Exploring Drug Repurposing for Rare Diseases: Leveraging Biomedical Knowledge Graphs and Access to Scientific Literature

Drug repurposing presents a potential solution for finding new therapies for rare and orphan diseases. The limited number of patients affected by rare diseases, combined with scarce research and the financial burden of clinical trials, creates a significant barrier to developing new drugs. Drug repurposing utilizes the known safety profile and effectiveness of existing medications to fast-track the development of life-saving therapies. Recently drug repurposing has focused on utilizing biomedical knowledge graphs to uncover hidden connections between diseases and drugs, revealing promising candidates for repurposing. Because most knowledge graphs in biomedical domain are made by text-mining scientific literature we decided to compare the amount of knowledge contained in open access and controlled (subscription only) access literature. Elsevier and Every Cure make logical partners and allowed the project to use Elseviers ability to access both controlled and open access publications and its proprietary Elsevier AI technology to construct the knowledge graph. Notwithstanding the fact that more than 50% of relationships in drug repurposing for rare diseases can be found in open access content, 45% of relationships remain only in controlled access. We argue that this is due to the large number of edges supported by single reference in the entire biomedical knowledge graph and does not reflect an intrinsic difference between open and controlled access.