AI diffusion models tailor drug molecules to custom-fit protein targets, speeding drug development and evaluation

University of Virginia School of Medicine scientists have developed a bold new approach to drug development and discovery ...
News Medical

GCARDTI: Advancing drug-target interaction prediction with hybrid graph learning

The identification of drug-target Interactions (DTIs) represents a pivotal link in the process of drug development and design. It plays a crucial role in narrowing the screening range of candidate ...
Phys.org

GraphBAN: Making drug discovery faster and more affordable through artificial intelligence

UM researchers have developed a deep learning model to predict compound protein interactions. GraphBAN is an inductive graph-based approach. The model is all about discovering new drug candidates in ...
inc42

Graph AI Raises $3 Mn To Automate Drug Safety Monitoring for Pharma Firms

Pharmaceutical-sector focussed AI startup Graph AI’s $3 Mn seed funding round was led by Bessemer Venture Partners The startup will use the capital for product innovation, team expansion, and ...
insideHPC

Why the World’s Biggest Brands Are Betting Big on Graph

In 2020, UHG deployed graph to track COVID-related hospitalizations, discharges, test results, and more at a provider and county level. Another use case involves predicting potential patient adverse ...