Junzhou Huang, Jenkins Garrett Endowed Professor in the Department of Computer Science and Engineering at The University of Texas at Arlington, has received a major federal grant to advance the use of artificial intelligence in antibody drug discovery research that could help accelerate the medical response to future pandemics. A $3.1 million R01 grant from the National Institutes of Health will support Dr. Huang’s work in applying machine learning to design antibodies that bind to viruses and other antigens a foundational step in developing treatments for infectious diseases and autoimmune diseases.

Traditionally, this process is slow and expensive, with it often taking more than a decade and billions of dollars to bring a drug to market. Huang aims to significantly reduce that timeline. This project is about using AI to automate and improve the early stages of drug development, particularly antibody design, Huang said. If we can predict the right binding interactions computationally, it could dramatically speed up the pipeline and lower the risks and costs of drug development.

The project builds on Huang’s long-standing research in protein structure prediction, including a high-ranking finish by his team in a prestigious international AI challenge. Competing against major institutions like Google DeepMind and the University of Washington, Huang’s team placed sixth overall in protein structure prediction and ranked first in the protein contact map prediction track.

The recognition opened doors to new collaborations, including a partnership with Tao Wang at UT Southwestern and Jun Wang at New York University. The team has already coauthored a high-impact paper published in Nature Cancer and is actively working to bridge the gap between academic research and real-world pharmaceutical applications.The goal is to shorten the response time to react to emerging diseases by enabling faster, AI-driven antibody development, Huang said. This could make a huge difference the next time we face a public health crisis.

Source: https://www.uta.edu/news/news-releases/2025/08/06/ai-research-targets-faster-drug-development