Flywheel is a cloud-based research data platform that ingests imaging and related data from multiple sources, curates it to common standards, automates processing and machine learning pipelines and provides for secure collaboration and regulatory compliance.
Flywheel Clinical Research Solutions
Improve Research Productivity, Secure Collaboration, and Reproducibility
- PACS & EMR Integration
- Metadata Management w/ Search
- Quality Controls
- Automated Pre-processing & Pipelines
- Customization via APIs, Python, & Matlab
Maximize Value of Clinical Data with Scalable Machine Learning Solution
- Labeling, Classification, and Image Annotation
- Manage Training Data Sets
- Automate Training Workflows
- Deploy Models for Translational Testing
- Provenance to Support Regulatory Approvals
Clinical Trials & Multi-Center Studies
Streamline Data Collection, Processing, and Sharing for Clinical Trials
- Secure Sharing & Collaboration
- De-Identification Workflow
- IRB-Compliant Projects
- Research Workflow Automation
- HIPAA & GDPR Compliance
Maximize the Value of Your Clinical Data
Streamline access to clinical imaging & related data
Aggregate data from multiple sources including your PACS/VNA, EMR and digital pathology for a comprehensive view of your patients.
Empower researchers with comprehensive data processing and analysis tools
Curate disparate data to consistent quality standards with labeling, classification, and image annotation workflows.
Reduce costs while ensuring privacy and security
Provide secure access and collaboration while ensuring IRB, HIPAA, GDPR, and 21 CFR Part 11 compliance with provenance, flagging and audit trails.
Your Strategic Partner for Clinical Research
Flywheel delivers a full range of research data management technology and professional services to help with your clinical research and execute your R&D strategy.
“Flywheel allows us to extract maximum value out of the assets we already have by standardizing data pipelines across all research projects. We are able to much more quickly access and collaborate on data while feeling confident that everyone is working off a shared, secure dataset that is always current. Our researchers are able to work much more efficiently on artificial intelligence and collaborative research while spending less time managing data.”
Peter McCaffrey, MD
Director of Pathology Informatics and Laboratory Information Systems and Assistant Professor of Pathology at the University of Texas Medical Branch