UTA researchers received a $3.1 million NIH grant to develop an AI-based computational framework that predicts how genes and drugs may work together, with the goal of identifying more effective drug combinations. The project combines deep learning, Bayesian statistics, computational biology, multi-omics data, and high-throughput drug screening, with researchers from UTA and UT Southwestern collaborating on the work. By improving the prediction and validation of drug synergies, the team hopes to make precision medicine more effective while reducing the time and cost of developing targeted treatments.
