Literature-based discovery of new candidates for drug repurposing

Abstract

Drug development is an expensive and time-consuming process; these could be reduced if the existing resources could be used to identify candidates for drug repurposing. This study sought to do this by text mining a large-scale literature repository to curate repurposed drug lists for different cancers. We devised a pattern-based relationship extraction method to extract disease-gene and gene-drug direct relationships from the literature. These direct relationships are used to infer indirect relationships using the ABC model. A gene-shared ranking method based on drug target similarity was then proposed to prioritize the indirect relationships. Our method of assessing drug target similarity correlated to existing anatomical therapeutic chemical code-based methods with a Pearson correlation coefficient of 0.9311. The indirect relationships ranking method achieved a significant mean average precision score of top 100 most common diseases. We also confirmed the suitability of candidates identified for repurposing as anticancer drugs by conducting a manual review of the literature and the clinical trials. Eventually, for visualization and enrichment of huge amount of repurposed drug information, a chord diagram was demonstrated to rapidly identify two novel indications for further biological evaluations.

The prescribable drugs with efficacy in experimental epilepsies (PDE3) database for drug repurposing research in epilepsy

“…[13][14][15][16] Hence, we employed literature mining of Medline abstracts to create the database. [13][14][15][16] Hence, we employed literature mining of Medline abstracts to create the database.…”

“…Literature mining of Medline abstracts has been used to identify potential new indications and disease associations of drugs. [13][14][15][16] Hence, we employed literature mining of Medline abstracts to create the database. Data were extracted from Medline abstracts through computational literature mining followed by "crowdsourced" manual curation ( Figure 1).…”

“…In addition, Medline abstracts have been used successfully to collate drug indications and drugdisease associations. [13][14][15][16] Reading the complete texts of all 500 publications included in the database would be impracticable. However, researchers using the database to identify promising drugs should perform detailed review and critical appraisal of the studies cited for those drugs.…”

“…[13][14][15][16] Reading the complete texts of all 500 publications included in the database would be impracticable. The database has been assembled from information present within Medline abstracts; the full publications have not been analyzed or critically appraised.…”

Rediscovering Don Swanson:The Past, Present and Future of Literature-based Discovery

“…Don is the father of the field of drug repurposing, which proposes new uses for existing approved drugs (e.g., Weeber et al, 2003; Yang et al, 2017). Prediction of adverse drug effects follows a similar type of logic (e.g., Shang et al, 2014; Hristovski et al, 2016), as does detection of co-morbidities and other relations among drugs, diseases and genes (Frijters et al, 2010; Ding et al, 2013; Vos et al, 2014).…”