Development of an open-source, flexible framework for interinstitutional data sharing and collaboration.

9583 Background: Clinical information, “-omic” datasets, and tissue samples are becoming more difficult to harmonize and manage for advanced data mining. We believe that clinical research data can be centralized and provide direct access to sample availability and associated data from a variety of information stores. Methods: We obtained a standardized set of anonymized patient data from the International Neuroblastoma Risk Group. The cohort consists of more than 11,000 children diagnosed worldwide between 1974 and 2002. The data consist of 34 metrics, such as age at diagnosis, stage of tumor, and other clinical and biological markers. We instantiated the dataset into a Postgres database, and using the Django web framework, created a data model for rapid development of tools and views and built a front-end interface for generating complex queries. To test the feasibility of accessing information on disparate and geographically distinct data samples, we have a formal agreement with the Children's Oncology ...