The Center convenes multi-stakeholder working groups around relevant regulatory science topics.
Education in Regulatory Science
This working group convened during the 2020 Global Conference on Regulatory Science (Oct 20-21) and discussed best practices to prepare and continually maintain a workforce equipped to maximize the application of regulatory science.
The complexity, and rapidity of change, in the life sciences makes regulatory science training and professional development all the more important. Many new areas of medical product development, and indeed, entire fields of scientific inquiry, ranging from neuroprosthetics to digital therapeutics to the use of cellular organelles to target human disease, pose novel challenges to regulators working to safeguard the health and well-being of the public. To expeditiously bring patients these advances, new technologies must be translated from fundamental sciences to medicine through the application of scientifically sound regulatory activities. The key challenge and opportunity facing educators is to develop and maintain currency in a workforce that is equipped to maximize the promise of regulatory science in rapidly evolving disciplines.
Incorporating perspectives from academia, industry and regulatory agencies, the group discussed the regulatory science instruction landscape, best practices for training, and learning barriers. It also proposed recommendations to maximize the impact of regulatory science education in delivering optimal patient health outcomes.
Digital Pathology, AI and Image-Based Biomarkers in Research and Clinical Practice
This working group held a workshop on October 20-21, 2020 during the Global Conference on Regulatory Science to cover emerging digital pathology technologies, image-based biomarkers and diagnostics, construction of multiplexed tissue and tumor atlases, use of digital pathology in clinical and research settings, and the regulation of new devices and tests.
Anatomic pathology is one of the most important diagnostic modalities, but it relies on technologies that are little changed in nearly a century: direct inspection of stained tissue sections using transmitted light microscopy. In the last few years however, pathology has become increasingly digital and is being transformed both by new measurement methods (such as multiplexed high-resolution imaging) and use of machine-learning or artificial intelligence (ML/AI) methods to interpret images and improve diagnosis. These developments will have a particularly large impact on precision medicine because they promise to combine the traditional strengths of histopathology with the molecular information needed to refine diagnostic and prognostic categories and specify optimal targeted therapies. However, the introduction of unfamiliar and untested imaging and ML/AI technologies brings substantial challenges with respect to evaluating performance and ensuring compliance with regulations.
This workshop provided multi-stakeholder discussion of challenges and opportunities in use of digital pathology in research and clinical applications among individuals involved in patient care, federal funding, regulatory review, manufacture of instruments and development of commercial algorithms.