MATCH: Advanced Machine Learning AlgoriThm for Compatible Human Leukocyte Antigen

A next-generation HLA-matching framework would have broad adoption potential among transplant centers, hospital systems, diagnostic and sequencing companies, and cell/gene therapy developers. The technology transition goals for this project is to deliver a validated, standards-based HLA matching framework (algorithms, analysis results, benchmarks) ready for adoption by transplant centers, labs, and regulators. This framework will be able to embed into commercial decision-support tools and services, license to diagnostics and cell therapy partners, and support clinical implementation and integration. If this project is successful, a validated and modern HLA matching framework will exist that uses deep sequencing and new transplant strategies, show improved clinical outcomes, and package the tools, standards, and pathways needed for rapid clinical and commercial deployment, effectively redefining how donor-recipient matching is done. 

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