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Last Updated: 10/28/16

Current CIP Initiatives

This page lists current opportunities from CIP.

For information about the funding process, go to Mechanisms or Guidelines.

The NCI’s Division of Extramural Activities provides information about newly approved concepts, which may become RFAs and PAs. Check the Concepts Cleared at the NCI Board of Scientific Advisors Meeting web site for the earliest possible information about future initiatives.

Quantitative Imaging Tools and Methods for Cancer Therapy Response Assessment (UG3/UH3)

  • Letter of Intent Due Date(s): April 9, 2017 (and at least 30 days prior to each subsequent receipt date)
  • Application Receipt Date: May 9, 2017; September 12, 2017; January 9, 2018; May 9, 2018; September 12, 2018; January 9, 2019; May 9, 2019; September 12, 2019; January 9, 2020
  • Expiration Date: January 10, 2020
  • Contacts:

    Scientific/Research Contact(s):
    Robert J. Nordstrom, Ph.D.
    National Cancer Institute (NCI)
    Phone: 240-276-5934
    Email: nordstrr@mail.nih.gov

    Darrell Tata, Ph.D.
    National Cancer Institute (NCI)
    Phone: 240-276-5894
    Email: darrell.tata@nih.gov

Funding Opportunity Purpose

This Funding Opportunity Announcement (FOA) encourages research project applications under the cooperative agreement (UG3/UH3) mechanism to address the development, optimization and validation of quantitative imaging (QI) software tools and methods for prediction and/or measurement of response to cancer therapies or for planning and validating radiation therapy treatment strategies in clinical trials.

The scientific scope of this FOA includes:

  • Development and optimization of QI tools and/or methods for treatment planning, predicting or measuring response to therapy as open source tools that will translate into clinical trial decision support
  • Validation of the optimized tools in clinical settings to demonstrate their value for decision support in ongoing single-site or multi-site clinical trials

A phased approach that emphasizes each of these activities must be proposed. Investigators must apply for both the UG3 and UH3 phases together in the single application. The UG3 effort is to be used for the development and optimization of QI tools and methods chosen for study by the investigating team, while the UH3 phase is for the validation of the tools/methods developed in the UG3 phase. The UG3 phase can be no more than 2 years in duration, and the total project cannot exceed 5 years. At completion, UG3 projects will be reviewed by program staff. Those that have met their milestones may be administratively considered by NCI program staff for transition to the UH3 validation phase.

Quantitative Imaging Tools and Methods for Cancer Response Assessment (U01)

  • Letter of Intent Due Date(s): April 9, 2017 (and at least 30 days prior to each subsequent receipt date)
  • Application Receipt Date: May 9, 2017; September 12, 2017; January 9, 2018; May 9, 2018; September 12, 2018; January 9, 2019; May 9, 2019; September 12, 2019; January 9, 2020
  • Expiration Date: January 10, 2020
  • Contacts:

    Scientific/Research Contact(s):
    Robert J. Nordstrom, Ph.D.
    National Cancer Institute (NCI)
    Phone: 240-276-5934
    Email: nordstrr@mail.nih.gov

    Darrell Tata, Ph.D.
    National Cancer Institute (NCI)
    Phone: 240-276-5894
    Email: darrell.tata@nih.gov

This purpose of this Funding Opportunity Announcement (FOA) is to provide a mechanism of support to research organizations interested in clinically translating already optimized quantitative imaging software tools capable of measuring or predicting the response of cancer to clinical therapies, or in translating imaging tools for planning and validating radiation therapy treatment strategies in clinical trials. The quantitative tools must have been developed and optimized during a performance period in the Quantitative Imaging Network (QIN) or under other separate funding. The proposed research effort should be an extension of the research that successfully completed the tasks of developing and optimizing the chosen software tools or data collection methods intended to facilitate clinical decision making during clinical trials. This FOA is intended to support the efforts of validating those tools in prospective multisite clinical trials in order to test tool performance and to demonstrate that the tool can be integrated into clinical workflow with a minimum of disruption.

PAR-16-385: Oncology Co-Clinical Imaging Research Resources to Encourage Consensus on Quantitative Imaging Methods and Precision Medicine(U24)

  • Release Date: August 24, 2016
  • Application Receipt Date: Nov 17, 2016; Jun 14, 2017; Nov 17, 2017; Jun 14, 2018
  • Expiration Date: Jun 15, 2018
  • Contacts:

    Huiming Zhang, Ph.D.
    Telephone: 240-276-5979
    Email: zhanghui@mail.nih.gov

    Cheryl Marks, Ph.D.
    Telephone: 240-276-6217
    Email: marksc@mail.nih.gov

    Richard V Mazurchuk, PhD.
    Telephone: 240-276-7126
    Email: mazurchukrv@mail.nih.gov

The purpose of this Funding Opportunity Announcement (FOA) is to invite Cooperative Agreement applications to develop research resources that will encourage a consensus on how Quantitative Imaging (QI) methods are optimized to improve the quality of imaging results for co-clinical trials. The scientific goals of this FOA are to: (a) perform the appropriate optimization of the pre-clinical quantitative imaging methods, (b) implement the optimized methods in the co-clinical trial, and finally (c) populate a web-accessible research resource with all the data, methods, workflow documentation, and results collected from the co-clinical investigations. Co-clinical trials are defined in this FOA as investigations in patients and in parallel (or sequentially) in mouse or human-in-mouse models of cancer that mirror the genetics and biology of the patients’ malignancies or pre-cancerous lesions. The co-clinical trial should include either (a) a therapeutic goal, such as the prediction, staging, and/or measurement of tumor response to therapies, or (b) a screening and early detection or a cancer risk stratification goal for lethal cancer versus non-lethal disease. Applicants are encouraged to organize multi-disciplinary teams with experience in mouse models research, human investigations, imaging platforms, QI methods, decision support software and informatics to populate the research resource.

PAR-16-044: Image-guided Drug Delivery (R01)

Source: FOA page

  • Release Date: January 28, 2016
  • Application Receipt Date: June 21, 2016; Nov 22, 2016; June 21, 2017; Nov 22, 2017; June 21, 2018; Nov 22, 2018
  • Expiration Date: Nov 23, 2018
  • Contacts:

    Scientific Contacts:
    Keyvan Farahani, Ph.D. (NCI),
    Phone: 240-276-5921, Email: farahank@mail.nih.gov

    Jessica Tucker, Ph.D. (NIBIB),
    Phone: 301-451-4778,
    Email: tuckerjm@mail.nih.gov

This Funding Opportunity Announcement (FOA) will support innovative research projects that are focused on image-guided drug delivery (IGDD), including real-time image guidance, monitoring, quantitative in vivo characterizations and validation of delivery and response. It will support research in development of integrated imaging-based systems for delivery of drugs or biologics in cancer and other diseases, quantitative imaging assays of drug delivery, and early intervention.

PAR-15-075: Academic-Industrial Partnerships for Translation of Technologies for Cancer Diagnosis and Treatment (R01)

Source: FOA page

  • Release Date: December 16, 2014
  • Application Receipt Date: First due date: Mar 6, 2015. Standard dates apply for following cycles.
  • Expiration Date: Jan 8, 2018
  • Contacts:

    NCI:
    Houston Baker, Ph.D., NCI.
    Phone: 240-276-5908
    Email: bakerhou@mail.nih.gov

    Miguel Ossandon, M.S., NCI.
    Phone: 240-276-5714
    Email: ossandom@mail.nih.gov

    Rao L. Divi, Ph.D., NCI.
    Phone: 240-276-6913
    Email: divir@mail.nih.gov

    NIBIB:
    Tiffani Bailey Lash, Ph.D., NIBIB.
    Phone: 301-451-4778
    Email: baileyti@mail.nih.gov

This Funding Opportunity Announcement (FOA) encourages applications from research partnerships formed by academic and industrial investigators, to accelerate the translation of technologies, methods, assays or devices, and/or systems for preclinical or clinical molecular diagnosis or in vitro imaging that are designed to solve a targeted cancer problem. The proposed systems may include molecular diagnosis, molecular imaging or related research resources. Funding may be requested to enhance, adapt, optimize, validate, and otherwise translate the following examples, among others: (a) current commercially supported systems, (b) next-generation systems, (c) quality assurance and quality control, (d) validation and correlation studies, (e) quantitative imaging, and (f) related research resources. Because applications should be translational in scope, this FOA defines innovation as a coherent translational plan to deliver emerging or new capabilities for preclinical or clinical use that are not yet broadly employed in preclinical or clinical settings. In addition, innovation may be considered as delivery of a new capability to end users. The partnership on each application should establish an inter-disciplinary, multi-institutional research team to work in strategic alliance to implement a coherent strategy to develop and translate their system to solve their chosen cancer problem. This FOA will support clinical trials that test functionality, optimize, and validate the performance of the proposed translational work. This FOA does not intend to support either actual commercial production or basic research projects that do not emphasize translation.

PAR-14-166: Early Phase Clinical Trials in Imaging and Image-Guided Interventions (R01)

  • Release Date: April 01, 2014
  • Application Receipt Date: June 30, 2014; Oct 10, 2014; Feb 9, 2015; June 9, 2015; Oct 9, 2015; Feb 9, 2016; June 9, 2016; Oct 11, 2016; Feb 9, 2017
  • Expiration Date: Feb 10, 2017
  • Contacts:

    Imaging trials:
    Lori A. Henderson, Ph.D., NCI
    Phone: 240-276-5930
    Email: hendersonlori@mail.gov

    Frank I. Lin, M.D., NCI
    Phone: 240-276-5932
    Email: frank.lin2@nih.gov

    Image-Guided Intervention [IGI] trials:
    Keyvan Farahani, Ph.D., NCI
    Phone: 240-276-5921
    Email: farahank@mail.nih.gov

    Radiation Therapy related trials:
    Bhadrasain Vikram, M.D., NCI
    Phone: 240-276-5690
    Email: vikramb@mail.nih.gov

EXPLANATORY NOTE: This is a new R01 grant-funded program announcement that supports Phase I/II clinical trials in imaging and IGI. Funds up to $500,000 in direct costs for a total project period of 2 or 3 years will be provided with a limit of $250,000 in direct costs in any single year. The previous R21 grant-funded program announcement referred to as PAR-14-013 has been terminated. Please see the FOA for explicit details including sections: (1) SF-424 (R&R) — Other Project Information and, (2) Application Review Information which highlights clinical trial protocol and background information requirements respectively.

PAR-14-116: Quantitative Imaging for Evaluation of Response to Cancer Therapies (U01)

This Funding Opportunity Announcement (FOA) invites research project — cooperative agreement (U01) applications which are expected to enhance the value of quantitative imaging (QI) in clinical trials for prediction and/or measurement of response to cancer therapies. One avenue for this enhancement is to emphasize the development, optimization and validation of state-of-the-art QI methods and software tools for potential implementation in single site phase 1 or 2 clinical trials. The second avenue to enhance QI methods is to address the challenges of integrating existing and or new QI methods as required for multicenter phase 3 clinical trials. This may involve evaluation of a range of multimodal imaging approaches, harmonization of image data collection, analysis, display and clinical workflow methods across imaging platforms, or testing their performance across different cancer sites.

Because this validation process is complex, a single research program cannot be expected to complete every detail from initial tool development to final integration into clinical trials. Therefore, it is anticipated that these research goals will require multidisciplinary efforts. Although the involvement of industrial partners in the development of the QI methods is not required, it is strongly encouraged. Awardees will also join the Quantitative Imaging Network (QIN) to share ideas and approaches in order to validate and standardize imaging data and related imaging metadata for quantitative measurements of prediction and/or response to cancer therapies.

See the CIP QIN Website for a description of the program.