Smart Lids for deep multi-animal phenotyping in standard home cages

Area of Science:

• Preclinical research
• Animal health monitoring
• Biotechnology

Background:

• The preclinical research field faces a reproducibility crisis and translational gap.
• Current manual health monitoring methods are labor-intensive, low-throughput, biased, and stressful for animals.
• Existing smart cages have limited adoption due to low throughput, high cost, or infrastructure requirements.

Purpose of the Study:

• To develop a novel, high-throughput, multi-animal health monitoring system for standard preclinical research cages.
• To address the limitations of existing animal monitoring technologies, including single-animal tracking and low data density.
• To enhance the accuracy and reliability of health metrics in animal models.

Main Methods:

• Development of the "Smart Lid" assay device that fits standard home cages and racks.
• Creation of a computer vision pipeline (Multi-Organism Tracker - MOT) for multi-animal tracking.
• Design of specialized ear tags for improved computer vision-based tracking accuracy.

Main Results:

• The Smart Lid system transforms standard racks into high-throughput monitoring platforms.
• The MOT pipeline achieves over 97% accuracy in multi-animal tracking.
• The system provides 21 health-related metrics, including activity, feeding, social interactions, and sleeping patterns, at a low operational cost (<$100/month).

Conclusions:

• The Smart Lid and MOT system offer a robust, accurate, and affordable solution for multi-animal health monitoring.
• This technology can significantly improve preclinical research by enhancing data reliability and animal welfare.
• The system's adaptability and comprehensive metric collection pave the way for advanced animal health assessment.