NCI Office of Data Sharing (ODS) Data Jamboree (Abstract Submissions): Submission #40
Submission information
Submission Number: 40
Submission ID: 145206
Submission UUID: b891f55b-46aa-4398-96e3-139c12ea54b2
Submission URI: /nci/ods-data-jamboree/abstractsubmissions
Submission Update: /nci/ods-data-jamboree/abstractsubmissions?token=ovZ9OHBcmhKPzwqMQselrB8PfgpjO76alpgd17-VF5g
Created: Mon, 06/23/2025 - 23:49
Completed: Mon, 06/23/2025 - 23:51
Changed: Mon, 06/23/2025 - 23:51
Remote IP address: 10.208.28.57
Submitted by: Anonymous
Language: English
Is draft: No
Presenter Information
Abstract Information
Methods to enable data interoperability
Interoperability, FHIR, Federated, Analytics
Building a FHIR-Based Data Integration Platform for Pediatric and AYA Cancer Research
Pediatric and adolescent/young adult (AYA) cancer research is hampered by fragmented data silos, inconsistent data standards, and labor-intensive harmonization processes that limit the pace of discovery and the delivery of precision care. To address these challenges, we propose an innovative data integration platform built on the Fast Healthcare Interoperability Resources (FHIR) standard. Leveraging oncology-specific FHIR profiles such as mCODE and extending them with pediatric- and AYA-specific data elements, the platform will enable automated, real-time extraction and harmonization of clinical, molecular, imaging, and patient-reported data from electronic health records and research databases across institutions
In this project we will explore the feasibility of deploying FHIR servers at participating sites, supporting secure, standards-based data exchange and federated analytics, thus preserving patient privacy while enabling collaborative research on rare and heterogeneous pediatric cancers. Automated APIs and tools will drastically reduce the manual effort required to prepare data for research, while supporting longitudinal tracking of patients from diagnosis through survivorship. By integrating diverse data modalities and facilitating seamless data sharing, the platform will accelerate biomarker discovery, risk stratification, and the development of personalized therapies. Ultimately, this project will establish a scalable, interoperable data ecosystem, transforming pediatric and AYA cancer research and care, and serving as a model for other rare disease domains.
We will get hands on with sample and representative datasets, compare the project goals against existing implementation guides and/or demonstrations, and craft a development plan toward achieving a minimum viable product (MVP). To the extent possible, and leveraging open-source assets, we will seek to demonstrate these features in code.
In this project we will explore the feasibility of deploying FHIR servers at participating sites, supporting secure, standards-based data exchange and federated analytics, thus preserving patient privacy while enabling collaborative research on rare and heterogeneous pediatric cancers. Automated APIs and tools will drastically reduce the manual effort required to prepare data for research, while supporting longitudinal tracking of patients from diagnosis through survivorship. By integrating diverse data modalities and facilitating seamless data sharing, the platform will accelerate biomarker discovery, risk stratification, and the development of personalized therapies. Ultimately, this project will establish a scalable, interoperable data ecosystem, transforming pediatric and AYA cancer research and care, and serving as a model for other rare disease domains.
We will get hands on with sample and representative datasets, compare the project goals against existing implementation guides and/or demonstrations, and craft a development plan toward achieving a minimum viable product (MVP). To the extent possible, and leveraging open-source assets, we will seek to demonstrate these features in code.