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What is a biomedical Data Lakehouse?
A biomedical data lakehouse is a powerful data platform designed to unify diverse health datasets—including clinical, multi-omics, imaging, and sensor data, among others—into a single, accessible environment. Tailored for the unique needs of health and biomedical research, it supports seamless data retrievals, QA/QC, de-duplication, de-identification, linkage, harmonization and organization, making data both discoverable and ready for use.
Researchers gain a secure, high-performance environment where data is cataloged, searchable, and readily prepared for analysis within a Trusted Research Environment, accelerating insights while maintaining strict data governance.
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Why lifebit?
The only lakehouse purpose-built for biomedical data
Only Lakehouse to seamlessly fetch EHR & NGS data
Connecting to and retrieving data from major EHRs like Epic, Cerner, and MedTech, as well as NGS providers and on-site sequencing facilities, Lifebit’s Lakehouse enables secure, flexible data access across extensive U.S. and global healthcare networks.
Fast, specialized data harmonization & product creation
Lifebit is trusted by top pharma and data providers for creating data products at scale. With industry-leading expertise in harmonizing to data models such as OMOP, linking and cataloging data, Lifebit has proven efficiencies across a global data network of over 250M patient datasets.
Compliant with the latest FDA RWE Requirements
Lifebit’s Trusted Data Lakehouse™ is the only lakehouse to meet stringent FDA real-world evidence guidelines, offering complete data lineage and provenance with each retrieval. Full audit trails ensure compliance and give users transparency to meet FDA standards.
How it works
Effortless and compliant data integration, standardization and cataloging
- 1. Create the organisation and workspace
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The process begins by setting up a new organization or selecting an existing one. Data administrators then create the primary workspace where data access is managed and organized. During this setup, admins specify essential details, such as AWS settings, to ensure secure integration with the data infrastructure.
- 2. Connect and set up existing data sources
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Data administrators define the retrieval methods and frequency (e.g., real-time, daily, weekly) for data connections. Lifebit’s Trusted Data Lakehouse™ supports multiple retrieval options, including Batch, EHR integration (e.g., Epic, Cerner), Batch FHIR, NGS system integration (e.g., Tempus, Foundation Medicine), and Direct Database Connection.
- 3. Perform QA, data cleaning, and harmonization
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Data is standardized to common data models, such as OMOP, using Lifebit’s proprietary AI automation for EHR data. NGS data is transformed from formats like FASTQ to annotated, prioritized VCF, allowing seamless downstream analysis. Lifebit integrates with leading tools like DRAGEN, Parabricks, Sentieon, and GATK to ensure high-quality, interoperable datasets that are ready for analysis.
- 4. Catalog data to establish a single source of truth
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All standardized data is securely cataloged within Lifebit’s platform, featuring advanced search, audit trails, and data lineage. Role-based access control ensures that researchers can easily access, query, and retrieve data compliantly. This comprehensive catalog simplifies data reuse and supports reproducible research and future discoveries.
- 5. Assess data for study readiness
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Lifebit’s Trusted Data Lakehouse™ automates quality assessments, data cleaning, de-duplication, and de-identification, allowing users to confirm that data meets fit-for-purpose criteria.
- 1. Create the organisation and workspace
-
The process begins by setting up a new organization or selecting an existing one. Data administrators then create the primary workspace where data access is managed and organized. During this setup, admins specify essential details, such as AWS settings, to ensure secure integration with the data infrastructure.
- 2. Connect and set up existing data sources
-
Data administrators define the retrieval methods and frequency (e.g., real-time, daily, weekly) for data connections. Lifebit’s Trusted Data Lakehouse™ supports multiple retrieval options, including Batch, EHR integration (e.g., Epic, Cerner), Batch FHIR, NGS system integration (e.g., Tempus, Foundation Medicine), and Direct Database Connection.
- 3. Perform QA, data cleaning, and harmonization
-
Data is standardized to common data models, such as OMOP, using Lifebit’s proprietary AI automation for EHR data. NGS data is transformed from formats like FASTQ to annotated, prioritized VCF, allowing seamless downstream analysis. Lifebit integrates with leading tools like DRAGEN, Parabricks, Sentieon, and GATK to ensure high-quality, interoperable datasets that are ready for analysis.
- 4. Catalog data to establish a single source of truth
-
All standardized data is securely cataloged within Lifebit’s platform, featuring advanced search, audit trails, and data lineage. Role-based access control ensures that researchers can easily access, query, and retrieve data compliantly. This comprehensive catalog simplifies data reuse and supports reproducible research and future discoveries.
- 5. Assess data for study readiness
-
Lifebit’s Trusted Data Lakehouse™ automates quality assessments, data cleaning, de-duplication, and de-identification, allowing users to confirm that data meets fit-for-purpose criteria.
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