RePurpose: An LLM-Assisted, Source-Traceable Drug Repurposing Tool with Retrospective Validation on Clemastine in Multiple Sclerosis

Summary: Thus far, evidence for drug repurposing is contained in target-, drug-, trial-, and literature-based data sources that are challenging to synthesize for non-specialists. Here, we introduce RePurpose, a web-based tool that takes as input a topic written in plain language and returns candidate drugs built from data in Open Targets, ClinicalTrials.gov, UniProt, and PubMed. For queries in the form of a goal, RePurpose filters candidate drugs by whether they modulate all targets implicated in the goal in the corresponding direction. Every candidate has a source that contributes evidence: a structured database, a clinical trial, or a proposal from a large language model. An adjustable ranking adjusts the order of candidates from well-studied to less well-known candidate drugs. We retrospectively tested RePurpose with the trial drug clemastine, which was being considered as a remyelinating agent in multiple sclerosis (MS). RePurpose retrieved clemastine in each replicate of the mechanism-worded queries, but in no replicates of the disease-worded queries, and no structured query retrieved it without the language model enabled. Its ranked outputs reflected the evidence supporting clemastine but not later evidence of harm in progressive MS, which was reachable only through an on-demand literature search. Our results imply that RePurpose may be better at tracing evidence around a hypothesis than generating new hypotheses. Availability and Implementation RePurpose Pharma is freely accessible at https://www.repurposepharma.com/. For code and more information on the application, see: https://github.com/nayagamnitin-hub/RePurpose-Pharma.