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The BioMedical Evidence Graph (BMEG) integrates different types of biomedical data into a unified graph for efficient application of machine learning and discovery algorithms across heterogeneous data types. BMEG will leverage the petabytes of genomics data available for tumor samples from repositories like the National Cancer Institute’s Genomic Data Commons to predict drug sensitivity, patient outcomes, and other clinically relevant phenotypes. The BMEG data model is instantiated in a scalable graph database optimized for storing and querying graphs containing terabytes of vertices and edges distributed across a multi-machine cluster. This graph is the store of record for the BMEG. It maintains the connections between projects, donors, samples, molecular data and treatment evidence and assures that these entities are associated correctly.