National Heart, Lung, and Blood Institute 1R43HL179155-01

Eliminating Donor Availability Disparities in Hematopoietic Stem Cell Transplantation with AI-based Prediction of Permissive HLA Mismatches in the Context of Posttransplant Cyclophosphamide

The project aims to develop a machine learning model to predict safe donor-recipient mismatches in hematopoietic stem cell transplantation using posttransplant cyclophosphamide, targeting improved outcomes for ethnic minority patients and reducing health disparities.

Description

Allogeneic hematopoietic stem cell transplantation (HCT) can cure various blood malignancies and disorders, but ethnic minority patients face lower donor availability and suboptimal transplant outcomes due to their underrepresentation in donor registries. To address this, the project aims to develop a machine learning model to predict safe donor-recipient mismatches in the current standard of care of posttransplant cyclophosphamide (PTCy). This model will help improve the selection of mismatched donors for ethnic minority patients, enhancing their HCT success rates and reducing health disparities.

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