On July 10, 2026, researchers at Rutgers University unveiled a groundbreaking artificial intelligence (AI) program designed to enhance the health assessment of lab animals. This innovation, developed in collaboration with international experts, was published in the journal Lab Animal.
AI Enhancements in Animal Health Monitoring
The team, led by Jeetendra Eswaraka, Ph.D., focused on noninvasive tracking of locomotor activity in mice. Traditional methods of assessing animal health were often limited due to the timing of assessments, which typically occur during the animals' less active daytime hours. This new AI approach allows for continuous monitoring and rapid detection of potential health issues.
By analyzing locomotor activity data using a large language model (LLM), the AI can alert veterinary staff about mice that may be developing health problems 3 to 5 days before visible symptoms appear. This early detection represents a significant advancement in lab animal care.
Impact of Continuous Monitoring
Eswaraka expressed pride in the project, stating, "This project on using machine learning and digital biomarkers to improve the health care of our animals has been a very fulfilling experience." This innovative technology not only enhances animal welfare but also improves operational efficiency by over 50%.
Michael E. Zwick, Ph.D., who also contributed to the study, emphasized the transformative potential of AI in research methodologies. He remarked, "AI programs such as this one are changing the way research is being conducted, and the Office for Research is at the forefront, using all available tools to better support Rutgers researchers." The ongoing development of such technologies is expected to have a profound impact on research practices globally.
Accreditation and Ethical Standards
The Rutgers University Animal Care Program (RUAC) has recently been reaccredited by AAALAC International, an organization that promotes humane treatment of animals in research. This reaccreditation confirms that RUAC meets and exceeds the highest ethical, regulatory, and technological standards, ensuring continued support for world-class research.
The study titled Enhanced health evaluation in mice using continuous home-cage monitoring and machine learning: a multicentric study highlights the collaborative efforts of researchers worldwide. This initiative is poised to set new benchmarks in the care and assessment of laboratory animals.
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