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Podcast: Decoding Digital Health: 2021 Developing Trends and Hot Topics in Digital Health


Time to Listen: 21:27 Practices: Digital Health, Health Care, Life Sciences, FDA Regulatory, Intellectual Property Transactions, Data, Privacy & Cybersecurity

The Ropes & Gray Decoding Digital Health podcast series discusses the digital health industry and related legal, business and regulatory issues. In this inaugural episode, the co-leads of the Ropes & Gray Digital Health Initiative, Megan Baca, Kellie Combs and Christine Moundas, take a multidisciplinary approach to exploring trends and hot topics for 2021 related to their transactional, FDA regulatory and health care practices. Many of the topics covered in this initial episode will be further discussed and explored throughout the series, including developments in artificial intelligence, big data and interoperability considerations, as well as regulations and guidance around telehealth, software as a medical device, and use of real-world evidence.

Decoding Digital Health


Transcript:

Kellie CombsKellie Combs: Hello, and welcome to our inaugural episode of Decoding Digital Health, a Ropes & Gray podcast series focused on legal, business, and regulatory updates impacting the digital health market. My name is Kellie Combs, and I am joined today by my co-leads of the Ropes & Gray Digital Health Initiative, Christine Moundas and Megan Baca. Christine, Megan, and I lead the cross-practice Digital Health Initiative, which is a multidisciplinary team of attorneys that advise pharma and biotech, medical device, technology companies, investors, and others on the most pressing issues and cutting-edge matters in the digital health space, which span regulatory, transactional, and litigation issues. On this episode of our podcast, we'll discuss trends that we're seeing in digital health in 2021 across our varying practices. Hi, Christine and Megan—thanks so much for joining us. Why don't we take a minute to first introduce ourselves to our listeners? Megan, would you like to start? 

Megan BacaMegan Baca: Hi, Kellie. Thanks so much. My name is Megan Baca. I am a partner in Ropes & Gray's Silicon Valley office. I have a background in computer science, but my practice spans from life sciences and health care companies to software and technology and consumer branded products. And I specialize in all things related to IP transactions, so I work on licensing and collaborations for big pharma, and many other types of IP transactions for a variety of different industries. I also work on mergers and acquisitions and other investments in companies in the digital health space. So I'm really excited to talk with everyone here today about the trends we're seeing in digital health because it's a really exciting area, and particularly in Silicon Valley, there's something new going on every day. Christine, can I pass the torch to you? 

Christine MoundasChristine Moundas: Sure—thanks, Megan. Hi, everyone. I'm Christine Moundas. I'm a partner in Ropes & Gray's New York office. I'm in the health care practice and also actively participate in our data practice. I provide a wide array of advice to health care, life sciences, and digital health companies, both a combination of regulatory, compliance, and transactional advice, particularly in some of these emerging areas where digital health is taking a lead and helping my clients to think about how either their digital health company needs to ensure that they're compliant, or to engage in a transaction that's going to take them to the next level, or advise health care or pharma or other types of companies on how to integrate digital health into their operations. So it's a pleasure speaking with you both today. Kellie, would you like to give a little background about your practice? 

Kellie Combs: Sure—thanks, Christine. I am Kellie Combs. I'm a partner in our life sciences regulatory and compliance practice, and I'm based in Washington, D.C. I advise clients, including pharma, biotech, medical device, and investor clients, on a wide range of FDA regulatory issues relevant not just to digital health, but to FDA regulation more broadly. With respect to digital health specifically, I work with clients thinking through issues related to real-world evidence, artificial intelligence as used in regulatory submissions, analysis of when a digital health technology might be considered a medical device and subject to FDA's regulatory oversight, and so on. And I'm really excited to be here with you both for our inaugural episode of this podcast. Now, let's turn to the substantive discussion. So with that, I'll turn it over to Christine. We've obviously worked a lot together over the years. What are you seeing right now in your practice? 

Christine Moundas: The past year or two have been super busy in a lot of ways, with the COVID pandemic really shifting the way we approach health care and the way the world has had to modify its usual business. And what I've seen is—in the context of the pandemic and how everything has shifted—actually a real maturation of a lot of digital health trends. I think it's actually incredible that a time of hardship would really be a time of innovation. But of course, everyone knows that telehealth has really taken off in a way that none of us could have predicted a year ago. And that has really led to people—both providers and patients—really understanding what does telehealth mean and understanding all the different ways in which telehealth can be useful for health care delivery. So that's one area where I've seen both a maturation of the regulations on the federal and state level as well as the uptake and adoption, and the companies involved with it, and the companies leveraging telehealth. So that's one big trend. 

The other thing that we're dealing quite a lot with is the implications of the information blocking regulations on health care providers, certified EHR technology vendors, and health information exchanges. These regulations stem from the 21st Century Cures Act—it was finalized by the Office of the National Coordinator for Health IT last year, and the compliance date was just earlier this month. It's really tremendously shifted the way all of our health care provider clients and different digital health clients have to think about the way they're interacting with others in the space when it comes to providing information, setting up interfaces, and charging fees associated with providing data. And really, the policy goal is to unlock the sharing of information across all these different health care players, but the practical implications of it and the compliance burden associated with it is really tremendous. So we are working with quite a number of companies on making sure that their information blocking compliance programs are put into place and then thinking through all the new practical things that they need to think through in light of those regulations. 

Then I would say artificial intelligence in health care and life sciences has really matured quite a bit as well. We're now seeing companies that just a couple years ago were in early phases of thinking through these issues or trying to develop or pilot algorithms or other things now actually going before the FDA with them, and going to market with real AI products. So that's been very rewarding to see and very exciting to see. 

Then finally, a lot of my clients, they've dabbled in the digital health space or they've adopted different digital health programs, but a lot of them only now are having their compliance programs catch up with those initiatives. That's been very interesting to see how people might not have initially issue spotted in the way that they should have early on, and now, they're working to clean up their programs or institute tighter compliance programs around their different digital health initiatives. And I think that's a very important trend and one that should come along with any space that's maturing. So I think overall those are the things I'm seeing. It's very busy and a very rewarding space, and I think everyone's just trying to make sure that they keep up with all the trends that are at play. 

Kellie, do you want to talk about some of the FDA regulatory trends you're seeing? 

Kellie Combs: It's interesting because as you described, there's been a maturation in the digital health space generally. I think we're certainly seeing some real advancement in FDA policy development as it relates to digital health technology. I'll highlight just two key regulatory developments that we've seen so far this year. The first is an Action Plan that the Agency issued on artificial intelligence and machine learning software as a medical device. Now, Christine, you, Megan, and I have all done a ton of work together on AI and machine learning over the years and really seen an uptick in what our clients are doing with respect to innovation, both in research and in diagnostic use. The Action Plan from FDA really just outlines a series of steps that the Agency is going to take to further its regulatory oversight of these sorts of technologies, and it's really just one more effort in the Agency's continuing push to modernize and clarify the regulation of digital health technology. This builds on a 2019 Proposed Framework for artificial intelligence and machine learning devices. And importantly, we don't yet have guidance from the Agency. This Action Plan just lays out what the Agency is planning to do when it comes to policy development. Among other things, the Agency is hoping to update the Proposed Framework that it released in 2019. Interestingly enough here, the FDA is planning to issue draft guidance on what it calls the Predetermined Change Control Plan for devices that incorporate artificial intelligence or machine learning. And this is essentially when sponsors are submitting an application to FDA, the Predetermined Change Control Plan outlines what types of anticipated modifications to the software may occur over time, as well as the methodology underlying the algorithm. That's been a real area of uncertainty for sponsors, so we're hopeful that guidance will provide some clarity moving forward. The Agency also through the Action Plan is going to encourage harmonization of what are called Good Machine Learning Practice developments, so really trying to set standards for developers of these sorts of tools. The Agency is planning to promote user transparency and also adopt a patient-centered regulatory approach that will include public workshops to get information about how device labeling can really inform transparency and benefit the patient or user experience. FDA is also going to work to support regulatory science efforts to develop methodology for the evaluation of machine learning algorithms, including for the identification and elimination of bias. And then finally, the Agency is planning to work with a variety of stakeholders who are piloting real-world performance process for these types of devices. 

Now, moving on from artificial intelligence, we've also seen quite a bit of movement lately at FDA when it comes to use of real-world evidence. Real-world evidence, which was already gaining prominence even before the pandemic, has been used extensively in connection with the development of COVID diagnostics, therapeutics, and vaccines. This increased use, as well as FDA policy development, are expected to continue this year. In fact, when FDA's Center for Drug Evaluation and Research—or CDER—released its guidance agenda for 2021, we saw that there are three guidance documents expected to be issued this year related to real-world evidence. Among others, there's one on real-world data, and in particular, assessing use of electronic health records and medical claims data to support regulatory decision making. We're expecting one on the use of patient registries as a real-world data source. And then finally, one that's broader and relates specifically to a requirement from the 2016 21st Century Cures Act, and that guidance will cover regulatory considerations for the use of real-world data and real-world evidence to support regulatory decision making for drugs and biological products. 

Now, as I mentioned earlier, we've seen a lot of movement with respect to real-world evidence when it comes to COVID diagnostics, therapeutics, and vaccines. And it really sounds like FDA is getting more familiar and more comfortable with these sorts of approaches. So just as one example, former FDA Deputy Commissioner Amy Abernethy said during the FDA/CMS Summit in December of last year that, "There's development of regulatory familiarity at FDA that will persist, and that learning from the use of real-world data during the pandemic will likely be built into the guidances that are coming out of these commitments going forward.” Now, it's a little too early to tell exactly what the guidance will cover, of course, but among other things, we expect the Agency to hit on when and whether real-world evidence or real-world data are fit for use, when trials or study designs that are used to generate real-world evidence can provide adequate scientific evidence to answer or help answer certain regulatory questions, how to determine whether studies meet FDA regulatory requirements (for example, for study monitoring and data collection), and then also gaps in real-world data sources and how to address those. We've seen over the years many companies—and especially during the pandemic—have been working closely with FDA to refine their individual approaches to use of real-world data or real-world evidence to support a specific regulatory submission, but our expectation is that the guidance coming from CDER this year will be able to provide more clarity to a broader set of companies seeking to incorporate real-world data or real-world evidence into their clinical development processes. 

So turning away now from the FDA regulatory landscape, Megan, I want to talk to you a little bit about the work that we've done on some of our transactional matters and what you're seeing right now in your practice. 

Megan Baca: Yes, I agree on the maturation point. I think that smaller companies are continuing to get traction and attention with investors. Large investors and companies continue to be very interested in this area for transactions and acquisitions. Kellie, you mentioned AI—I agree. In my practice, AI continues to be hot and definitely an area of interest. Our client Genesis Therapeutics, for example, has developed AI technology to assist with drug discovery and development, and they're right at the boundary of machine learning and biophysical simulation, it's called. Last year, we helped them negotiate and close a really substantial collaboration, their first with big pharma. And under that transaction, they're going to be working with the big pharma company to do compound screening, a really interesting transaction and very interesting for the big pharma as well to be partnering with an AI company like this one. We also helped them close their Series A, which was over $50 million, so quite substantial for a small new company. These kinds of collaborations are really interesting. So for traditional life sciences licensing attorneys who are very familiar with the typical IP frameworks that come with these collaborations, you really have to think afresh about a lot of the concepts when you enter into the digital health space. For example, deals that involve AI platforms, you have to think about some of the traditional concepts differently. For example, in life sciences collaborations, it's oftentimes an improvement made to another party's IP or technology owned by the party that brought that technology to the table, but that doesn't really translate well when it comes to AI models. For example, one party may bring data and the other uses that data to train its algorithms. So then you have a newer, smarter, faster, better algorithm based on that data, and the AI platform can't really unlearn the data—and you wouldn't want it to—because the data's been used or consumed to improve the underlying algorithms. Data owners may be fine with that, but they are sensitive to a platform that might retain the data within the platform indefinitely, and that would mean potentially in the future using it for the benefit of a competitor if, for example, it's a target-specific deal and then the AI company does additional deals with other collaboration partners. So there's ways to address this, but definitely have to avoid some of the pitfalls in a typical license that just contains standard definitions of things like "know-how" that would include data and improvements. 

Another area that is really interesting is to think about how the data output differs from a normal collaboration deal where you might have a compound screening deal that a more traditional one party might have exclusive rights in any of the compounds that come out of the screening that meet a certain threshold. Here though in this AI space, you could generate millions or even billions perhaps of theoretical compounds, and so you have to rethink the type of screening criteria that you're looking for under these collaborations to identify where the exclusivity lies because the owner of the AI platform may in the future work with other partners and regenerate that exact data output or the same compound structures, for example, and shouldn't be tied up because it happened to pop out of a previous collaboration amongst perhaps millions or billions of other potential compounds. So the IP and confidentiality provisions of these agreements, just as one example of many, are areas where licensing attorneys really need to focus and think about how these deals are different than the traditional pharma models. 

On the other side of the spectrum from our small clients, our large pharma clients and device company clients do continue to be very interested in finding ways to raise their own IQ on digital health matters, to really get at the learning curve on how to build digital health initiatives. And they're realizing the value of digital health for their companies and also the challenges of succeeding in digital health. It's obviously incredibly complicated and requires a tightly coordinated approach between lots of different internal specialty groups. For example, just doing a deal that involves a digital health asset, whether it's a license or an acquisition, brings together not just your normal transactional attorneys, but certainly needing data and privacy specialists, whether it be for consumer data or other highly regulated data, you need specialists in IP, you need regulatory specialists, and others. Basically all of us on the podcast here represent a lot of the voices you would hear when doing these types of transactions. Christine, do you want to jump in there with any thoughts? 

Christine Moundas: I agree with you. I think it really does require a cross-disciplinary approach because there are so many different regulatory hooks here, just different considerations that people might not realize when they're jumping into the deep end on digital health. I really have been encouraging clients to make sure that they take that holistic cross-disciplinary approach on the front-end rather than stumbling upon issues on the back-end. I agree with you, and it's important for small companies and it's really important for big companies, too. So I echo what you're saying there. 

Megan Baca: We do have so many clients doing exciting deals in this space. I don't know if you guys have additional ones, but I've seen deals in all types of wearables, consumer deals, clinical trials of research wearables, apps for absolutely everything. I see investors interested in behavioral health apps, cost control apps for health, IT services, AI for lots of different areas from pathology to radiology to drug discovery, and definitely discussions around how to use blockchain technology for health care applications. 

Kellie Combs: Megan, I think in addition to the categories you mentioned, what we're seeing not just in deals, but in many of our regulatory matters as well, is companies that are leveraging digital health technology to really bring medical advancements and tools directly to consumers. Previously, perhaps a consumer or patient needed to work with a health care professional to access certain technology and was not able to have certain technology at his or her fingertips. And it'll be interesting to see how FDA grapples with these sorts of advancements because, keep in mind, that of course FDA's regulatory framework in many ways is built around the idea of a patient working directly with a health care professional or under her supervision in order to get care or to get treatment. So it'll be interesting to see how this plays out. 

Well, I think that rounds out the conversation for today. Megan and Christine, thanks so much for joining me. I've learned a ton from you both, as usual. To our listeners, please stay tuned for additional podcasts in this series that will further discuss developing trends and hot topics within the industry. As you can see, we've really just scratched the surface today and there's so much to continue to discuss. On upcoming podcasts, we'll talk about developments related to artificial intelligence, big data initiatives and interoperability considerations, as well as regulations and guidance around telehealth, software as a medical device, mobile apps, and more. Thanks so much for listening today. We appreciate you tuning in to our Decoding Digital Health podcast series. If we can help you navigate any of the topics that we've been discussing, please don't hesitate to get in touch with us. For more information about our practice or other topics of interest in the digital health space and to sign up for our mailing list—with access to alerts and updates on notable developments as well as invitations to digital health-focused events—please visit ropesgray.com/digitalhealth. You can also subscribe to this series wherever you regularly listen to podcasts, including on Apple, Google and Spotify. Thanks again for listening.

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