Adam Amara, cofounder & CEO at Turing Biosystems, discusses network-based modelling and multiomics integration on metabolic networks, multilayer networks to integrate mutiomics and clinical data with knowledge graphs, and the use of TuringDB.ai to analyse large biomedical knowledge graphs and build digital twins.

This project leverages graph neural networks (GNNs) to predict the antiviral potency of small molecules by analyzing their molecular structures and interactions. By learning complex patterns in chemical data, GNNs can identify promising drug candidates with high efficacy against viruses. The insights gained from this approach aim to accelerate antiviral drug discovery and development.