Acute myeloid leukemia (AML) is caused by proliferation of mutated myeloid progenitor cells. The standard chemotherapy regimen does not efficiently cause remission as there is a high relapse rate. Resistance acquired by leukemic stem cells is suggested to be one of the root causes for relapse. Therefore, there is an urgency to develop new drugs for therapy. Repurposing approved drugs for AML can provide a cost-friendly, time-efficient, and affordable alternative. The multiscale interactome network is a computational tool that can identify potential therapeutic candidates by comparing mechanisms of the drug and disease. Communities that could be potentially experimentally validated are detected in the multiscale interactome network using the algorithm CRank. In this research, we identify therapeutic candidates for AML and their mechanisms from the interactome, and isolate prioritized communities that are dominant in the therapeutic mechanism that could potentially be used as a prompt for pre-clinical research to focus on biological functions and mechanisms that are associated with the disease and drug. The results from the interactome and its combination with the prioritized communities are evaluated through literature search and Gene Ontology (GO) enrichment analysis.