Researchers at UC San Diego, Linnaeus Bioscience, and the Seattle Children's Research Institute have developed a new AI-powered technology called MycoBCP that analyzes images of tuberculosis cells to identify potential drug candidates. This breakthrough aims to address the urgent need for new TB treatments due to the rise of drug-resistant strains.
University of California - San DiegoFeb 7 2025 Tuberculosis is a serious global health threat that infected more than 10 million people in 2022. Spread through the air and into the lungs, the pathogen that causes "TB" can lead to chronic cough, chest pains, fatigue, fever and weight loss.
Linnaeus Bioscience is a San Diego-based biotechnology company founded on technology developed in the UC San Diego School of Biological Sciences laboratories of Professor Joe Pogliano and Dean Kit Pogliano. Their bacterial cytological profiling method provides a shortcut for understanding how antibiotics function by rapidly determining their underlying mechanisms.
This is the first time that this kind of image analysis using machine learning and AI has been applied in this way to bacteria. Tuberculosis images are inherently difficult to interpret by the human eye and traditional lab measurements. Machine learning is much more sensitive in being able to pick up the differences in shapes and patterns that are important for revealing underlying mechanisms.
"A critical component of progressing towards new drug candidates is defining how they work, which has been technically challenging and takes time," said Parish, a co-author of the study. "This technology expands and accelerates our ability to do this and allows us to prioritize which molecules to work on based on their mode of action. We were excited to collaborate with Linnaeus in their work to develop this technology to M. tuberculosis.
Establishing Linnaeus Bioscience in the regional San Diego biotechnology hub allowed Joe and Kit Pogliano to push the BCP technology out into the marketplace, where other companies could have access to it. The company now receives samples from all over the world for rapid analysis and identification of new bacterial drug candidates.
TUBERCULOSIS DRUG DISCOVERY ARTIFICIAL INTELLIGENCE MACHINE LEARNING HEALTH TECHNOLOGY
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