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Bioinformatics Research

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The Bioinformatics Research team develops and utilizes software tools and analytic methods to discover new patterns and biomarkers, predict clinical outcomes, facilitate cellular therapy matching, and model inventory sources to save and improve patient lives. At the intersection of science and technology, this team pursues high-impact and innovative research and produces strategic applications for the business to bridge the transition from research to operations. The CIBMTR Bioinformatics Research Program moves in the direction of computational biomedicine with activities in four main areas: Genomics / omics & high-throughput bioanalytics, machine learning & clinical predictions, cellular therapy matching, and donor registry modeling.

Donor Registry Modeling

To determine how to best meet the needs of all patients in need of cellular therapy, the Bioinformatics Research Program models the composition of the Donor Registry and Biobank in order to project and optimize the need and availability of cellular therapies for patients in need. These and related projects help increase the likelihood of finding a match for patients who have HLA types more commonly found outside the US and seek to prepare a ready source of cellular therapy in case of acute radiation emergency. The Bioinformatics Research Program ensures that CIBMTR and NMDP are at the forefront of research and that new technologies and clinical findings can be incorporated into the operational side of CIBMTR and NMDP as swiftly and seamlessly as possible. 

Genomics / Omics & High-Throughput Bioanalytics

Program staff members develop processing and annotation workflows to characterize variation in donors and cellular therapy products, patients, and transplant donor-recipient pairs. The team leverages technology platforms that enable integrated, scalable data analysis and high-throughput bioanalytics on a variety of omics sources, including whole-genome, exome, protein, and methylation sequencing and microarrays. Bioinformatics researchers analyze patterns in donors and recipients to identify associations with transplant outcomes and factors that contribute to event-free survival.

Machine Learning & Clinical Predictions

The Bioinformatics Research Program prepares platforms for data science applications and builds and trains models for analysis of business and clinical data collected in daily operations at CIBMTR and NMDP and through network partners and research trials. Applications from search archives and donor availability, for example, provide insight into areas of future focus and improvement for NMDP operations. The Bioinformatics Research Program examines:

  1. Provider-reported clinical data and electronic medical records 
  2. Patient-reported data on the five areas of financial, cognitive, physical, sexual, and emotional health
  3. In-depth collection of omics data from therapy sources and recipients

Collating and integrating these data, team members investigate and develop clinical predictions and applications for improving survival outcomes and quality of life for all.

Cellular Therapy Matching

The Bioinformatics Research Program investigates algorithms to improve the prediction of missing data and the selection of cellular therapies for patients for best survival and quality of life outcomes. Program researchers improve the collection, analysis, validation, and utilization of data on donors and patients with diverse ancestry for feature improvements. The Bioinformatics Research team utilizes fresh approaches leveraging graph imputation and matching are tested for accuracy, flexibility, and scalability to produce applications for NMDP and ensure new clinical results can be incorporated into the matching algorithm as soon as possible. Finally, researchers translate research results and evidence-based guidelines to user interfaces to optimize cellular therapy matching and donor selection for physicians and transplant centers.


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