Solicitation: 75N95020R00005
NCATS established the NCATS Collaborative Scientific Platform in 2018 to integrate, manage, secure, and analyze data across the translational spectrum, from basic research through pre-clinical research, clinical research, clinical implementation, and public health improvements. This platform-as-a-service (PaaS) currently supports NCATS, the National Cancer Institute (NCI), and the President’s Emergency Plan for AIDS Relief (PEPFAR). The Platform has integrated hundreds of live intramural and third-party data sources in support of dozens of ongoing, critical scientific projects that rely on continuous access, data, and analyses within the Platform. The Collaborative Scientific Platform is now the standard means for accessing and collaboratively analyzing NCATS screening data for dozens of investigators at both NCATS and NCI, and for accessing and analyzing RNASeq and several kinds of proteomics data at NCI. Pilot projects are underway within the Platform to extend its use to clinical applications that will support NCATS (the Clinical and Translational Science Awards (CTSA) and Rare Diseases Clinical Research Network (RDCRN)), NCI, and PEPFAR.
The Platform is based on the Gotham software platform from Palantir, Inc., under contract number HHSN271201800020I, awarded in 2018, and continued under contracts 75N95020P00041 (2019) and 75N95020D00003 (2020).
Purpose and Objectives: Provide a commercial, enterprise-level collaborative translational research scientific platform as a service (PaaS) to integrate, manage, secure, and analyze data across the translational research spectrum.
Project requirements:
- A commercial software solution deployable on day one of the project and that can be configured within expedited timelines. Respondents must possess FedRAMP authorization so that an agency authority to operate (ATO) can be granted upon award of a contract.
- An open data architecture, where data always remains under the full control of NCATS and can be easily exported in open, non-proprietary data formats via open application programming interfaces (APIs). The software should be built on an open, distributed microservices architecture with open, well-documented representational state transfer (REST) APIs that are designed to seamlessly interface with other systems, adapt to meet evolving needs, and avoid system lock-in.
