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…
Registration is now open for Multiscale Modeling Consortium celebrates 20 years of the Interagency Modeling and Analysis Group (IMAG): Lessons from the past that guide the future at the NIH Campus in Bethesda, MD, June 28-29, 2023. Hybrid option available. Agenda available.
May 1st - Travel Award applications received on May 1st will receive full consideration. Awards will be notified on May 15th.
May 15th (11:59pm EDT) - All poster…Close
The NIH Common Fund issued two new notice of funding opportunity announcements from the Common Fund Data Ecosystem (CFDE): OTA-23-004 (due date: May 30, 2023) and RFA-RM-23-002 (due date: June 28, 2023). The purpose of these funding announcements is to establish the CFDE Data Resource Center, Knowledge Center, and Integration and Coordination Center. These centers will provide technical and administrative coordination and support to enable broad use of the data sets and knowledge…Close
Registration is now open for the Summer 2023 Human Tumor Atlas Network (HTAN) hybrid meeting on June 12-13, 2023. Meeting Website. The Summer 2023 HTAN meeting will take place virtually and at the Broad Institute in Cambridge, MA. Participants outside of the HTAN program are welcome and highly encouraged to join the meeting virtually to learn more about HTAN and interact with HTAN investigators. The two-day meeting will highlight the HTAN atlases that are currently available and include…Close
The AIM-AHEAD program launched six open funding and fellowship opportunities at the intersection of AI/ML and health disparities. These opportunities are primarily aimed at institutions/organizations that serve underserved and underrepresented populations.
1. Call for Proposals: Consortium Development Projects to Advance Health Equity
2. Call for Proposals: Data and Infrastructure Capacity Building
3. Call for Proposals: Program for Artificial Intelligence Readiness (PAIR)
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.
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.
- For more information, Accelerating Precision Radiation Oncology through Advanced Computing and Artificial Intelligence
- A report from the meeting is featured in Radiation Research (April 2022).
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
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.
In May 2021, leaders of the NCI-DOE Collaboration presented at the American Association for Cancer Researchers (AACR) Annual Meeting. Watch the presentation.
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.