2016 will go down as a year that taught us to question our assumptions. The election of Donald Trump, an outcome almost no one predicted, left many with a sense of uncertainty about what 2017 will bring in the biomedical and health-care space. To bring clarity to these unsure times, FasterCures has compiled a list of issues critical to the future of medical innovation that we’ll be tracking over the coming year. While some issues will be closely linked with the people and policies of the new presidential administration, we think all will be important to continuing the progress toward faster cures and treatments.
1. FDA: What is the roadmap going forward?
2017 could be an exceptionally important year at the Food and Drug Administration (FDA). We don’t know who will lead the FDA as commissioner, and at least one senior leader has announced his retirement. We know that the dust-up over the agency’s approval in September of Sarepta’s Exondys 51 for Duchenne muscular dystrophy has led to a lot of discussion about how decisions will be made going forward. And we know the number of approvals in 2016 was lower than the record-breaking numbers of recent years, due to a declining number of New Drug Applications from industry, though some fingers will undoubtedly be pointed at the agency. The 21st Century Cures Act, passed in December, contains some “real but modest regulatory innovations“ that are being portrayed by some (erroneously, we believe) as reducing FDA’s standards for approval. And this will be the first time the critical user-fee agreements that help fund the agency will have been agreed to during one Congress and presidential administration but approved during another, making passage more complex than usual. Can the agency keep the pedal to the metal on the progress it’s been making in recent years to improve product review and approval, as well as create tools and resources to help streamline the part of the R&D process they can impact? Take note: FDA needs strong allies and partners to ensure they are ready for the innovation and challenges ahead.
2. What size would you like: small, medium or big science?
The National Institutes of Health (NIH) under Francis Collins’ leadership has been at the center of several “big science” initiatives aimed at creating infrastructure for future advances in medicine: the Brain Research through Advancing Innovative Neurotechnologies®(BRAIN) Initiative to create the arsenal of tools needed to unlock the mysteries of the human brain, the Precision Medicine Initiative® to build an army of research participants that will allow us to make individualized approaches to treatment a reality and the Cancer Moonshot (initiated by Vice President Joe Biden) to change and accelerate the research paradigm. We know that President Barack Obama, a self-professed science nerd, has prioritized advancing innovation and lent his full support to these initiatives. Will these investments remain a priority under new executive branch leadership? If these are not priorities, what will replace them as new focus areas? Will growing pushback from the basic science community against these large-scale, centralized, team-science projects shift federal investment away from these initiatives to basic science more broadly? Can science lead the way toward some common ground? Passage of the 21st Century Cures Act seems to have sent a strong signal about the bipartisan commitment to innovation given what was funded in that law.
3. Clinical trial innovation and reform: It’s a big job but somebody’s gotta do it.
There has been much interest in and excitement about the potential of innovative trial designs, such as adaptive trials and platform trials, to make the long and expensive clinical trial process more efficient and effective. Examples such as I-SPY in breast cancer, Lung-MAP in lung cancer and GBM AGILE in glioblastoma give tantalizing glimpses of how we can “set up trials around patients and disease rather than setting up a trial around a drug,” in the words of FDA’s Janet Woodcock, who is enthusiastic about these trials, when planned and executed well. FDA is overdue to update its almost seven-year-old draft guidance on adaptive designs to give sponsors more clarity around the benefits and expectations of trials conducted this way, which involve much more up-front planning and collaboration than traditional trials. 2017 should be the year to put in place the best practices, tools and resources necessary to make these collaborative, transparent learning environments the rule rather than the exception.
4. Doing science in the real world.
One of the elements of the 21st Century Cures Act that has attracted criticism is its requirement that FDA develop a framework and guidance for using “real-world evidence” to inform its decision-making in specific circumstances, including new indications for already approved drugs and for satisfying post-marketing requirements. This is something the agency – recognizing that randomized controlled trials, while essential, paint an incomplete picture of a product’s performance under real-world conditions – has already been considering and prioritizing for some time, and has in fact drafted policy for in the context of regulating devices. In addition, the Patient-Centered Outcomes Research Institute Institute has created the National Patient-Centered Clinical Research Network (PCORnet), a platform for collecting and using real-world data and evidence; the NIH Collaboratory is building the knowledge base for the conduct of pragmatic (or “real-world”) trials; and the Precision Medicine Initiative® will collect real-world data on 1 million people “in the wild” to support new discoveries. This movement is gaining steam, and the research world needs to get on board.
5. Patient-centricity: What’s the ROI?
In last year’s Top 10 list, we said it was time to stop talking about patient engagement and “put a ring on it” before the passion fades. We spent much time and effort in 2016 working on tools and resources to help build the science of patient input that will be the foundation of this new relationship with patients. Other organizations are also ramping up efforts, including Patient Focused Medicines Development, the Biotechnology Innovation Organization and the Clinical Trials Transformation Initiative. The concept has been sold, investments of time and treasure are being made and now many stakeholders, especially in industry, want to know, “What kind of return can I expect to get on my investment?” Companies need guidance from FDA, like what is outlined in the Prescription Drug User Fee Act (PDUFA) commitment letter, so that they can align their R&D enterprises accordingly. Without that, it’s unclear if patient-centricity will gain further traction beyond sound bites and goodwill. A recent survey by the Drug Information Association cited results as “reduced screen failure rates, faster patient recruitment, improved subject retention, reduced protocol amendments, and a greater number of patient relevant endpoints.” Expect to see more focus in 2017 on quantitative and qualitative metrics of the value of patient-centricity and patient engagement.
6. Move over direct-to-consumer ads – it’s time for direct-to-patient R&D.
Kathy Giusti, founder of the Multiple Myeloma Research Foundation, recently wondered in a Huffington Post blog why finding the cancer treatment or trial perfectly suited to you couldn’t be more like shopping for the perfect little black dress online. Why can’t the predictive analytics employed by Amazon and Netflix be put to work on something more impactful than recommending movies? “What can we learn from other industries with a proven track record for transforming data insights into incredible value?” She’s working with Harvard Business School’s Kraft Precision Medicine Accelerator to answer that question. 2017 should be the year when direct-to-consumer leaders help the medical community define the value proposition, engagement strategies (including building trust), infrastructure requirements and more to incentivize patients to share data and participate in research. We also need to make sure the algorithms don’t screen out things that would be good options – just as one romantic comedy viewing shouldn’t predestine you to forever get those flicks recommended. Groups like the Institute for eHealth Equity must be critical partners to ensure that underserved communities don’t get left on the other side of the “digital divide.”
7. Digitization of disease, and health.
It took the great recession of 2008 and the resulting HITECH Act to push the health-care industry to the point where it’s reliably using computers as “dumb” storage devices for electronic health records. But we’re now seeing “smart” applications of computing power to all those data that are redefining how we think about disease and health. For example, researchers at Mt. Sinai used Big Data analytics of its patients’ records to create a “Google Maps of disease” that elucidated, for instance, that there appear to be three distinct subtypes of type 2 diabetes. On the individual level, Eric Topol at Scripps is working toward the creation of scalable approaches to collecting and tracking people’s health information across multiple domains (-omics, biosensors, even social media) and across time to create their individualized “medical geographical information system” – their coordinates on the Google Maps of health, if you will, enabling more effective disease prevention and treatment. Artificial intelligence and deep learning hold the promise of improving disease diagnosis and treatment exponentially. Expect this trend to accelerate in 2017 as the technologies become more accessible and affordable.
8. Data sharing: Where there’s a will, there needs to be a way.
There remain good reasons why sharing data among researchers and across sectors can be hard, including data quality and the funding necessary to support sharing, which is clearly not cost-free. But maybe we have reached a tipping point, as expectations and commitments change and the ecosystem comes to terms with the fact that this is the way the rest of the world already works. NIH is requiring more and more sharing of data and providing infrastructure and incentives to support it; in the Cancer Moonshot its importance is second only to more funding for cancer research. Industry has realized the benefits and is moving to create platforms for sharing its data. The medical journal enterprise – after the New England Journal of Medicine created a bit of a conflagration by calling secondary users of data “research parasites“ – is finally engaging in the dialogue about solutions in a serious way. But are we in danger of merely creating more “silos of excellence” that don’t necessarily get us to the goal of being able to access and analyze the right data to answer the right question at the right time? 2017 should be about analyzing the data-sharing landscape and collaborating to better knit together complimentary efforts.
9. Evolution of value frameworks.
If the shift in health care from paying for volume to paying for value is a durable one in the new political paradigm we are entering, frameworks to define the value of treatments will continue to be of intense interest and debate. Some of those that made a splash in 2015 were amended in 2016, marking a slow evolution toward capturing the complexity of the definition of value and the importance of patients’ role in defining it. The recent Institute for Clinical and Economic Review report on psoriasis medications seems to be a promising example of how engagement with patient organizations and the expertise they can bring improved the review process and produced recommendations that were more likely to reflect the lived experience of patients with the disease. FasterCures and Avalere Health are hard at work producing a “Patient Perspective Value Framework,” which we hope will bring a new level of transparency and 360-degree view about the possible measures, data sources and methods for determining value. This is a trend that must accelerate if it’s to catch up with the debate about health-care costs in this country.
10. Blockchain could be good for your health.
What does the blockchain platform, best known for enabling the bitcoin virtual currency, have to do with health? Plenty, apparently. A recent Deloitte survey found that health-care and life sciences companies are deploying the decentralized database technology, which enables unchangeable data transactions, at a greater rate than any other industry. They believe it can help solve privacy, security and scalability issues related to electronic health records. In fact, the Office of the National Coordinator for Health IT conducted a challenge in 2016 to come up with promising applications. In the medical R&D realm, researchers are experimenting with using blockchain to improve the accuracy of and trust in clinical trials data, positing it as the platform for a patient-centric model of health data sharing and proposing that it could help solve the reproducibility crisis. Will the hope turn out to be hype in 2017?
We’ll be watching all of these issues because there are a million things we haven’t done yet to ensure that our R&D system and partners keep on innovating for patients. Just you wait!