The Biostatistics Program at Fred Hutch Cancer Center is recognized as one of the leading centers for biostatistical research and collaboration in the United States. Our faculty develop and apply rigorous statistical methods to advance science across cancer prevention, early detection, treatment, and health policy, as well as cardiovascular disease, Alzheimer’s disease, autoimmune diseases, and basic biological research including molecular biology, genomics, and immunogenetics.
With deep expertise in statistical innovation, our faculty collaborate across disciplines including public health, epidemiology, clinical sciences, data science, and artificial intelligence. We partner with investigators at Fred Hutch, the University of Washington, Seattle Children's Research Institute, and national research networks. We design studies, analyze complex biomedical and clinical data, and lead methodological advances in genomics, medical imaging, real-world evidence, and AI-driven analytics.
To showcase the breadth and impact of our research, we organize our expertise into eight Biostatistics Research Hubs. Each hub highlights affiliated faculty, core methods, data resources, and collaborative projects across Fred Hutch and beyond. Explore the hubs to connect with top biostatisticians and learn more about the scientific questions driving our work.
Research Hubs
Statistical Learning and Data Science
Faculty develop statistical and machine learning methods for complex biomedical data, supporting individualized prediction, adaptive trial design, and data integration in population health studies.
Statistics in Genomics and Genetics
Faculty design statistical tools for high-throughput molecular data, including transcriptomics, epigenomics, and gene–environment interactions. Their work supports discovery in cancer genomics, integrative multi-omics, and population-scale risk modeling.
Statistics in Imaging
Faculty develop methods for extracting quantitative information from biomedical images, including MRI, pathology, and radiomics. Their work supports spatial modeling, early detection, and image-based monitoring of cancer progression and treatment response.
Clinical Trials and Data Coordination
Faculty lead the design and coordination of clinical trials and data centers, developing methods that support precision medicine, prevention, and real-world impact.
Statistics in Epidemiology
Faculty advance statistical methods for epidemiologic research, including observational studies, screening programs, and longitudinal population data. Their work supports causal inference, biomarker validation, and cancer prevention strategies that inform clinical guidelines and public health policy.
Health Policy Statistics
Faculty design models to evaluate healthcare interventions, screening strategies, and policy alternatives. Their work supports decision-making through simulation, comparative effectiveness, and equity assessment, translating real-world data into evidence for national health guidelines and system planning.
Mobile and Wearable Data Science
The Mobile and Wearable Data Science Hub develops statistical and machine-learning methods for analyzing smartphone- and wearable-derived health data. Work spans high-frequency longitudinal sensor streams, linkage with clinical data, and tools for monitoring, surveillance, and personalized intervention.
Teaching Statistics in the Health Sciences
Faculty lead reproducible and accessible education initiatives in statistical science for health researchers and professionals. Their work fosters innovation in teaching, mentorship, and curriculum development using real-world biomedical data and open-source tools.
Funded Projects
Biostatistics faculty lead a wide portfolio of federally and privately funded research projects, advancing statistical methods and applications in cancer, public health, and biomedical science. Explore current PI-led grants spanning methodological innovation, collaborative studies, and career development awards.
Consortia and Clinical Trials
Our faculty lead multi-institutional consortia and clinical trials, advancing trial design, monitoring, and analysis across oncology, screening, diagnostics, immunotherapy, and precision medicine. Methods include adaptive and Bayesian designs, platform trials, biomarker validation, and real-world evidence integration, with impact on prevention, early detection, and treatment worldwide.
Biostatistics Collaboration and Consulting Center (BC3)
BC3 provides consulting and collaborative support for investigators across Fred Hutch, UW, and Seattle Children’s. Services include study design, power analysis, statistical methods, data interpretation, and grant or manuscript preparation, offering an entry point to deeper collaborations with our faculty statisticians.