Article: Advocating for automation in animal research: using home cage monitoring to advance welfare, reproducibility and scientific openness Open Access
Independent resource.
Abstract:
Recent advances in artificial intelligence (AI) and machine learning (ML) technologies present significant opportunities to drive substantial progress in laboratory animal science. However, to realise this potential, the animal research community must radically change the way in which it generates, annotates and shares large datasets to enable and foster the required interdisciplinary collaboration.
Herein, we highlight the importance that new developments in automated welfare and phenotypic analysis for laboratory animals offer in reducing subjectivity, limiting influencing factors, increasing the rigor, robustness and quality of data, and enhancing the relevance and translatability of animal studies. In particular, we discuss the opportunities and potential impact of home cage monitoring (HCM) systems on reducing both the numbers of animals used in research (reduction) and their discomfort (refinement). We also address the significant logistical, cultural and resource challenges that the research animal community must overcome to attract and collaborate effectively with informaticians and data scientists to realise these ambitions.