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The NIH ScHARe social science data repository and research collaboration platform has been launched. This innovative ScHARe platform will:

  • host a wealth of social determinants of health and other social science datasets
  • provide cloud computing tools and secure workspaces to allow easy, low-cost analysis of these data
  • foster collaborations to develop AI bias mitigation strategies and advance health disparity and health care delivery research using big data

The ScHARe platform also…

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The National Cancer Institute (NCI) is hosting a virtual workshop focused on methods to address data limitations for applying artificial intelligence approaches in cancer research. The Cancer AI Research: Computational Approaches Addressing Imperfect Data workshop will run April 3-4, 2023, from 11 AM - 5 PM ET each day.

The goals of this workshop are to (1) examine the state of the science for AI methods designed to operate on noisy, complex, or low-dimensional data; (2) explore…

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Submit Your Manuscript for a special issue of Cancers: “Modeling Strategies for Drug Response Prediction in Cancer.”

Increase the visibility of your research in deep learning-based drug response prediction by submitting a manuscript to this special issue of Cancers (IF: 6.575, ISSN 2072-6694), guest edited by Rick L. Stevens. Cancers is an international, peer-reviewed, open access journal of oncology, published semimonthly online by…

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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 ECICC_Community@nih.gov.

Origin

The ECICC Community arose from the strategic interagency collaboration between the National Cancer Institute (NCI) and the Department of Energy (DOE), 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 twin 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 Resources

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

AACR

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

MicroLabs
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 ECICC_Community@nih.gov.

Created by Carolyn Kelley Klinger Last Modified Tue June 21, 2022 10:15 am by Lynn Borkon