A New UI for AI-Driven Drug Repurposing in Rare Genetic Diseases: Real-World Impact from the NCATS Translator Program
Year: 2025
Type: conference-paper
Abstract: The NIH NCATS Translator program now exposes > 200 million semantically harmonized edges, weaving together genomic, pharmacologic, and clinical evidence from over 20 Knowledge Providers—spanning resources such as ClinVar, DrugCentral, DisGeNET, SPOKE, SemMedDB, and real-world EHR aggregates. Leveraging Translator’s reasoning APIs and graph-machine-learning pipelines, our team has systematically surfaced candidate therapeutics for rare monogenic disorders and validated several in patient-specific studies. To democratize this workflow, we built a web-based interface featuring “Smart Queries” that identify drugs predicted to modulate a target gene or treat a disease. This talk will present (i) clinical successes achieved to date, (ii) a live walkthrough of the new UI, and (iii) practical guidance on integrating Translator into rare-disease research pipelines worldwide—accelerating the path from graph insight to patient impact.
Author: Andrew Crouse
Institution: University of Alabama at Birmingham
Language: English
Subfield: Computational Theory and Mathematics
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4413913798