FDA CDRH Network of Experts: CALL FOR EXPERTS IN DIGITAL HEALTH

for Network of Experts in Digital Health (“NoDEx”)

Network of Experts Program Background

The Center for Devices and Radiologic Health (CDRH) Network of Experts is a vetted network of external partner organizations and their member scientists, clinicians and engineers who can provide CDRH staff with simple and expedited feedback when needed to supplement existing knowledge and expertise within the Center. The program is designed to broaden staff exposure to clinical and scientific viewpoints, but not to provide external policy advice or opinions.

Despite the robust internal cadre of scientific expertise within CDRH at FDA, it is unrealistic to expect staff to encompass all the applicable expertise and experience necessary to fulfill its mission, especially given the rapidly growing complexity of medical devices. This is particularly true when it comes to new and emerging fields and pioneering technologies like digital health. In these areas, it is often beneficial to incorporate expertise and further scientific understanding from sources outside of the agency.

Digital Health Pool of Expertise

CDRH is committed to improving U.S. patient access to digital health medical devices. CDRH aims to provide oversight that is timely and effective while maintaining appropriate patient protections, including cybersecurity, for:

• Software as a medical device (SaMD)
• Medical devices enabled by software – i.e., software in medical device (SiMD), and
• Medical devices that otherwise incorporate novel digital health technologies

The Network of Experts aims to develop a pool of expertise in digital health and cybersecurity, comprised of experts in various subfields (e.g., cardiology, sports medicine). Such a pool will provide rapid feedback to FDA staff as needed, to help fulfill the agency’s mission.

This effort is timely, as it will also serve FDA’s soon to be established Digital Health Center of Excellence, intended to provide a unified and collaborative environment at CDRH for consistently applying best practices, conducting research, support and/or training for software and digital technologies.

Areas of Interest

• Artificial Intelligence
• Wearables / Medical IOT
• Digital Therapeutics
• Software Engineering
• Real World Evidence
• Cybersecurity
• Digital Biomarkers

Expectations

Experts’ CVs and conflict of interest forms (see ‘Applications’ below) will be on file and available for review by CDRH staff via an internal website. They will not be made public. When staff encounter questions for which they require external expertise, they may request a teleconference with select experts from the pool. Experts will be presented with the issue background, and questions for discussion, after which time they may agree or disagree to take part in a teleconference. Calls are scheduled for no more than an hour at a time at the participants’ convenience. Discussions are transcribed for recordkeeping purposes, and experts are given the opportunity to review and correct any transcripts once they are available. Members of the pool should expect to receive no more than three invitations in a given year; this number may vary depending on need and current key issues.

Potential Topics

Topics may be related to digital health and/or cybersecurity as it applies to specific medical fields or more broadly across the healthcare spectrum. Discussion and feedback may be related to pre-or post-market issues, clinical care, new developments in the field, or other relevant issues.

Tenure

Selected applicants will remain in the pool for a period of one year, at their discretion. Should experts decide not to be contacted for discussion, they may opt out at any time.

Requirements

Interested parties should possess recognized expertise and leadership, as demonstrated through authorship of peer-reviewed publications, advisory committee membership, regular speakership, etc., in any of the following fields or subfields:

• Artificial Intelligence
  • Machine learning-based approaches including supervised and unsupervised learning, genetic algorithms, reinforcement learning, etc.
  • Medical image-based analyses including computer-aided detection/diagnosis and digital pathology
  • Natural language processing
  • Bias, validation, explainability, and trustworthiness of AI systems
  • Continuously adaptive systems
  • Adversarial AI
  • Good Machine Learning Practices (GMLP)/ Machine Learning Operations (MLOps)
  • Neural network architecture
  • Development and use of common data sets for machine learning
• Physiologic Sensors, Wearables, and Medical Internet of Things (IOT)
  • Novel physiologic sensors
  • Novel applications of physiologic sensor data, including for general wellness
  • Use of data derived from digital health technologies as real-world evidence to support medical device evaluation and claims
  • Benefit-risk considerations related to general population-based screening
  • Statistical issues related to continuous measurement
  • Data integrity and quality issues, especially as applied to novel data sources
• Digital Therapeutics
  • Considerations for digital therapeutic clinical study design, including digital sham/ control interventions
  • Real world performance monitoring of clinical therapeutics
• Software Engineering
  • Applications of quality system approaches to agile environments
  • Novel approaches to demonstrating software capabilities and performance attributes (i.e. beyond traditional documentation)
  • Automation of software QA systems
  • Interoperability especially regarding medical systems
• Real-World Evidence
  • Real world evidence from digital health technologies for medical product development
  • Real world evidence for post-market monitoring and signal detection
  • Novel clinical trial design utilizing digital health technologies
  • Development and utilization of common data sets
• Mobile Networks & Wireless Communication
  • Applications of Bluetooth, wifi, and other wireless communication technology in digital health
  • Interoperability of digital health technology
  • 5G technology
• Cybersecurity
  • Threat modeling
  • Intrusion detection
  • Cloud security
  • Secure Development
  • Cryptography
• Digital Biomarkers
  • Development, verification and validation of digital biomarkers
  • Novel phenotypic signatures and composite biomarkers
  • Use of digital biomarkers in mobile clinical trials

Application Instructions

• Interested members of any Network of Experts partner organization are asked to forward a recent (within six months) copy of their CV to NoEDigiHealth@fda.hhs.gov. Should partner-members be asked to join the pool of experts, they will also be requested to complete a conflict of interest form, which remains in effect for a period of six months. Conflicts or perceived conflicts of interest do not preclude experts from taking part in the pool or speaking with staff; forms are for informational purposes only.
• When responding, experts are asked to please include ‘DHP’ and their specific field(s) of interest (see above) in the email subject line. Their home organization should be stated within the body of the email. Cover letters are not required.

Notification

• Selected members will be notified by email within two months of submission.

Contact Information

Submissions and/or any questions regarding the program should be sent to: NoEDigiHealth@fda.hhs.gov