Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.09.25.311142v1?rss=1 Authors: Agastheeswaramoorthy, K., Sevilimedu, A. Abstract: Drug repositioning is emerging as an increasingly relevant option for rare disease therapy and management. Various methods for identifying suitable drug candidates have been tried and range from clinical symptomatic repurposing to data driven strategies which are based on the disease-specific gene or protein expression, modification, signalling and physiological perturbation profiles. The use of Artificial Intelligence (AI) and machine learning algorithms (ML) allows one to combine diverse data sets, and extract disease-specific data profiles which may not be intuitive or apparent from a subset of data. In this case study with Fragile X syndrome and autism, we have used multiple computational methodologies to extract profiles, which are then combined to arrive at a comprehensive signature (disease DEG). This DEG was then used to interrogate the large collection of drug-induced perturbation profiles present in public databases, to find appropriate small molecules to reverse or mimic the disease-profiles. We have labelled this pipeline Drug Repurposing using AI/ML tools - for Rare Diseases (DREAM-RD). We have shortlisted over 100 FDA approved drugs using the aforementioned pipeline, which may potentially be useful to ameliorate autistic phenotypes associated with FXS. Copy rights belong to original authors. Visit the link for more info