NEW NCI Cancer Research Data Commons (CRDC) Request for Information (RFI) on AI Readiness! Responses due: November 30, 2023. NCI's CRDC seeks broad community input on the artificial intelligence readiness (i.e., data representation in a format that enables and eases the application of artificial intelligence/machine learning (AI/ML) approaches) of data across the multiple components of NCI’s Cancer Research Data Commons (CRDC). For more information, visit htt…Close
Calling All Cancer Research Innovators! Provide your feedback to NCI’s Cancer Research Data Commons (CRDC) Request for Information (RFI) on AI/ML use cases by November 30! View the full RFI at this link: https://grants.nih.gov/grants/guide/notice-files/NOT-CA-24-002.html. Don’t miss this opportunity to impact healthcare innovation!Close
Envisioning Computational Innovations for Cancer Challenges (ECICC) Scoping Meeting - March 2019
Envisioning Computational Innovations for Cancer Challenges: Scoping Meeting
March 6-7, 2019 | Livermore, CA
A Scoping Meeting is a large-scale, highly interactive, multi-disciplinary meeting that maximizes diverse expertise to break down a broad topic area into actionable challenges and opportunities.
A two-day, highly interactive, multi-disciplinary meeting for cancer, data, and computational scientists – at all career levels – who want to collaborate across disciplines to accelerate predictive oncology. A scoping meeting maximizes diverse expertise to break down a broad topic area into actionable challenges and opportunities. This meeting arose from a collaborative program between the National Cancer Institute (NCI) and the Department of Energy (DOE), Joint Design of Advanced Computational Solutions for Cancer (JDACS4C), to simultaneously accelerate advances in precision oncology and computing.
The meeting was held at Livermore Valley Open Campus at Lawrence Livermore National Laboratory on March 6-7, 2019.
Summaries of Challenge Areas:
Download the summary write-ups of the 4 cancer challenge areas from the Scoping Meeting
Identify lean-in scientific challenge areas that push the limits of current cancer research computational practices and compel the development of innovative computational technologies
Build a community, multi-disciplinary engagement, and collaboration among cancer, data, and computational scientists to create transformative impact
Demonstrate how to break down silos and work across domains, disciplines, and organizations
Define the types of cultural shifts in cancer research that could be possible with high-performance computing (HPC)
Since 2016, the National Cancer Institute and the US Department of Energy have been collaborating on the Joint Design of Advanced Computing Solutions for Cancer (JDACS4C) program to simultaneously accelerate advances in precision oncology and computing. The JDACS4C program has three research pilots that align with several existing NCI and DOE programs and are jointly led by DOE and NCI supported scientists. All three pilots embody a multi-disciplinary, team science approach. Together, these pilot projects are intended to pioneer new approaches to research and attain a greater understanding of cancer biology, diagnostics, prognostics, and treatment. The pilots utilize existing and emerging sources of cancer related data, increasingly large-scale multimodal data analysis, and simulations combined with advanced computational methods and algorithms from the DOE Exascale Computing Project. Intra- and extramural researchers have begun to access and use the jointly developed HPC and deep learning resources, such as the CANcer Distributed Learning Environment (CANDLE).
Current JDACS4C partners include the US National Cancer Institute, the US Department of Energy, Frederick National Laboratory for Cancer Research, and four DOE National Laboratories, including Argonne, Lawrence Livermore, Los Alamos, and Oak Ridge.
Inspired by the JDACS4C program, this Envisioning Computational Innovations for Cancer Challenges scoping meeting is based on the premise that greater capabilities and approaches to accelerate cancer research can be achieved through team science, technology adoption and collaboration/integration with the broader cancer research community.