Data4Cure's AI-Driven Drug Target Discovery and Cancer Subtyping at AACR 2025
Data4Cure will present two new research abstracts at the 2025 American Association for Cancer Research (AACR) Annual Meeting. These presentations highlight Data4Cure's advances in AI-based approaches for drug target discovery and large-scale cancer subtyping using foundation models applied to large collections of sequencing data.
In the first study, titled "Knowledge graph AI-based prioritization of drug target candidates" (Abstract LB112/13), Data4Cure researchers leveraged the company's large-scale biomedical knowledge graph encompassing over 4 billion relations across more than 1 million entities including genes, diseases, drugs, pathways, cell types and tissues. To prioritize candidate cancer drug targets, they trained and optimized 17 state-of-the-art knowledge graph embedding (KGE) and graph neural network (GNN) models. The best such models significantly outperformed standard machine learning approaches, uncovered clusters of predicted targets enriched for specific biological functions and identified novel target candidates, including within previously underexplored functional classes.
The second study, titled "Foundation model integration of >180,000 bulk RNA-seq samples identifies cancer subtypes with prognostic and treatment response associations" (Abstract LB343/6), describes the development of RNA1, a novel transformer-based foundation model trained on over 180,000 bulk RNA-seq profiles. RNA1 enables systematic assignment of cancer samples to molecular subtypes and the discovery of new subtypes across more than 36,000 tumor samples. RNA1-based subtyping shows significant associations with survival outcomes as well as with drug response outcomes on published clinical trial datasets, outperforming previously published subtyping approaches across a majority of evaluated benchmarks.
Both projects build upon Data4Cure's Biomedical Intelligence Cloud platform and its mission to help turn complex multi-modal data into knowledge that drives biomedical research and therapeutic innovation.
-Data4Cure Team