Administrative Supplements for P30 Cancer Centers Support Grants (CCSG) to Enhance the Utility of Data Available through the Childhood Cancer Data Initiative (CCDI) Ecosystem

Organization
NIH
Type
NIH
Application Due Date
06-30-2023
Comments
If interested in applying, contact Sarah Laye at slaye@som.umaryland.edu
Brief Description

In December 2019, Congress approved funding for the Childhood Cancer Data Initiative (CCDI) that aims at improving treatment and outcomes for childhood and adolescent and young adult (AYA) cancer patients by accelerating data collection, analysis, and sharing.

The three major goals of CCDI are:

-gathering data from every child, adolescent, and young adult (AYA) diagnosed with a childhood cancer, regardless of where they receive their care

-creating a national strategy of appropriate clinical and molecular characterization to speed diagnosis and inform treatment for all types of childhood cancers

- developing a platform and tools to bring together clinical care and research data that will improve preventive measures, treatment, quality of life, and survivorship for childhood cancers.

The National Cancer Institute (NCI) is creating a pediatric and AYA cancer data ecosystem to aggregate and generate data of multiple types from multiple sources to accelerate innovative discovery of biomarkers and therapies in pediatric and AYA cancers. The data will include key information from basic research, pre-clinical studies, clinical trials, epidemiology and population studies, cancer surveillance, and routine healthcare settings including but are not limited to molecular data, imaging data, drug screen assay data, real-world patient data, patient-reported outcome, electronic health records, and cancer registry data that will be shared in accordance with FAIR Principles (findable, accessible, interoperable, and reusable). To date, a variety of datasets have been collected and shared through the CCDI data ecosystem including omics data (e.g., DNA/RNA sequencing, proteomic characterization), patient treatment or demographic data (phenomics), medical imaging, preclinical models (e.g., drug screens), environmental exposure, clinical trials (e.g., intervention, response, adverse events), longitudinal outcomes or survivorship data including recurrence and subsequent cancers, and other relevant patient information. This data ecosystem will continue to grow data and new resources will be added into the ecosystem on a continual basis. This presents an unprecedented opportunity for all types of investigators to learn from data on every child, adolescent and young adult represented in order to improve our fundamental understanding of pediatric cancer and new therapeutic interventions.