Powering Federal Health Discovery
Lifebit turns Fragmented Federal Data into Unified, Federated Discovery
Demonstrating how Lifebit’s federated platform turns multi-source biomedical data into a single auditable research workflow — what would normally take a research consortium years.
“With Lifebit’s data transformation and mapping tools, we can process and harmonize distributed data through a single centralized, auditable, and reproducible workflow — something that would normally take years to achieve.”
Consensus feedback from NLM Federated Data Workshop participants
Challenges
- Siloed, fragmented data assets both within and between labs and ICs
- Requiring NIH authentication to any cloud-based system
- No ability to analyze large distributed cohorts
- Limited standardization of data and data elements within or between disease areas
- Lack of privacy-preserving methods to identify patients across studies
Outcomes
- First federated platform ever deployed in NIH
- Research authentication via NIH Identity Access Management (IAM)
- Collaboration without moving sensitive data — reducing delays and costs
- Reduced privacy and governance risk
- Faster scientific discovery through increased intra- and inter-IC data access
impact
1hr
Data access request
down from 2 weeks
8
ICs onboarded
across NIH
19
pan-IC datasets
mapped to the OMOP CDM
100%
Data standardization
achieved
FAQs
A federated platform for the NIH research community
Lifebit’s federated platform connects to NIH data assets where they live and brings analytics to them. Researchers describe a question once; the platform dispatches it across sources; only governance-cleared aggregate results return.
What the architecture demonstrated:
One auditable workflow, many data custodians
Every step of the federated analysis is captured in an end-to-end audit trail — one researcher question, one workflow, one log, even when the underlying data lives across multiple NIH-affiliated repositories.
Years-long harmonization compressed into a workflow
Data harmonization that traditionally requires multi-year programs is implemented as a re-runnable analysis layer — the same harmonized view can be regenerated whenever a new source is added.
Compute-to-data, by default
NIH data custodians retain custody. Researchers do not pull patient-level records into their own environments. The federation layer enforces this architecturally.
A platform researchers actually want to use
Familiar tooling — Jupyter, R, Nextflow, standard biomedical libraries — runs inside the federated environment, so researchers don’t trade workflow ergonomics for governance compliance.
Next step
Ready to harmonize distributed data without moving it?
Lifebit’s federated platform is the analytics layer behind sovereign and consortium-scale biomedical research programs worldwide.