This project will use advanced AI to integrate genomic, metabolomic, and biomarker data for the discovery of novel risk signatures and therapeutic targets in Type 2 Diabetes (T2D). By leveraging large-scale Australian biobank datasets and global consortia resources, the project will pinpoint genetic variants and metabolic pathways associated with disease onset, progression, and treatment response. Machine learning models will prioritise targets linked to insulin resistance, beta-cell dysfunction, and metabolic inflammation. Findings will be validated across diverse populations to ensure global relevance and translatability. Partnerships with diagnostic companies, clinical laboratories, and research institutes will accelerate the transformation of discoveries into clinically applicable biomarker panels. These panels will enable earlier and more precise identification of at-risk individuals and guide the development of targeted therapies. 

Call for Partnerships:
We welcome partnerships with universities, health services, primary care networks, technology providers, government agencies, and community health organisations to provide data access, clinical expertise, digital health capacity, and co-funding for large-scale trials.