Biostatistics and Informatics Core
- Institution
- Seattle Children's Hospital, WA
- Principal investigator
- Sonya Heltshe
- Funding
- $189K
- Duration
- 2010–2030
Moonbase score
Still being scored
Abstract
PROJECT SUMMARY/ABSTRACT The Biostatistics and Informatics Core is a newly formed Core to support the central aims of the University of Washington (UW) Cystic Fibrosis (CF) Research and Translation Center (CFRTC). It is formed under a continuity of leadership and out of services that have been a cornerstone of the CFRTC by providing novel design, analytics and quantitative methods and analytics. With the advent of big data in CF, a new bioinformatics component has been added to the Core focused on applying cutting-edge computational methods to analyze “omics” data. The Core leaders bring services, expertise, and a long history of collaboration with CF researchers, especially in diabetes, pancreatic function and highly effect CF transmembrane conductance regulator (CFTR) modulator therapy. Further, the Core has a strong training component for CF researchers and clinicians. The Core establishment is an acknowledgement of the increasing complexity of translational and basic research in CF and the need for a dedicated resource to provide integrated analytic support to the UW CFRTC research base. The services focus on biostatistical support, study design, epidemiologic methods, comparative effectiveness and cost analyses, ancillary study enrichment, and novel bioinformatics services to guide and assist the research base with analysis of large- scale omics data. The Core aims are consistent with the overall CFRTC: 1) adapt biostatistical methods and outcomes to the post-HEMT era, 2) enhance understanding of non-pulmonary comorbidities in CF and improve decision making and policy through effectiveness and cost analytics, 3) and perform state-of-the art bioinformatics on human and animal data to understand pathophysiology and clinical manifestations of CF post-HEMT. The Core will foster collaboration across the CFRTC through training and sharing existing databases that enable ancillary analyses.
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