- Speech by
Amy Abernethy, MD, PhD.
Principal Deputy Commissioner - Office of the Commissioner
(Remarks as prepared for delivery)
Thank you. It’s an honor to be here at the MDMA Annual Meeting this morning. And it’s a particular honor to follow Congressman Upton - Fred. As you all know, Fred was a tireless champion for 21st Century Cures—a bipartisan, bicameral, multiyear effort that recommitted our country to advancing medicine. Cures is the recognition by Congress that FDA plays an integral role in the cycle of innovation.
Sir, as a citizen, I am glad to be here today to thank you in person for your work and your commitment to the agency and our mission - Cheers to Problem Solving.
I am excited that I get to be at the Agency during this pivotal time.
This is a crucial time in the development of a truly modern medical product ecosystem—an ecosystem that provides cutting-edge technologies at sustainable costs -- and that prioritizes, above all, the health and safety of the patient.
All the participants in this medical product ecosystem, including FDA, have a challenge: specifically, how do we harness new technologies -- including new technologies of data collection and analysis -- to support the goal of ensuring more access by patients to improved therapies? How do we match the speed of new technology development with the speed of medical product review, approval and monitoring?
Honestly, this challenge is what brought me to FDA, and my first several weeks on the job have convinced me that FDA—with its incredible staff and the trust of the American public—can lead us through an era of incredible technological advance, driven by new ways of applying data.
So let me step back and tell you a little bit about my story so that we can get to know each other.
I came to FDA as Principal Deputy Commissioner earlier this year and recently added the role as Acting Chief Information Officer.
My background is as an oncologist. I was on the faculty at Duke where I was a practicing clinician as well as a professor of medicine. At Duke, I ran an organization called the Center for Learning Healthcare.
At the Center, we focused on this question: How do we build data and technology solutions to simultaneously improve day-to-day clinical care delivery while also conducting research in the clinical environment? Our group studied how to organize the data, we studied point-of-care data collection solutions embedded in the EHR or a patient’s tablet computer, and we studied the quality of data routinely collected in the clinic and methods to improve data quality. Other questions focused on harnessing these datasets for clinical trials, participant recruitment, new statistical analyses and healthcare quality monitoring. The patient was always the focus, and we organized datasets anchored by longitudinal patient journeys and patient-defined outcomes. The summary goal was to pressure test the components needed to build a patient-centered learning healthcare system (take note of this, because it will come back up in our story later).
But we hit a ceiling at Duke, especially when it came to our ability to aggregate data across institutional boundaries (combine data between Duke and UNC – gosh forbid!). We also hit a ceiling on our ability to recruit and retain key talent such as software engineering and product managers.
So, in 2013-2014 I started to wonder: what if we motivate the technology industry—software developers in Silicon Valley—to get behind this idea of creating learning healthcare systems? What if we get venture capital to help us solve this problem?
But these are hard questions to contemplate from within the walls of academia, so I jumped in with both feet and joined a health tech start-up. Employee #30. We built software for oncologists and patients -- for example an electronic health record – and then pulled data out of those software systems into a common data model. A key goal was to clean the data - post-processing- and make it ready for secondary purposes like healthcare quality monitoring and—especially—clinical research. We were recapitulating the learning healthcare model that I worked on at Duke.I spent the last 4.5 years in-health-tech start-up-land learning the in’s and out’s of venture funding, business development, agile software product design, data lakes and pipelines, and advanced analytics. We were proudly patient centric.
And, what was interesting about that experience was the importance of the FDA. Regulations set the guideposts within which industry works. By clarifying what to do – and what not to do, regulations kept us from getting distracted and focused our energy on that which would be most impactful. What I learned was that the FDA both set the direction and clarified how to get there.
If we want to maximize impact on public health, setting the vision and the guideposts is a solid path. Joining the FDA made perfect sense to me.
Back to Congressman Upton. 21st Century Cures was formulated during the time that I was working in the tech industry. This was my introduction to the interconnectedness of legislation and modern medicine. It codified many of the remarkable and impactful policies FDA already had underway and created a vision for the future of medicine as well as the regulatory infrastructure we need to support such a vision.
One factor of 21st Century Cures that may be its most important, is that it created an opportunity to look across the FDA and see how it matches the medical innovation ecosystem. There has never been a doubt about the importance of the FDA to medical product development, and the FDA has continuously improved and evolved throughout the user fee cycles. But we need to look further into the future, 20 years and beyond, and make sure we can be prepared.
The Cures Act provided the opportunity to look across the medical ecosystem to see what is working, and perhaps more importantly, what is not working, for patients. While Cures did not address everything, it gave us an opportunity to assess the US medical product innovation system and prepare for the future.
What do I mean by this? Cures anticipates a future of progressively more personalized and refined care, made possible because we are capitalizing on our understanding of biology plus investments in data and engineering. It compels us to modernize the process of clinical evidence development for medical products, approving these products as soon as we can confidently do so – and then monitoring how approved products perform across time.
Cures set up the why and what – but not necessarily the how. Now it is up to us – the collective us - to figure out how to do it.
My role as Principal Deputy Commissioner is to support the agency as we look to future challenges and innovations in medicine. Said differently, I am blessed with the “forward leaning role” at the agency – I get to take the long view.
I believe that there are a lot of lessons to be learned from the way that the Center for Devices and Radiological Health (CDRH), under Dr. Shuren’s leadership, has evolved the total product life cycle approach to medical device regulation. This approach is based on data and evidence tailored to the technology and disease state under consideration.
As Dr. Shuren knows, I call it the “prototype of the future”; there is even a special box on the main whiteboard in my office that says “CDRH = Prototype”. I’m from Orlando – In my head I call it “The EPCOT of Healthcare”. For those of you not fully initiated in Orlando trivia - Disney’s EPCOT stands for the Experimental Prototype Community of Tomorrow. Replace the E with evidence-generating and you get the Evidence-generating Prototype Community of Tomorrow.
CDRH’s organizational structure and innovative approach harnesses data to support informed regulatory decision making. CDRH uses the Congressionally mandated “least burdensome” standard in both the pre- and post-market. CDRH’s approach to continuous assessment is consistent with agile medical product innovation. Devices are studied across time, so we can improve patient outcomes, while also mitigating serious risks to patients that may not be identifiable in pre-market trials.
CDRH’s strategy for progressively reducing residual uncertainty related to device benefits and risks over time mirrors the core concept of a learning health care system: creating data-driven feedback loops to drive improvements in product development and care delivery.
To unleash the full potential of a learning health care system – to deliver improved patient outcomes at a sustainable cost without sacrificing safety – the FDA is going to have to learn how to apply and scale similar strategies across its entire regulatory portfolio.
In fact, I’d go so far as to say we don’t have a choice.
Let’s stop and contemplate for a moment what this really means for FDA. More personalization leads to more indications intended for smaller populations. More continuous evaluation and re-evaluation of medical products across their life-cycle using data-driven feedback loops multiplies the number of reviews per product. Systematic learning requires frequent and timely updated communications. We at FDA are going to have to scale what we do – expand our review and knowledge management capacity multi-fold – in order to keep up.
Fulfilling our critical public health mission at a time of rapid technological innovation requires the agency to scale its capacity for conducting efficient product reviews and clearances. We must harness a wide variety of “fit for purpose” strategies for assessing evidence of product safety and efficacy in the pre- and post-market.
This will entail greater use of real-world data in tandem with evolving insights into disease biology, sometimes in a near real time basis, helping patients and providers to deploy the right treatment to the right patient, at the right time.
Greater use of real-world evidence can also help regulators assess and reduce residual risks and uncertainties around novel technologies, especially as these novel technologies get used in populations or treatment settings that may not have been studied in pre-market registration studies. This way we don’t delay access of novel technologies for targeted patient cohorts where it is possible to make an informed benefit-risk assessment, and use real-world evidence to fill in knowledge gaps as use of the novel technology expands post-market.
This is our vision for the future, but we’re implementing it today.
You may be wondering how my role as Acting Chief Information Officer ties into all of all of this. In the 21st Century Cures Act, Congress established a national agenda to modernize how we harness evidence to advance medical product development. In other words, there is a whole bunch of data and technology embedded in Cures.
Congress prioritized developing streamlined clinical trial designs powered by informatics; greater use of real-world evidence derived from electronic health records (EHRs) and other sources; and, increasingly, required technical interfaces between clinical data systems that make them much more interoperable and accessible.
Congress recognized that reliable and readily accessible data could be combined and analyzed to answer important clinical questions in a fraction of the time of a traditional clinical trial.
For example, EHR data linked to next-generation genomic sequencing output can be used to identify new drug targets, define treatment effectiveness, and generate contemporaneous control data for single arm trials. The same datasets can also support real-time healthcare quality monitoring and potentially even support new pay-for-performance payment models.
Stakeholders across the medical product ecosystem are working to make Cures’ vision a reality. And FDA is playing a critical role in creating a regulatory roadmap for efficiently translating data into reliable evidence.
Clear standards for utilizing RWE for FDA clearance or approval decisions can help stakeholders align around best practices for curating data across the patient journey; and harness new approaches – like artificial intelligence algorithms – in ways that make medical product and care delivery much more transparent, patient-focused, and efficient.
That’s an exciting vision, and one I’m deeply committed to. Remember my story about the Center for Learning Healthcare. This topic has shaped my career and is shaping our forward-looking story at FDA.
But, frankly, FDA is going to have to get our own house in order to make it a reality. Let me invite you under the hood at FDA – within the walls of the agency. This isn’t a complaint; simply a statement of the current state of things we must address in order to prepare ourselves for the future envisioned in Cures.
Today we have real challenges, including a siloed tech organizational structure that doesn’t reflect a modern, analytic systems-approach to medical product development; a fragmented and outdated governance system for assessing and prioritizing our enterprise technology needs; and legacy IT systems that have accreted over time, that sometimes make it hard to do basic work like answering email, let alone allowing reviewers and agency leadership to leverage decades of clinical trial data to drive consistent innovation in regulatory science and processes.
My work is focused on breaking down those silos and scaling FDA’s internal data architecture; creating more transparent and collaborative approaches for enterprise IT platforms; and strengthening the agency’s human capital to address these technology challenges with greater confidence internally, rather than relying on a steady succession of one-off contractors that leave us with complex piecemeal solutions that don’t scale.
I’m currently working with the agency’s senior leadership to develop a new enterprise-wide strategy for data and analytics that clearly identifies our existing challenges, and offers a roadmap for enterprise solutions, without limiting the ability of the Centers to craft analytics that fit their specific needs.
We’ll have much more to say about this in the coming months.
This is the reason that I took on the Acting CIO role. It was clear that in order to prepare for a future envisioned and enabled through Cures, we have to have our own house in order. So I might as well roll up my sleeves and help out.
How does this translate to CDRH? As I said, CDRH is our EPCOT. Our prototype where we can learn how to make it all happen, what is needed, what breaks.
FDA’s medical device reviewers have been at the forefront of the evolving role of digital technologies in regulatory decision making simply because devices are designed to be iterative, improving performance in 18-24 month time frames. Sponsors benefit from close feedback loops, such as communication from surgeons implanting medical devices – and, increasingly, the patients who use them. A great example here is the artificial pancreas, which was driven by the parents of children with Type 1 diabetes.
It’s also been relatively simple to incorporate connected technologies into implantable and wearable devices, that then routinely report performance data back to providers and manufacturers.
For example, we are witnessing the emergence of digital biomarkers that incorporate geolocation data or accelerometer data from smartphones or other wearable devices; these give us important information on patient function and response to treatment across a range of disorders, including depression or cancer. Data is patient generated, basically zero cost, and can be assessed without requiring patients to travel to a medical center.
Software innovation looks different than the traditional medical product innovation of the past; software innovation cycles can be measured in weeks and months rather than years. The Pre-Cert program is a pilot in progress, and an ongoing learning process for the agency and the software community. It is a natural evolution of CDRH’s pragmatic approach to device regulation and innovation.
I believe that the transformative promise of data for our medical enterprise is a remarkable opportunity that we need to seize for the benefit of patients. Modernizing FDA’s internal IT infrastructure will help us not only keep pace with these opportunities; it will help fulfill Congress’ vision for the Cures Act, unleashing the full promise of precision medicine to deliver new treatments for previously intractable ailments.
One of the initiatives I am most excited about is the National Evaluation System for Health Technology, otherwise known as NEST – also on your agenda for later this morning.
I believe that NEST will enable more timely identification and resolution of safety concerns, improve access and analysis of data to ensure timely responses to public health threats, better characterize real-world performance of medical devices, and facilitate premarket clearance or approval of new devices and new uses of currently marketed devices, without the need for patients to participate in additional clinical trials.
In doing so, we will be able to drive down the time and cost of medical product development and increase the value and use of real-world data to meet the needs of medical device ecosystem stakeholders through a market-driven, collective buying power approach and using a neural network data model.
The promise of NEST is clear: Real-time device safety information means better outcomes for patients who depend on devices to improve their health. Another promise of NEST is to serve as an exemplar – showcasing how to use real-world data and thoughtfully generate evidence across the device space and beyond.
The agency remains committed to making the promise a reality by prioritizing NEST’s development, and ensuring it’s set up for long-term success to advance public health. The concept of NEST is directly in line with 21st Century Cures in that it will support and accelerate the innovation cycle for the benefit of patients. For example, NEST can help facilitate reimbursement as improved data collection can contribute to “coverage with evidence development (CED)” opportunities. Aligned with this vision, the Center for Medicare and Medicaid Studies (CMS) serves on the NEST Governing Committee.
The system will help improve the quality of real-world evidence that FDA can use to detect emerging safety signals quickly and take appropriate actions. This constant feedback will also enable medical device manufacturers to continue to develop innovative improvements for their products.
One goal of NEST that as a physician struck me as one of the most important components, is how NEST will help healthcare providers and patients be better informed about the evolving benefit-risk profile of devices on the market and enable them to make more informed decisions. NEST directly aligns with that patient-centric learning healthcare vision.
One other priority that CDRH has been working on and I believe is a critical and inevitable part of personalized medicine is In Vitro Clinical Tests. My professional experience has proven how critical these tests are for patients and our healthcare system—for every single part of our healthcare system. From drug development and determining the appropriate trial participants, determining patient treatments and monitoring progress, to payment and reimbursement for these tests.
We need a unified approach to the regulation of in vitro clinical tests that can keep up with the rapid advancement of technology and protect patient safety. Appropriately tailored FDA oversight will facilitate the development of analytically and clinically valid tests and provide healthcare providers and patients the performance information they need to make well-informed decisions. FDA will continue to work with Congress and stakeholders towards this goal.
Another exciting and critical priority is the Digital Transformation initiative at CDRH that will help leverage and analyze data collected every day in clinical practice for regulatory decisions, detect safety signals earlier, and assure innovators understand the evidentiary requirements for new products to meet FDA’s gold standard and come to market.
We received funding from Congress to support CDRH’s digital transformation, a critical component of modernizing the regulatory structure.
Sufficient funding in this area will assure greater and more transparent interactions between CDRH and its customers, including providing industry with the ability to track their premarket submissions online and to engage with CDRH staff on their submissions in a virtual work space. Digital Transformation will enable processes closer to the speed of industry to streamline workflows, reduce the cost of maintaining data and network security, and improve the timeliness of delivery of services. We will reduce, if not eliminate, duplication, and establish an integrated environment, to use modern analytical and artificial intelligence tools, and process applications effectively, while also responding quickly to regulatory questions.
The concepts behind initiatives like the Digital Transformation are not new—they are something that have been discussed and contemplated for many years. The difference now is that these are no longer just ideas. These are funded initiatives that are critical to our medical enterprise. And it needs to work.
Before I close, I would like to scale out to 100,000 feet for a moment. The big Why. The U.S. has been at the forefront of both the information technology revolution and the advent of precision medicine driven by the deciphering of the human genome. In fact, the developments in precision medicine we’re seeing today would be impossible without advances in computing power and analytic platforms that have driven the cost of NGS sequencing down even faster than Moore’s Law.
Congress has tasked the agency with the creation of a modern regulatory system for translating new digital and biologic insights into safer and more effective medical products as efficiently as possible.
As we do so, U.S. patients will benefit from accelerated access to important new medical therapies, while our economy benefits from both reduced economic burden associated with debilitating chronic diseases and a well-performing biomedical enterprise.
FDA’s continuous improvements in regulatory process efficiency make evidence generation more timely, efficient and robust. FDA’s work to create efficiency is not new, but we now have tools that can bring our work further. Part of this work is not simply creating efficiency in our systems, it is also making sure that we improve the predictability, efficiency and transparency of our regulatory systems so evidentiary requirements to bring devices to market are clear and understood. By doing this we ensure that patients are ultimately benefiting from more safe and effective devices on the market because more companies are able to understand and meet the FDA’s gold standard, in addition we can detect safety signals earlier, and that FDA can continue to leverage real world evidence for regulatory decisions including new approvals and labeling expansions.
So, to say it succinctly, we are doing all of this for the following: To ensure that patients get the greatest benefit from our national investments in basic sciences and engineering as soon as possible And as a byproduct, it is good for our economy; this is great too.
As I close here with you today, I reflect that it comes back full circle to where we started. That is the reality of iterative learning healthcare. Testing it out, finding what works, finding the path. It is unlikely we will get everything perfect on the first try, which just increases the imperative to get on with it!
Core elements of this vision include:
- Iterative learning cycles
- A technical infrastructure plus people and processes to pull it off
- A forward-looking view - a focus on the future
- A model that places the patient at the center
The Cures Act has set the mandate; thank you Congressman Upton and All. Cures incorporates core components of modernized medical product development and review, directly in line with a learning healthcare vision. Devices, by their very nature are continuously evolving and built on a foundation of engineering, technology and data – it’s a perfect set up. CDRH is the prototype environment, our EPCOT; in CDRH, the data, technical, process and people transformation needed to meet this mandate is already underway. CDRH exemplifies the “how” – how are going to get this done, what does it look like, how do we adjust, what infrastructure do we need, what are reasonable timelines and metrics. CDRH points our way toward the future.
I stand ready to make these concepts and ideas a reality.