4.2 Article

Co-Clinical Imaging Resource Program (CIRP): Bridging the Translational Divide to Advance Precision Medicine

Journal

TOMOGRAPHY
Volume 6, Issue 3, Pages 273-287

Publisher

GRAPHO PUBLICATIONS
DOI: 10.18383/j.tom.2020.00023

Keywords

co-clinical trial; preclinical PET; MR; CT; quantitative imaging; informatics; precision medicine; patient-derived tumor xenograft (PDX); genetically engineered mouse model (GEMM); cell transplant model (CTM)

Funding

  1. Washington University Co-Clinical Imaging Research Resource, NCI [U24CA209837]
  2. Siteman Cancer Center Support Grant [P30CA091842]
  3. Duke Preclinical Research Resources for Quantitative Imaging Biomarkers, NCI [U24CA220245]
  4. Integrating OMICS and Quantitative Imaging Data in Co-Clinical Trials to Predict Treatment Response in Triple Negative Breast Cancer, NCI [U24CA226110, CPRIT RR160005]
  5. University of Michigan Quantitative Imaging Research, NCI [U24CA237683]
  6. Vanderbilt University-PET imaging Resource to Enhance Delivery of Individualized Cancer Therapeutics, NCI [U24CA220325]
  7. PENN Quantitative MRI Resource for Pancreatic Cancer, NCI [U24CA231858]

Ask authors/readers for more resources

The National Institutes of Health's (National Cancer Institute) precision medicine initiative emphasizes the bio-logicaland molecular bases for cancer prevention and treatment. Importantly, it addresses the need for consistency in preclinical and clinical research. To overcome the translational gap in cancer treatment and prevention, the cancer research community has been transitioning toward using animal models that more fate fully recapitulate human tumor biology. There is a growing need to develop best practices in translational research, including imaging research, to better inform therapeutic choices and decision-making. Therefore, the National Cancer Institute has recently launched the Co-Clinical Imaging Research Resource Program (CIRP). Its overarching mission is to advance the practice of precision medicine by establishing consensus based best practices for co-clinical imaging research by developing optimized state-of-the-art translational quantitative imaging methodologies to enable disease detection, risk stratification, and assessment/prediction of response to therapy. In this communication, we discuss our involvement in the CIRP, detailing key considerations including animal model selection, co-clinical study design, need for standardization of co-clinical instruments, and harmonization of preclinical and clinical quantitative imaging pipelines. An underlying emphasis in the program is to develop best practices toward reproducible, repeatable, and precise quantitative imaging biomarkers for use in translational cancer imaging and therapy. We will conclude with our thoughts on informatics needs to enable collaborative and open science research to advance precision medicine.

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