Discovering candidates for drug repositioning based on biomedical semantic information

Abstract

It is a problem to be high costs, long research time and high failure rate during drug development process. In order to solve this problem, drug repositioning which is to use known drugs to new diseases has been an important part of research because it would reduce costs and time of drug development process. Previous research has focused on the literature mining and simple database integration using ABC model. ABC model is to assume that A-C relationship could be deduced by integrating known A-B and B-C relationships. In this paper, we suggest the template model using database integration to discover candidates for drug repositioning based on biomedical semantic information. Our research model finds a similar disease pair with shared symptoms and then shared association genes, pathways or biological processes. Also, the similar disease pair could share also their drugs. From this semantic information, it is possible to discovery candidates for drug repositioning. From the research validation, our candidates for drug repositioning are actually experimented in clinical trials database and the biomedical literature. Therefore, we notice that our research model is a useful tool for drug developers. In the future work, we are going to organize a template and take various biological relationship databases in order to create more elaborate model.