Predictive Radiation Oncology - A New NCI-DOE Scientific Space and Community. Radiation research Buchsbaum, J. C., Jaffray, D. A., Ba, D., Borkon, L. L., Chalk, C., Chung, C., Coleman, M. A., Coleman, C. N., Diehn, M., Droegemeier, K. K., Enderling, H., Espey, M. G., Greenspan, E. J., Hartshorn, C. M., Hoang, T., Hsiao, H. T., Keppel, C., Moore, N. W., Prior, F., Stahlberg, E. A., Tourassi, G., Willcox, K. E. 1800


With a widely attended virtual kickoff event on January 29, 2021, the National Cancer Institute (NCI) and the Department of Energy (DOE) launched a series of 4 interactive, interdisciplinary workshops-and a final concluding "World Cafe" on March 29, 2021-focused on advancing computational approaches for predictive oncology in the clinical and research domains of radiation oncology. These events reflect 3,870 human hours of virtual engagement with representation from 8 DOE national laboratories and the Frederick National Laboratory for Cancer Research (FNL), 4 research institutes, 5 cancer centers, 17 medical schools and teaching hospitals, 5 companies, 5 federal agencies, 3 research centers, and 27 universities. Here we summarize the workshops by first describing the background for the workshops. Participants identified twelve key questions-and collaborative parallel ideas-as the focus of work going forward to advance the field. These were then used to define short-term and longer-term "Blue Sky" goals. In addition, the group determined key success factors for predictive oncology in the context of radiation oncology, if not the future of all of medicine. These are: cross-discipline collaboration, targeted talent development, development of mechanistic mathematical and computational models and tools, and access to high-quality multiscale data that bridges mechanisms to phenotype. The workshop participants reported feeling energized and highly motivated to pursue next steps together to address the unmet needs in radiation oncology specifically and in cancer research generally and that NCI and DOE project goals align at the convergence of radiation therapy and advanced computing.

View details for DOI 10.1667/RADE-22-00012.1

View details for PubMedID 35090025