The Early Detection Research Network: Clinical Validation Centers (U01 Clinical Trial Optional)
Funding Agency:
- National Institutes of Health
The mission of the EDRN is to discover, develop, and validate biomarkers and imaging methods to detect early-stage cancers and precancers that are likely to progress and to translate these into clinical tests. EDRN is a highly collaborative program that helps coordinate biomarker research within the extramural community and with other NCI programs in cancer prevention, screening, and treatment to reduce cancer incidence, morbidity and mortality (see EDRN Strategic Plan, https://edrn.nci.nih.gov/about/bookshelf). Since its inception in 2000, the EDRN has followed a "vertical" approach to develop and validate early detection biomarkers that rely on collaborations and hand-offs among technology developers, basic scientists, clinicians, radiologists, epidemiologists, biostatisticians, and other health professionals.
The NCI expects that EDRN investigators will collaborate with industry both to develop biomarkers and/or reagents and to provide a clinical environment for the evaluation of new technologies. Early interactions with industry, which lead to research collaborations are likely to benefit both EDRN grantees and industry partners. Many EDRN investigators have or have had fruitful collaborations with the industry in the past. It is hoped that validated molecular biomarkers and/or imaging methods will ultimately be commercialized into diagnostic products for early detection of cancer and cancer risk assessment and subsequently be tested in clinical utility trials.
The EDRN provides an infrastructure to expedite the clinical application of molecular and imaging data through its knowledge environment, which was developed in collaboration with NASA's Jet Propulsion Laboratory (JPL). The architecture of the knowledge environment is based on supporting and linking molecular data (genomics, proteomics, etc.) to clinical phenotypes and imaging. The EDRN Informatics Center at JPL (JPL IC) leverages cloud-based capabilities to support the increasing data and computational demands of the program. The infrastructure also supports capabilities to run repeat analyses of complex genomics and proteomics data, image analysis including radiomics, and other complex data types. Over the years, EDRN has built several data repositories on biomarkers, imaging, and analytical tools. These resources will be employed to help build specific, interoperable data platforms that will allow investigators to mine and analyze data using artificial intelligence (AI) and other machine learning languages (MLL). Data science is poised to play a major role for new or improved risk stratification, early detection, and precision prevention strategies, particularly in patients with ambiguous symptoms or at high risk for the disease. In recent years, EDRN has amassed large amounts of imaging data and combined it with clinical information to diagnose patients, recognize tumor types, and/or make any follow-up care and treatment decisions. These imaging and data analytics will provide unprecedented opportunities for in silico biomarker discovery, accurately identify early-stage aggressive neoplasms from indolent or benign lesions for many cancers and make more accurate predictions about their aggressiveness.
EDRN's specific interests include but are not limited to the following:
- Discover, develop, evaluate, and validate promising 'omic' biomarkers (e.g., genomic, proteomic epigenomic, metabolomic) for effective cancer risk assessment, early detection, and diagnosis and prognosis of early-stage cancers and pre-neoplastic lesions.
- Develop and validate biomarkers to improve the detection of cancer progression for patients on active surveillance.
- Develop and implement diagnostic assays/tests for accelerating biomarker discovery and translation into the clinic. This would include measures of diagnostic or predictive accuracy, sensitivity, and specificity.
- Facilitate the development of high-throughput, sensitive assay methods to identify, verify and validate biomarkers that are useful in the assessment of risk, detection, diagnosis, and prognosis of early-stage cancers or their lethal precursors.
- Integrate molecular biomarkers with imaging approaches to improve the performance of tests, reduce false-positive rates, and improve the detection of clinically significant cancers.
- Implement, expand and/or modify new or existing imaging modalities, protocols, and associated informatics to improve the performance of tests.
- Develop and implement AI and MLL algorithms to facilitate the discovery and translation of multiple biomarkers.
- Support collaboration among academic and industrial leaders, whose areas of interest are in molecular biology/molecular genetics, imaging, data science, clinical oncology, public health, and/or other related areas, leading to the development of early cancer diagnostics.
- Conduct clinical/epidemiological studies (e.g., cross-sectional, prospective, retrospective) in order to evaluate the predictive value of biomarkers.
- Improve the informatics infrastructure to facilitate precompetitive data and/or image sharing on biomarker discovery, development, and validation.
- Serve as a core resource so that NCI and the cancer community at large can leverage the well-developed EDRN infrastructure and expertise in order to facilitate translational cancer research, clinical utility trials, and cancer prevention and therapeutic trials.
An applicant may request a budget of up to $550K in FY2023 and $785K per year in FY2024-FY2027 (direct costs).
September 19, 2022
Sudhir Srivastava, Ph.D., M.P.H., National Cancer Institute (NCI), Telephone: 240-276-7028
Email: srivasts@mail.nih.gov