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Solutions
Helping Life Sciences Teams Move Faster with Trusted Healthcare Data Partnerships
BCONZ helps pharmaceutical, biotechnology, healthcare AI and research organizations identify research-ready healthcare data through governed, institution-led partnerships that support scientific discovery.
Teams can start by reviewing available research data modalities, submitting a research data request, or contacting BCONZ to discuss a specific program.
Trusted partnership model
BCONZ supports teams with disciplined research planning, governed access and end-to-end collaboration across health systems and life sciences.
Science first
Focus on research outcomes and scientific rigor over transactional data access.
Enterprise-ready
Designed for regulated workflows with governance, quality review, and collaboration built in.
Who We Support
Solutions for every research organization
BCONZ partners with pharmaceutical, biotech, AI, CRO, academic and device teams to solve development and research challenges.
Pharmaceutical Companies
Accelerate drug development with research-ready cohorts, biomarkers and trial feasibility support.
Explore SolutionsBiotechnology Companies
Support early discovery, target validation and rare disease research with purpose-built datasets.
Explore SolutionsHealthcare AI
Power model development and validation with multi-modal healthcare data and clinical labels.
Explore SolutionsContract Research Organizations
Improve study feasibility, site selection and patient identification with data-driven insights.
Explore SolutionsAcademic Research
Enable collaborative studies and publications with institution-led research data partnerships.
Explore SolutionsMedical Devices
Validate devices and digital biomarkers with imaging, outcomes and wearable data.
Explore SolutionsSolutions by Industry
Tailored support for each life sciences organization
Each solution block explains the research challenge, BCONZ support model, relevant data modalities and example projects.
Pharmaceutical
Typical challenges
- Patient stratification
- Biomarker discovery
- Clinical trial feasibility
- Real-world evidence
How BCONZ helps
- Research-ready cohorts
- Longitudinal data
- Molecular data
- Imaging
- Outcome data
Relevant healthcare data
- Research-ready cohorts
- Longitudinal data
- Molecular data
- Imaging
- Outcome data
Typical project examples
- Target validation
- Companion diagnostics
- Protocol optimization
Biotechnology
Typical challenges
- Rare disease research
- Early discovery
- Target validation
How BCONZ helps
- Clinical and molecular datasets
- Multi-omics
- Specialized cohorts
Relevant healthcare data
- Clinical and molecular datasets
- Multi-omics
- Specialized cohorts
Typical project examples
- Biomarker research
Healthcare AI
Typical challenges
- Model development
- Model validation
- Bias assessment
- Generalizability
How BCONZ helps
- Multi-modal datasets
- Clinical labels
- Imaging
- Pathology
- Longitudinal outcomes
Relevant healthcare data
- Multi-modal datasets
- Clinical labels
- Imaging
- Pathology
- Longitudinal outcomes
Typical project examples
- Foundation models
- Clinical AI
- Decision support
Contract Research Organizations
Typical challenges
- Study feasibility
- Site selection
- Patient identification
How BCONZ helps
- Feasibility assessment
- Research landscape
- Cohort estimation
Relevant healthcare data
- Feasibility assessment
- Research landscape
- Cohort estimation
Typical project examples
- Study planning
- Protocol alignment
- Operational readiness
Academic Research
Typical challenges
- Population studies
- Publications
- Grant-funded research
How BCONZ helps
- Collaborative datasets
- Institutional partnerships
- Scientific oversight
Relevant healthcare data
- Collaborative datasets
- Institutional partnerships
- Scientific oversight
Typical project examples
- Cohort discovery
- Translational analysis
- Published research
Medical Devices
Typical challenges
- Device validation
- Digital biomarkers
- Clinical evidence
How BCONZ helps
- Imaging
- Longitudinal outcomes
- Wearables
Relevant healthcare data
- Imaging
- Longitudinal outcomes
- Wearables
Typical project examples
- Validation studies
- Signal development
- Evidence generation
Research Areas
Research and development focus areas supported by BCONZ
Practical pathways for drug discovery, precision medicine, healthcare AI research and real-world evidence generation.
Drug Discovery
Clinical Development
Precision Medicine
Healthcare AI
Digital Health
Real World Evidence
Biomarker Discovery
Companion Diagnostics
How Engagement Works
Partnering through a premium research timeline
Organized steps from research discussion through ongoing collaboration, with data partners engaged where institution-led review is required.
1
Research Discussion
2
Feasibility
3
Governance
4
Project Definition
5
Dataset Preparation
6
Delivery
7
Ongoing Collaboration
Why Organizations Choose BCONZ
Trusted partnership advantages for research teams
Premium support that connects healthcare data, governance and collaborative research execution.
Trusted Partnerships
Enterprise teams work alongside institution-led partners to align goals and preserve trust.
Research-ready Data
Data is curated, linked and reviewed to support science rather than just transactions.
Responsible Governance
Access, oversight and review are embedded at every stage of the research workflow.
Collaborative Ecosystem
Research organizations, healthcare providers and life sciences teams engage in shared, purpose-driven programs.
Frequently Asked Questions
Answers to common research partnership questions
Clear guidance on collaboration, cohorts, governance and data modalities.
Can projects involve multiple healthcare organizations?
Yes. We support multi-institutional research through governed partnerships and collaborative data programs.
Can custom cohorts be defined?
Custom cohorts are defined with research partners and healthcare organizations to meet study objectives while preserving governance.
How is governance handled?
Governance is managed through institution-led review, scoped access and research-purpose commitments.
Can imaging and genomics be combined?
Yes. We support multi-modal research by combining imaging, molecular and clinical signals within trusted partnerships.
How are research priorities discussed?
Priorities are shaped through collaborative planning sessions with research sponsors, clinical partners and data governance teams.
Let's Discuss Your Next Research Project