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Frederick National Laboratory for Cancer Research issued a request for proposal. To further advance AI in Medical Imaging (AIMI) large datasets, acquired through routine standard of care, are needed to train and evaluate the performance of the ML/AI algorithms. The datasets need to be correctly de-identified to maintain patient privacy while at the same time preserving as much scientifically relevant information as possible. Large datasets from the existing standard of care radiology…



U.S. Department of Energy’s INCITE program seeks proposals for 2023: INCITE’s open call provides an opportunity for researchers to pursue transformational advances in science and technology through large allocations of computer time and supporting resources at the Argonne Leadership Computing Facility (ALCF) and the Oak Ridge Leadership Computing Facility (OLCF). Both are DOE Office of Science user facilities located at DOE’s Argonne…



Welcome to the Envisioning Computational Innovations for Cancer Challenges Hub Site

The Envisioning Computational Innovations for Cancer Challenges (ECICC) is dedicated to accelerating computational oncology and developing research collaborations across cancer and computational sciences. Scientists from over 200 organizations in academia, government, and industry have participated in multidisciplinary events to share their ideas and expertise, develop use cases, and explore new research collaborations.

Thanks to broader engagement with the research community, new resources and collaborative research opportunities developed by the NCI-DOE Collaboration are shaping the future of predictive oncology, drug discovery, and clinical applications! 

We invite you to join us! To receive an invitation, please send an email to


The ECICC Community arose from a collaborative program between the National Cancer Institute (NCI) and the Department of Energy (DOE), Joint Design of Advanced Computing Solutions for Cancer (JDACS4C) to simultaneously accelerate advances in precision oncology and computing.

A multidisciplinary, highly interactive Scoping Meeting was held to identify cancer challenge areas that push the limits of current cancer research computational practices and compel the development of innovative computational technologies:

  • Generation of synthetic data sets for training, modeling and research
  • Hypothesis generation using machine learning (ML)
  • Creating digital twin technology
  • Development of adaptive treatments

Download the Scoping Meeting Report.

The ECICC Community has decided to focus its current work in two areas: cancer patient digital twins and predictive radiation oncology.

Cancer Patient Digital Twin

Members of the ECICC Community published a commentary in Nature Medicine: "Digital twins for predictive oncology will be a paradigm shift for precision cancer care," which describes how digital twins can transform cancer care! Read the latest news on the Cancer Patient Digital Twin page.

On March 4, 2022, principal investigators from five cancer patient digital twin project teams reported on their project results, challenges and future work. Watch their presentations. These teams originated in July 2020 with the five-day virtual ideas lab, “Toward Building a Cancer Patient ‘Digital Twin." The event brought together a diverse group of researchers to form new collaborations and create innovative research projects that would advance the development of a cancer patient digital twin. In late 2020, these five project teams were selected to receive seed funding—made possible by DOE and NCI—through Frederick National Laboratory for Cancer Research. Three of those teams were also invited to apply for additional DOE funding.

Predictive Radiation Oncology

Four Interactive, Multidisciplinary Workshops + a World Café* were held in March 2021 to help shape a “Blue-Sky” vision for the future of Radiation Oncology. 

NCI-DOE Collaboration Resources

For more information on the work of the NCI-DOE Collaboration, visit the website. 

    NCI-DOE Collaboration Publications

    NCI-DOE Collaboration Capabilities

Related Resources

Interagency Modeling and Analysis Group (IMAG): IMAG is a government group of program officials from multiple federal government agencies supporting research funding for modeling and analysis of biomedical, biological and behavioral systems. 

Previous Events


In May 2021, leaders of the NCI-DOE Collaboration presented at the American Association for Cancer Researchers (AACR) Annual Meeting. Watch the presentation.

Building on the cancer challenges identified at the Scoping Meeting, we held a series of virtual interactive Micro Labs on Cancer Challenges and Advanced Computing to continue the discussions:
  • 1st MicroLab, June 2019: See information about our 1st Micro Lab

  • 2nd MicroLab was held on September 25, 2019, 3:00 – 4:30 pm ET.  Based on the breakout discussions from the first Micro Lab, participants developed use cases and identified critical next steps to shape future research in computational oncology! Download the presentations from the September 2019 Micro Lab on Cancer Challenges and Advanced Computing.


If you are interested in learning more or joining this multi-disciplinary community, please contact

Created by Carolyn Kelley Klinger Last Modified Mon May 2, 2022 6:16 pm by Lynn Borkon