Co-clinical imaging resource program (CIRP): Bridging the translational divide to advance precision medicine

Kooresh I. Shoghi, Cristian T. Badea, Stephanie J. Blocker, Thomas L. Chenevert, Richard Laforest, Michael T. Lewis, Gary D. Luker, H. Charles Manning, Daniel S. Marcus, Yvonne M. Mowery, Stephen Pickup, Ann Richmond, Brian D. Ross, Anna E. Vilgelm, Thomas E. Yankeelov, Rong Zhou

Research output: Contribution to journalArticlepeer-review

Abstract

The National Institutes of Health’s (National Cancer Institute) precision medicine initiative emphasizes the biological and 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 fatefully 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.

Original languageEnglish
Pages (from-to)273-287
Number of pages15
JournalTomography (Ann Arbor, Mich.)
Volume6
Issue number3
DOIs
StatePublished - Sep 2020

Keywords

  • CT
  • Cell transplant model (CTM)
  • Co-clinical trial
  • Genetically engineered mouse model (GEMM)
  • Informatics
  • MR
  • Patient-derived tumor xenograft (PDX)
  • Precision medicine
  • Preclinical PET
  • Quantitative imaging

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