RHGT , a novel model for Drug Repurposing; the process of utilizing available drugs for newer indications and diseases. The model is a Relation-aware Heterogeneous Graph Transformer, it learns relations between drugs, diseases, and genes; resulting with useful drugdisease associations. Although many Graph Neural Networks (GNNs) have been developed for Drug Repurposing tasks, RHGT model still outperformed them. The networking of the model can be divided into three consecutive embedding modules; subtype-level network, node-level network, and an edge-level network. The output of the first level is the input of the other two, and the output of the second level is the input the last one; level-by-level learning. Each level serves as an irreplaceable factor to the high-performance RHGT demonstrates.