequate data rights to commercialize an AI technology. The post addresses the contractual commitments that a developer of a healthcare AI tool should secure in order to have the data rights necessary for development and commercialization.

Emerging medical imaging technologies being developed for the terahertz spectrum may face regulatory hurdles from an unexpected Federal agency: the Federal Communications Commission (FCC). While the Food and Drug Administration (FDA) has jurisdiction over medical devices with respect to safety and effectiveness – including premarket approval, inspection of manufacturing facilities, and monitoring of post-market adverse events – the FCC has jurisdiction over certain technical and spectrum use requirements for medical devices that operate on radiofrequency (RF) spectrum. Medical device developers need to be aware of the current state of play at the FCC in these areas.

As our use of AI technology becomes more frequent, interconnected, and integral to daily life, the liability exposure to AI product designers and manufacturers continues to escalate. There are more potential liability risks, including product liability risks, in our current environment than ever. With AI technology embedded in interconnected software and hardware products, gone are the days where we can neatly separate data security and privacy from product liability exposure.

There has been a marked increase in the amount of money being invested by Chinese investors into U.S. early stage biotechnology companies since 2017, spurred on by direct encouragement from Beijing through its Made in China 2025 industrial policy, which specifically targets biotech as a strategic industry eligible for greater government backing.

Software developers are racing to develop health care products that leverage artificial intelligence (AI), including machine learning and deep learning. Examples include software that analyzes radiology images and pathology slides to help physicians diagnose disease, electronic health records software that automates routine tasks, and software that analyzes genetic information to support targeted treatment. The one thing that all of these products have in common is a need to interact, in some way, with real world medical data. However, this real world data can be protected by the Health Insurance Portability and Accountability Act of 1996 (HIPAA) as well as a patchwork of federal and state laws and regulations. Below we discuss the contexts in which developers may encounter these laws, as well as strategies to navigate related legal issues.

For much of the past 18 months, the Trump Administration, and in particular CMS, have talked a good game regarding reducing pharmaceutical prices. On October 16, 2018, a key component of the Administration’s strategy was revealed in the form of CMS’ Proposed Rule requiring manufactures to include the “list price” for prescription drugs reimbursable by Medicaid or Medicare in television advertisements. While I do think that there will be new initiatives to address drug pricing, I believe most will come through the state and not the federal level. This post addresses six potential initiatives from a recently released report of the National Governors' Association.

On October 18, 2018, FDA released a new draft guidance, Content of Premarket Submissions for Management of Cybersecurity in Medical Devices, which describes the Agency’s current thinking and recommendations on designing medical device software with adequate cybersecurity controls.  Once finalized, the draft guidance will supersede a final guidance of the same name issued in 2014.

Artificial intelligence—AI—is the future of everything. But when patient health is on the line, can we trust algorithms to make decisions instead of patients or their health care providers? This post, the second in our blog series about AI in health care, explores FDA’s proposed regulatory model that is supposed to be better suited for AI (and similar technologies) while still protecting patients.

In the first new guidance document from FDA in several years specific to the subject of direct-to-consumer (DTC) promotion of prescription drugs and biological products, the Agency is recommending that companies take additional steps to ensure that quantitative efficacy or risk information does not convey inaccurate information and does not have the potential to confuse consumers. The draft guidance defines quantitative efficacy and risk information as “information that numerically addresses the likelihood or magnitude of a drug’s effectiveness or risks.” FDA’s advice on how to most clearly share this type of information should be considered by companies when developing any form of DTC promotional media, whether they are digital, broadcast, in traditional print format, or otherwise.

The Trump Administration is moving full speed ahead with its proposals under the Blueprint to Lower Drug Prices (the “Blueprint”). Earlier this week, the Centers for Medicare & Medicaid Services (“CMS”) released a proposed rule that would require pharmaceutical manufacturers to disclose the list price of their pharmaceutical products in direct-to-consumer (“DTC”) television ads (the “Proposed Rule”).

As in any technology area, it is important to consider patent protection early in the development of an AI-related invention. However, AI inventions raise a number of particular issues that, if not addressed fully or at the right time, could be fatal to securing U.S. patent protection that would otherwise be available to prevent others from making, using, selling, or importing the invention. This article identifies common pitfalls in getting a patent for AI inventions and provides insights on how to avoid them. These principles apply not only to AI-related inventions, but also to digital health inventions more broadly.

The Journal of the American Medical Association in its September 18, 2018, issue included four articles on deep learning and Artificial Intelligence (AI). In one of several viewpoint pieces, On the Prospects for a (Deep) Learning Health Care System, the author’s conclusions aptly describes why health care providers, entrepreneurs, investors and even regulators are so enthusiastic about the use of AI in health care.

Drug and device manufacturers will need to update their reporting systems and provide new training to their sales staff in the coming years based on changes to the Physician Payment Sunshine Act included in the final opioid package passed last week. Beginning with data reported in 2022, the Sunshine Act will cover payments made to advanced practice nurses and physician assistants. The change will also impact state laws requiring the reporting of payments made to these provider types, which will be preempted by federal law.

This week, Congress and the White House need to finalize a government spending bill in order to avoid a shutdown. While all signs point to a deal being reached, it is widely expected that several agencies will be operating on a continuing resolution for the first couple months of fiscal year 2019. While the Departments of Labor, HHS, and Education are expected to receive a full appropriation prior to September 30th, the FDA, which is funded through the Department of Agriculture, is expected to be funded through the continuing resolution, which will go through December 7th.

Over the past couple of years, FDA has introduced multiple programs allowing faster review of medical devices in order to get them to market more quickly. Some of the FDA’s efforts have been highly visible, such as the Breakthrough Devices program in the 21st Century Cures Act and the Software Precertification pilot program in the FDA’s Digital Health Innovation Action Plan. Others have been less trumpeted but are still significant developments for device manufacturers.

In May, the Trump Administration announced its Blueprint to Lower Drug Prices and HHS Secretary Azar issued a Request for Information seeking comments from interested parties “to help shape future policy development and agency action” related to drug pricing issues.

As an immediate follow-up to last week’s release of the FDA’s Biosimilars Action Plan, the Agency is announcing a public hearing for September 4, 2018 to gather stakeholder input on “FDA’s approach to enhancing competition and innovation in the biological products marketplace, including by facilitating greater availability of biosimilar and interchangeable products.”

In the time since the Federal Circuit issued its Vanda Pharma decision in April, Vanda Pharm. Inc. v West-Ward Pharm. Intl. Ltd. 887 F.3d 1117 (Fed. Cir. 2018), we have had more good news for the patent eligibility of claims relating to diagnostic or similar tests utilized in treating patients.

In a highly anticipated step, which had been teased by agency leadership in their public appearances over the past several months, FDA released a series of draft guidance documents pertaining to the development and approval of gene therapy products on July 11, 2018.

Recently the U.S. Department of Justice (DOJ) issued a statement that it had intervened in a False Claims Act (FCA) case against Insys Therapeutics, Inc. and consolidated five separate qui tam cases into one case, U.S. ex rel Guzman v. Insys Therapeutics, Inc., filed in the U.S. District Court for the Central District of California.