Drug Repurposing Prediction for Immune-Mediated Cutaneous Diseases using a Word-Embedding-Based Machine Learning Approach.

ABSTRACT: Immune-mediated diseases affect more than 20% of the population, and many autoimmune diseases affect the skin. Drug repurposing (or repositioning) is a cost-effective approach for finding drugs that can be used to treat diseases for which they are currently not prescribed. We implemented an efficient bioinformatics approach using word embedding to summarize drug information from more than 20 million articles and applied machine learning to model the drug-disease relationship. We trained our drug repurposing approach separately on nine cutaneous diseases (including psoriasis, atopic dermatitis, and alopecia areata) and eight other immune-mediated diseases and obtained a mean area under the receiver operating characteristic of 0.93 in cross-validation. Focusing in particular on psoriasis, a

SUBMITTER: Patrick MT 

PROVIDER: S-EPMC6387843 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature