Highly-pathogenic avian influenza is a growing problem, both in agriculture and beyond. Waterfowl are the primary carriers, but the virus easily spreads to other birds and has made the jump to other species, from cattle to even elephant seals on remote South Atlantic islands.<\/p>\n
While it has yet to spread between humans, 71 people have contracted HPAI from animals since 2024, and two died. HPAI has had a severe impact on the poultry industry and the people who rely on it for food and employment.<\/p>\n
The U.S. Department of Agriculture\u2019s Animal and Plant Health Inspection Service is investing $100 million into treating HPAI, with Utah State University receiving $1.9 million to develop novel treatments, drugs and therapies through AI and machine learning. Associate Professor Rakesh Kaundal, who is the director of the USU Bioinformatics Facility<\/a> and leads the Kaundal Artificial Intelligence and Advanced Bioinformatics Lab (KAABiL<\/a>), will spearhead the effort. His project was one of only 58 proposals selected for funding by APHIS out of a total of 417, and the only one selected from Utah.<\/p>\n At the heart of KAABiL\u2019s efforts is machine learning, a subfield within artificial intelligence focused on using adaptive algorithms to identify patterns within massive and complex datasets. Using conventional laboratory techniques, it might take years to analyze the thousands of ways that a virus like HPAI interacts with its host\u2019s genes, proteins and biological pathways. By using machine learning to narrow the search to the most promising targets, that process speeds up to a matter of weeks.<\/p>\n \u201cMachine learning helps us analyze biological information at a scale and speed that humans alone cannot achieve,\u201d Kaundal said. \u201cIt quickly sorts through vast amounts of data to identify which host pathways the virus depends on most and which therapeutic strategies are most likely to work. This acts as a force multiplier, allowing us to focus laboratory testing on only the most promising options, saving time, reducing cost, and accelerating the development of safe, effective, and long-lasting solutions for U.S. agricultural biosecurity.\u201d<\/p>\n By using the funding to build and expand advanced computational facilities, KAABiL will establish the infrastructure for new insights into how HPAI works and which treatments are likely to be effective against the virus. Kaundal expects new tools for detecting HPAI infections, improved antivirals for treating sick animals and people and mutation-resistant vaccines to come out of the work done with the new funding.<\/p>\n \u201cThis grant does not simply fund a single project,\u201d he said. \u201cIt establishes a durable AI and big data ecosystem within the Quinney College of Agriculture and Natural Resources, with our lab serving as a central engine for more interdisciplinary innovations and workforce development in these areas. It positions USU at the forefront of applying artificial intelligence and bioinformatics to real-world agricultural problems, moving discoveries from abstract computation to practical tools that protect producers and consumers.<\/p>\n Because KAABiL collaborates broadly with USU\u2019s Institute of Antiviral Research, and Department of Animal, Dairy, and Veterinary Science, and other USU and USDA labs, the funding will indirectly support the spread of knowledge and skills throughout the university. Related research in areas such as crop disease forecasting, climate-resilient agriculture, soil microbiome analysis, and precision livestock management all stand to benefit from the technologies and expertise developed through the work on HPAI.<\/p>\n \u201cGraduate students, postdoctoral researchers, and faculty will receive hands-on experience with AI-based biological modeling, reproducible data science, and real-world agricultural biosecurity problems,\u201d Kaundal said. \u201cThese trainees will carry AI and data-centric thinking back to their home departments, multiplying the impact of the investment and embedding advanced computational literacy across the college. The tools, workforce and partnerships developed through this project will support future innovations in sustainable livestock production, disease prevention and food system resilience.\u201d<\/p>\n