CDRH Outlines Top 10 Science Priorities for 2017

Regulatory NewsRegulatory News | 21 September 2016 |  By 

The US Food and Drug Administration’s (FDA) Center for Devices and Radiological Health (CDRH) plans to leverage real-world evidence and more “Big Data” for regulatory decisions, according to a list of its science priorities for 2017.

As far as what will change between 2016 and 2017, the 13-page report says that thanks to more “needs submissions from staff,” CDRH was able to identify new topic areas, including clinical trial design and precision medicine, as well as describe existing topic areas in greater detail.

“Although the area of human factors is not prominently identified as a priority, it is still an unmet need and is reflected in the descriptions of other FY 2017 top ten priorities (e.g. infection control and predicting medical device clinical performance). Patient reported outcome measures and patient preference were combined as patient input and the reprocessing priority was renamed to the more inclusive topic of infection control,” the report says.

The top ten CDRH regulatory science priorities include:

  • Leverage “Big Data” for regulatory decision-making, including warehouses that host genomics, anatomical, biological, clinical trial and device performance and safety data contain scientific and clinical information relevant to medical devices.
  • Modernize biocompatibility and biological risk evaluation of device materials to better determine the safety profile of implantable or patient-contacting medical devices.
  • Leverage real-world evidence and employ evidence synthesis across multiple domains in regulatory decision-making as currently most regulatory decisions are based on information provided by manufacturers while data from traditional clinical trials is mostly limited to higher risk devices.
  • Advance tests and methods for predicting and monitoring medical device clinical performance
  • Develop methods and tools to improve and streamline clinical trial design
  • Develop computational modeling technologies to support regulatory decision-making. For example, FDA says, “improved multi-modality imaging simulation (e.g., x-ray, CT, MRI, US, optical) and realistic, anthropomorphic digital reference material (i.e., phantoms), could enable robust predictions of imaging system performance for a wider range of patient populations.”
  • Enhance the performance of digital health and medical device cybersecurity
  • Reduce healthcare associated infections by better understanding the effectiveness of antimicrobials, sterilization and reprocessing of medical devices
  • Collect and use patient input in regulatory decision-making
  • Leverage precision medicine and biomarkers for predicting medical device performance, disease diagnosis and progression



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