A foundation model for clinician-centered drug repurposing
Harvard University · Stanford University · +7 more institutions
Abstract
Drug repurposing—identifying new therapeutic uses for approved drugs—is often a serendipitous and opportunistic endeavour to expand the use of drugs for new diseases. The clinical utility of drug-repurposing artificial intelligence (AI) models remains limited because these models focus narrowly on diseases for which some drugs already exist. Here we introduce TxGNN, a graph foundation model for zero-shot drug repurposing, identifying therapeutic candidates even for diseases with limited treatment options or no existing drugs. Trained on a medical knowledge graph, TxGNN uses a graph neural network and metric learning module to rank drugs as potential indications and contraindications for 17,080 diseases. When…
Citation impact
- FWCI
- 52.07
- Percentile
- 100%
- References
- 57
Authors
10- KHKexin Huang
Harvard University, Stanford University
- PCPayal Chandak
Harvard–MIT Division of Health Sciences and Technology
- QWQianwen Wang
Harvard University
- SHShreyas Havaldar
Mount Sinai Health System, Icahn School of Medicine at Mount Sinai
- AVAkhil Vaid
Mount Sinai Health System, Child Health and Development Institute, Icahn School of Medicine at Mount Sinai
Topics & keywords
- Drug repositioning
- Foundation (evidence)
- Repurposing
- Drug
- Medicine
- Pharmacology
- Intensive care medicine
- Computational biology