Big Data Tops FDA’s 2016 Priorities

FDA’s Center for Devices and Radiological Health (CDRH) plans to embrace the use of big data and patient reported outcomes in regulatory decision making, according to its 2016 Regulatory Scientific Priorities.

The U.S. regulatory paradigm is out of sync with our innovation cycles and data channels, said Jeffrey E. Shuren, M.D., CDRH Director, in previewing the priorities at AdvaMed 2015 in October. A medical device ecosystem based on data, including crowd sourced clinical data, a national evaluation system, unique device identification and patient reported outcomes and preferences—if these could all coexist with supportive reimbursement models, Shuren said, it would be a game-changer to reduce the time and cost involved in getting products to market.

Shuren’s premise is that the multitudes of data streams within healthcare should be leveraged to support the ability to set information standards, develop benefit/risk profiles and establish quality checks to determine what data needs to be collected on a device before it is approved.

“Rather than thinking about premarket and postmarket, it’s patient access,” Shuren says. “The more we understand about the technology, the more we broaden patient access. This has implications not only on the regulatory side, but adopted on the reimbursement side; you think [differently] about funding clinical studies, because really a clinical study is about patient access to a technology. If you think about it that way, it changes the paradigm.”

FDA’s announcement comes months after major companies announced that they seek to harvest and analyze larger and broader sets of data to impact patient outcomes beyond device manufacturing. In April, Medtronic and Johnson & Johnson announced big data partnerships with IBM. Medtronic’s work will focus on its diabetes business, while Johnson & Johnson and IBM are developing coaching systems centered on pre- and postoperative patient care for joint replacement and spinal surgery.

The general topic of big data has brought up warranted concerns over the years. One pertains to security concerns over privacy protection. Another relates to the ways that data is pulled and sorted. If data is collected for different purposes and in different ways and then merged, it is difficult to draw meaningful conclusions. A third concern is the view of big data as a panacea. Data—big or small—cannot be used as the only tool to answer a question.

With limited information at this point, it’s hard to see how FDA will leverage this focus in a timely and meaningful way, and what this will require from device makers. Government‘s “big data” initiatives have required significant industry investments and headaches, e.g. the Global UDI Database, the Sunshine Act. While this CDRH priority emphasizes leveraging data that is already being collected, but underutilized in regulatory decision making, device companies should push for greater understanding of the initiative. How and what data will be collected? What decisions will the data influence? Who will determine the meaningfulness of the correlations found in the data in order to determine whether or not a device meets the standards of safety and effectiveness?

Embracing data tools speaks to less than a handful of CDRH’s priorities. Device companies can expect CDRH to take a deeper look at materials and reusable devices.

The ten regulatory science priorities for 2016 include:

1. 1. Leverage “Big Data” for regulatory decision making
   2. Leverage evidence from clinical experience and employ evidence synthesis across multiple domains in regulatory decision making
   3. Improve the quality and effectiveness of reprocessing reusable medical devices
   4. Develop computational modeling technologies to support regulatory decision making•  FDA has received a growing number of submissions that include simulation data, leading the agency to believe that computer modeling and simulation (M&S) has the potential to supplement traditional models used to evaluate devices. The development of M&S techniques in conjunction with validation methodologies may help companies get devices to market utilizing less-burdensome approaches.
   5. Enhance performance of digital health and medical device cybersecurity
   6. Incorporate human factors engineering principles into device design•  FDA isn’t the only regulatory body with an eye on human factors. Manufacturers can expect greater focus on the topic from the EU, China and Japan. Three human factors problem areas for device manufacturers are people requirements, design requirements and testing requirements.
   7. Modernize biocompatibility/biological risk evaluation of device materials
   8. Advance methods to predict clinical performance of medical devices and their materials
   9. Advance the use of patient reported outcome measures in regulatory decision making
   10. Collect and use patient experience/performance in regulatory decision making

CDRH weights the priorities equally. The list, developed by the Regulatory Science Subcommittee, serves as a guide for the division’s strategic research and funding decisions and alerts device companies on how to target their regulatory resources to complement FDA’s activities. Save Supplier