ArticleLaboratory animals2026
Challenges and expectations on the use of automated home cage monitoring for advancing laboratory animal care and welfare.
Article in Laboratory animals, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
COST Action TEATIME unites experts to advance automated monitoring technologies for laboratory animals, with a focus on Home Cage Monitoring (HCM) systems. The use of HCM has great potential to revolutionise welfare monitoring by enabling continuous, non-invasive tracking of physiological and behavioural patterns in group-housed animals within their undisturbed housing environment. These systems capture spontaneous behaviours - such as feeding, grooming, social interactions and sleep cycles - across day and night phases, offering objective data for welfare and scientific assessments. This real-time monitoring might allow for early detection of distress, disease progression and subtle welfare changes, supporting timely interventions and refined humane endpoints. Unlike traditional clinical scoring, which relies on brief daily observations, HCM provides longitudinal, individualised insights and reduces observer bias. It might also facilitate better characterisation of positive affective states, contributing to more holistic welfare evaluations. Despite technological progress, challenges remain in data integration, sensitivity and standardisation across facilities. Effective implementation requires real-time alert capabilities, robust data management, and interdisciplinary collaboration among scientists, veterinarians and data experts. HCM systems should complement - not replace - human expertise, enriching welfare monitoring and scientific reproducibility. Their integration can improve husbandry, refine severity assessments, advancing both animal welfare and scientific replicability.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.