Drug development is a process that is incredibly expensive and time-consuming. Computational drug repurposing can help to assign new indications for approved drugs. It is capable to reduce the cost of drug developments. Machine learning models have been introduced to repurpose drugs long before. Recent studies formulate computational drug repurposing problem as a latent link prediction task on a heterogenous network. A number of computational methods have been developed based on graph neural networks.