The Translational Data Accelerator (TDA) advances translational research at Fred Hutch Cancer Center by reducing the technical and policy barriers to using sensitive data effectively. Our goal is to accelerate data driven discovery via self-service data exploration applications, reliable data models, multimodal datasets and AI enabled data science tools. We aim to enable staff across clinical trials, clinical research, and laboratory sciences to spend less time overcoming technical or policy barriers and more time advancing science.
The Translational Data Accelerator is responsible for the infrastructure, data products and data governance processes that support translational science, including:
- The translational data platform including its infrastructure and data access applications
- Trusted, governed modeled data products, analytic datasets and research archives
- Data governance policies, process, stewardship supports, and workflows enabling (re)use of these data
- AI and LLM enablement via technology and governance supports for responsible use of AI in our work and research
Our Resources
Our Data
The Translational Data Accelerator develops and maintains trusted data models that make clinical and molecular data easier to discover, analyze, and share for research. These models are built from raw data we ingest from a variety of sources to support the diverse data needs of our translational data community.
Our Applications
The Translational Data Accelerator provides a suite of applications that support researchers with varying levels of technical expertise and through the different stages of the translational research lifecycle.
Our Support
Our team hosts a variety of support resources for translational researchers, from Data House Calls, to regular Data Deep Dive workshops, to data extract or workflow building requests to direct consulting projects.
Accelerator Staff
We are part of the Office of the CDO specifically focused on translational data resources. You can find more about the broader team on ocdo.fredhutch.org.
Data Science
The Data Science team develops the data models, analytical datasets, and AI-enabled capabilities that help researchers turn data into discovery. Working across clinical, molecular, and multimodal data, the team maintains research-ready data products, supports translational research initiatives, and develops methods that enable reproducible and scalable scientific analysis.
Data Engineering & Platform
The Data Engineering & Platform team builds and operates the infrastructure, applications, and data pipelines that power the Translational Data Accelerator. The team is responsible for securely integrating, processing, and delivering data while maintaining the reliability, performance, and security of the research data platform.
Data Governance
The Data Governance team enables the responsible use of clinical and research data by developing policies, stewardship practices, and access processes that balance scientific opportunity with privacy, security, and regulatory requirements. The team works closely with researchers and institutional partners to reduce barriers to data access while ensuring that sensitive data are used appropriately, ethically, and in accordance with institutional standards.
Our Guiding Principles
Our approach to supporting Fred Hutch staff focuses on the following guiding principles.
Prioritize Data Democratization and Ethical Data Stewardship
We are committed to data democratization - making it accessible, understandable, and actionable for everyone in our organization, regardless of technical expertise. Through intuitive tools and a culture of ethical data stewardship, we ensure data serves as a driving force for innovation and responsible decision-making across healthcare and research.
Build, Foster and Empower Data Communities of Practice
We are dedicated to building and supporting data-related communities of practice that span the Fred Hutch, from the clinic to the research labs. By providing shared platforms, tools, open documentation, training and peer-to-peer programs, we empower our teams to collaborate, share knowledge, and establish best practices that drive innovation in their fields.