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Research-Ready Healthcare Data
Trusted Healthcare Data for Scientific Discovery
BCONZ helps connect healthcare organizations with life sciences researchers through governed access to research-ready clinical, molecular and real-world healthcare data.
Explore how these data capabilities support life sciences and healthcare AI solutions, or discuss an institution-led collaboration through our healthcare data partnership pathway.
Data ecosystem
A research data platform that brings clinical, molecular, imaging and real-world sources together for purpose-built science.
Governed access
Access is granted only for approved scientific studies and defined research use.
Research-ready quality
Data is curated, linked and reviewed to support reliable research workflows.
Research Data Ecosystem
Modern research combines multiple data modalities
The strongest scientific programs connect clinical, molecular, imaging and real-world sources rather than relying on isolated datasets.
1
Clinical Data
↓2
Genomics
↓3
Multiomics
↓4
Medical Imaging
↓5
Digital Pathology
↓6
Real World Data
↓7
Research Insights
Research Data Modalities
Data types built for scientific collaboration
Research-ready healthcare data is organized for researchers, sponsors and healthcare organizations through governed collaboration, not open-ended data brokerage.
Longitudinal Clinical Data
Patient journeys, encounters, diagnoses and treatment histories assembled for research-ready cohorts.
Typical Research Uses
- Outcome studies
- Cohort definition
- Epidemiology
Genomics
Sequencing, variant calls and sample metadata paired with clinical context for precision discovery.
Typical Research Uses
- Target identification
- Biomarker research
- Population genomics
Transcriptomics
RNA expression profiles linked to sample and clinical data for functional and translational studies.
Typical Research Uses
- Gene expression analysis
- Pathway modeling
- Disease stratification
Proteomics
Protein measurements curated with sample provenance for mechanism research and therapeutic discovery.
Typical Research Uses
- Target validation
- Biological signatures
- Drug response modeling
Medical Imaging
Radiology and clinical imaging datasets prepared for advanced visual analytics and AI training.
Typical Research Uses
- Imaging biomarkers
- Model development
- Phenotype extraction
Digital Pathology
High-resolution pathology data aligned with clinical endpoints for research-grade histopathology studies.
Typical Research Uses
- Tissue phenotyping
- Algorithm validation
- Digital diagnostics
Biospecimens
Linked specimen metadata and provenance information that support translational research and assay development.
Typical Research Uses
- Biomarker discovery
- Sample tracking
- Translational studies
Real World Data
Claims, device, and longitudinal care records curated to complement clinical and molecular datasets.
Typical Research Uses
- Health economics
- Patient journey analysis
- Post-market research
Disease Areas
Research focus across clinical specialties
Trusted data partnerships that support oncology, cardiology, neurology and other strategic healthcare research areas.
Oncology
Cardiology
Neurology
Rare Diseases
Diabetes
Respiratory
Women's Health
Infectious Disease
How Research Projects Begin
Structured steps from question to secure delivery
A transparent project timeline connects research planning, governance, dataset preparation and delivery.
1
Research Question
Define the scientific objective and identify the data needed to answer it.
2
Feasibility Assessment
Evaluate data availability, cohort size and alignment to study requirements.
3
Governance Review
Confirm research scope, access controls and partner commitments before data preparation.
4
Dataset Preparation
Curate, link and standardize data elements for reproducible research workflows.
5
Quality Review
Validate completeness, consistency and provenance before secure delivery.
6
Secure Delivery
Provide access through trusted channels for approved research teams.
Responsible Governance
Governance that supports trusted research partnerships
Controls and oversight are built into every research engagement without calling out specific laws.
Purpose-specific access
Data use is scoped to approved scientific objectives and governed research plans.
Institutional oversight
Research programs are overseen by clinical and academic stakeholders to preserve trust.
Research agreements
Agreements define data scope, permitted analysis and collaboration expectations.
Privacy by design
Data handling is built for privacy with minimal exposure and strong controls.
Who We Support
Research and development partners across the enterprise
A platform designed for pharmaceutical sponsors, biotech innovators, healthcare AI teams and academic research programs.
Pharmaceutical
Biotechnology
Healthcare AI
Academic Research
CRO
Medical Devices
Frequently Requested Data
Modern FAQs for research-ready datasets
Accessible answers to common research questions about cohort design, governance and collaboration. For a specific study, use the research data request form.
Can BCONZ create custom cohorts?
Yes. We work with research teams and healthcare partners to define study cohorts from available data modalities while preserving governance and scientific fit.
Do you support longitudinal studies?
Longitudinal patient histories are a core part of our research-ready datasets, enabling studies over time and outcomes analysis.
Can genomic data be linked?
Genomic and molecular data can be linked to clinical and outcomes records within trusted data partnerships.
How are research projects reviewed?
Each project is reviewed for purpose, governance, data suitability and partner commitments before work begins.
Can multiple institutions collaborate?
Yes. We support collaboration across hospitals, research centers and life sciences organizations through governed data partnerships.
Ready to Explore Research Data?