SMART CAGES, BETTER WELFARE: SUPPORTING THE 3RS IN ANIMAL RESEARCH WITH HOME-CAGE MONITORING AND SYSTEM SELECTION
DOI:
https://doi.org/10.26873/SVR-2247-2025Keywords:
laboratory animals, automated behaviour tracking, refinement, continuous data collection, stressAbstract
High welfare standards for animals used in research is as much an ethical issue as it is a cornerstone of high-quality science. Researchers can improve both animal welfare and data reliability by implementing strategies that reduce stress in experimental animals. One modern and effective approach is to monitor animals within their familiar home-cage environment. Home-cage monitoring (HCM) systems integrate multiple approaches to automatically, continuously, and non-invasively monitor the physiology and behaviour of laboratory animals within their home environments. HCM favours the animals’ natural rhythms and behaviours while reducing stress from various sources and the need for human intervention. In this article, we explore how HCM contributes to the 3Rs framework introduced by Russell and Burch and focus particularly on how to select the most appropriate HCM system for specific research needs. We discuss available resources and practical limitations for system choice, and provide a brief outlook on the evolving role of artificial intelligence to analyse HCM data. We also discuss the opportunities and barriers to HCM adoption, particularly in relation to countries with developing research structure and limited funding in Europe. Our central message is clear: use of HCM technologies supports 3Rs and promotes both better science and better animal welfare.
Pametne kletke, večja dobrobit: podpora načelom 3R v raziskavah na živalih s spremljanjem v domači kletki in ustrezno izbiro sistema
Izvleček: Visoki standardi dobrobiti živali v raziskavah niso zgolj etična obveznost, temveč tudi temelj visokokakovostne znanosti. Raziskovalci lahko izboljšajo tako dobrobit živali kot tudi zanesljivost podatkov z uvedbo strategij, ki zmanjšujejo stres pri poskusnih živalih. Eden izmed sodobnih in učinkovitih pristopov je spremljanje živali v njihovem domačem okolju. Sistemi za spremljanje v domači kletki (HCM, angl. home-cage monitoring) združujejo več pristopov za samodejno, neprekinjeno in neinvazivno spremljanje fiziologije in vedenja laboratorijskih živali v njihovem domačem okolju. HCM podpira naravne ritme in vedenja živali ter zmanjšuje stres iz različnih virov in potrebo po posegih človeka. V članku opisujemo, kako HCM prispeva k načelom 3R, ki sta ga uvedla Russell in Burch, s posebnim poudarkom na izbiri najprimernejšega sistema HCM za specifične raziskovalne potrebe. Obravnavamo razpoložljive vire in praktične omejitve pri izviri sistema ter podajamo kratek pogled na razvijajočo se vlogo umetne inteligence pri analizi podatkov HCM. Prispevek obravnava tudi priložnosti in ovire pri uvajanju HCM, zlasti v povezavi z državami z manj razvito raziskovalno infrastrukturo in omejenimi sredstvi v Evropi. Naše osrednje sporočilo je jasno: uporaba tehnologij HCM podpira načela 3R ter spodbuja boljšo dobrobit živali in boljšo znanost.
Ključne besede: laboratorijske živali; avtomatsko spremljanje vedenja; izboljšave; kontinuirno zbiranje podatkov; stres
References
Abdollahi Nejat M, Stiedl O, Smit AB, van Kesteren RE. Continuous locomotor activity monitoring to assess animal welfare following intracranial surgery in mice. Front Behavi Neurosci 2024; 18: 1457894. doi: 10.3389/fnbeh.2024.1457894
Agency EM. Guideline on the principles of regulatory acceptance of 3Rs (replacement, reduction, refinement) testing approaches. London: European Medicines Agency , 2016.
Anderson N. Animal welfare and the human-animal bond in student education–how can we understand animal feelings? How do we ask for consent from a horse? Slov Vet Res 2025; 62(1): 5–7. doi: 10.26873/SVR-2194-2025
Bailey J. Does the stress of laboratory life and experimentation on animals adversely affect research data? A critical review. Altern Lab Anim 2018; 46(5): 291-305. doi: 10.1177/026119291804600501
Bailey KR, Crawley JN. Anxiety-related behaviors in mice. 2011.
Bailoo JD, Reichlin TS, Wuerbel H. Refinement of experimental design and conduct in laboratory animal research. ILAR J 2014; 55(3): 383-91. doi: 10.1093/ilar/ilu037
Bains RS, Forrest H, Sillito RR, et al. Longitudinal home-cage automated assessment of climbing behavior shows sexual dimorphism and aging-related decrease in C57BL/6J healthy mice and allows early detection of motor impairment in the N171-82Q mouse model of Huntington’s disease. Front Behav Neurosci 2023; 17: 1148172. doi: 10.3389/fnbeh.2023.1148172
Bains RS, Wells S, Sillito RR, Armstrong JD, Cater HL, Banks G, et al. Assessing mouse behaviour throughout the light/dark cycle using automated in-cage analysis tools. J Neurosci Methods 2018; 300: 37-47. doi: 10.1016/j.jneumeth.2017.04.014
Balcombe JP, Barnard ND, Sandusky C. Laboratory routines cause animal stress. Contemp Top Lab Anim Sci 2004; 43(6): 42-51.
Barnum CJ, Blandino P, Deak T. Adaptation in the corticosterone and hyperthermic responses to stress following repeated stressor exposure. J Neuroendocrinol 2007; 19(8): 632-42. doi: 10.1111/j.1365-2826.2007.01571.x
Bartelik A, Čater M, Cevik ÖS, Franco NH, Voikar V. Focus on novel approaches: Home-cage monitoring of laboratory mice. Scand J Lab Anim Sci 2024;50(1).
Blenkuš U, Gerós AF, Carpinteiro C, Aguiar PdC, Olsson IAS, Franco NH. Non-invasive assessment of mild stress-induced hyperthermia by infrared thermography in laboratory mice. Animals 2022; 12(2): 177. doi: 10.3390/ani12020177
Bohlen M, Hayes ER, Bohlen B, Bailoo JD, Crabbe JC, Wahlsten D. Experimenter effects on behavioral test scores of eight inbred mouse strains under the influence of ethanol. Behav Brain Res 2014; 272: 46-54. doi: 10.1016/j.bbr.2014.06.017
Bohnslav JP, Wimalasena NK, Clausing KJ, Dai YY, Yarmolinsky DA, Cruz T, et al. DeepEthogram, a machine learning pipeline for supervised behavior classification from raw pixels. Elife 2021; 10: e63377. doi: 10.7554/eLife.63377
Bolaños LA, Xiao D, Ford NL, et al. A three-dimensional virtual mouse generates synthetic training data for behavioral analysis. Nat Methods 2021; 18(4): 378-81. doi: 10.1038/s41592-021-01103-9
Brakel K, Aceves AR, Aceves M, Hierholzer A, Nguyen Q-N, Hook MA. Depression-like behavior corresponds with cardiac changes in a rodent model of spinal cord injury. Exp Neurol 2019; 320: 112969. doi: 10.1016/j.expneurol.2019.112969
Camilleri MP, Bains RS, Williams CK. Of mice and mates: automated classification and modelling of mouse behaviour in groups using a single model across cages. Int J Comput Vis 2024; 132(12): 5491-513. doi: 10.1007/s11263-024-02118-3
Castelhano-Carlos MJ, Baumans V. The impact of light, noise, cage cleaning and in-house transport on welfare and stress of laboratory rats. Lab Anim 2009; 43(4): 311-27. doi: 10.1258/la.2009.0080098
Chapa JM, Maschat K, Iwersen M, Baumgartner J, Drillich M. Accelerometer systems as tools for health and welfare assessment in cattle and pigs–a review. Behav Processes 2020; 181: 104262. doi: 10.1016/j.beproc.2020.104262
Clay AW, Bloomsmith MA, Marr MJ, Maple TL. Habituation and desensitization as methods for reducing fearful behavior in singly housed rhesus macaques. Am J Primatol 2009; 71(1): 30-9. doi: 10.1002/ajp.20622
De Chaumont F, Coura RD-S, Serreau P, Cressant A, Chabout J, Granon S, et al. Computerized video analysis of social interactions in mice. Nat Methods 2012; 9(4): 410-7. doi: 10.1038/nmeth.1924
de Chaumont F, Ey E, Torquet N, et al. Real-time analysis of the behaviour of groups of mice via a depth-sensing camera and machine learning. Nat Biomed Eng 2019; 3(11): 930-42. doi: 10.1038/s41551-019-0396-1
Deacon RM. Assessing nest building in mice. Nat Protoc 2006; 1(3): 1117-9.
Droste SK, de Groote L, Atkinson HC, Lightman SL, Reul JM, Linthorst AC. Corticosterone levels in the brain show a distinct ultradian rhythm but a delayed response to forced swim stress. Endocrinology 2008; 149(7): 3244-53. doi: 10.1210/en.2008-0103
Fairhurst GD, Frey MD, Reichert JF, Szelest I, Kelly DM, Bortolotti GR. Does environmental enrichment reduce stress? An integrated measure of corticosterone from feathers provides a novel perspective. PLoS One 2011; 6(3): e17663. doi: 10.1371/journal.pone.0017663
Faraji J, Ambeskovic M, Sauter N, Toly J, Whitten K, Lopes NA, et al. Sex-specific stress and biobehavioral responses to human experimenters in rats. Front Neurosci 2022; 16: 965500. doi: 10.3389/fnins.2022.965500
Franco NH, Correia-Neves M, Olsson IAS. How “Humane” Is Your Endpoint?—Refining the science-driven approach for termination of animal studies of chronic infection. PLoS Pathog 2012; 8(1): e1002399. doi: 10.1371/journal.ppat.1002399
Fuochi S, Rigamonti M, O'Connor EC, De Girolamo P, D'Angelo L. Big data and its impact on the 3Rs: a home cage monitoring oriented review. Front Big Data 2024; 7: 1390467. doi: 10.3389/fdata.2024.1390467
Füzesi T, Daviu N, Wamsteeker Cusulin JI, Bonin RP, Bains JS. Hypothalamic CRH neurons orchestrate complex behaviours after stress. Nat Commun 2016; 7(1): 11937. doi: 10.1038/ncomms11937
gaburro s, winter y, loos m, kim jj, stiedl o. editorial: home cage-based phenotyping in rodents: innovation, standardization, reproducibility and translational improvement. Front Neurosci 2022; 16: 894193. doi: 10.3389/fnins.2022.894193
Golini E, Rigamonti M, Iannello F, et al. A non-invasive digital biomarker for the detection of rest disturbances in the SOD1G93A mouse model of ALS. Front Neurosci 2020; 14: 896. doi: 10.3389/fnins.2020.00896
Goulding EH, Schenk AK, Juneja P, MacKay AW, Wade JM, Tecott LH. A robust automated system elucidates mouse home cage behavioral structure. Proc Natl Acad Sci USA 2008; 105(52): 20575-82. doi: 10.1073/pnas.0809053106
Gouveia K, Hurst JL. Reducing mouse anxiety during handling: effect of experience with handling tunnels. PLoS One 2013; 8(6): e66401. doi: 10.1371/journal.pone.0066401
Grieco F, Bernstein BJ, Biemans B, et al. Measuring behavior in the home cage: study design, applications, challenges, and perspectives. Front Behav Neurosci 2021; 15: 735387. doi: 10.3389/fnbeh.2021.735387
Hawkins P. Progress in assessing animal welfare in relation to new legislation: opportunities for behavioural researchers. J Neurosci Methods 2014; 234: 135-8. doi: 10.1016/j.jneumeth.2014.02.008
Hen I, Sakov A, Kafkafi N, Golani I, Benjamini Y. The dynamics of spatial behavior: how can robust smoothing techniques help? J Neurosci Methods 2004; 133(1/2): 161-72. doi: 10.1016/j.jneumeth.2003.10.013
Ho H, Kejzar N, Sasaguri H, et al. A fully automated home cage for long-term continuous phenotyping of mouse cognition and behavior. Cell Rep Methods 2023; 3(7): 100532. doi: 10.1016/j.crmeth.2023.100532
Hölter SM, Wells S, Voikar V, 20135 CA. Improving biomedical research by automated behaviour monitoring in the animal home cage–action needed for networking. Lab Anim 2023; 57(1): 79–83. doi: 10.1177/00236772221117451
Home Cage Monitoring Technologies: COST TEATIME; 2025. www.cost-teatime.org/about/technologies/
Hsieh CM, Hsu CH, Chen JK, Liao LD. AI-powered home cage system for real-time tracking and analysis of rodent behavior. iScience 2024; 27(11): 111223. doi: 10.1016/j.isci.2024.111223
Ivanenko A, Watkins P, van Gerven MAJ, Hammerschmidt K, Englitz B. Classifying sex and strain from mouse ultrasonic vocalizations using deep learning. PLoS Comput Biol. 2020; 16(6): e1007918. doi: 10.1371/journal.pcbi.1007918
Jirkof P. Burrowing and nest building behavior as indicators of well-being in mice. J Neurosci Methods 2014; 234: 139-46. doi: 10.1016/j.jneumeth.2014.02.001
Kahnau P, Mieske P, Wilzopolski J, et al. A systematic review of the development and application of home cage monitoring in laboratory mice and rats. BMC Biol 2023; 21(1): 256. doi: 10.1186/s12915-023-01751-7
Kousholt BS, Præstegaard KF, Stone JC, et al. Reporting quality in preclinical animal experimental research in 2009 and 2018: a nationwide systematic investigation. PLoS One 2022; 17(11): e0275962. doi: 10.1371/journal.pone.0275962
Krackow S, Vannoni E, Codita A, et al. Consistent behavioral phenotype differences between inbred mouse strains in the IntelliCage. Genes Brain Behav 2010; 9(7): 722-31. doi: 10.1111/j.1601-183X.2010.00606.x
Lazic SE. The problem of pseudoreplication in neuroscientific studies: is it affecting your analysis? BMC Neurosci 2010; 11(1): 5. doi: 10.1186/1471-2202-11-5
Lin Y, Yang F, Shang B, Speich JE, Wan Y-JY, Hashida H, et al. Reporting quality of animal research in journals that published the ARRIVE 1.0 or ARRIVE 2.0 guidelines: a cross-sectional analysis of 943 studies. Cardiovascular Diagnosis and Therapy. 2024;14(6):1070-82.
Loonen ICM, Voskuyl RA, Schenke M, van Heiningen SH, van den Maagdenberg AMJM, Tolner EA. Spontaneous and optogenetically induced cortical spreading depolarization in familial hemiplegic migraine type 1 mutant mice. Neurobiol Dis 2024; 192: 106405. doi: 10.1016/j.nbd.2024.106405
Luxem K, Mocellin P, Fuhrmann F, et al. Identifying behavioral structure from deep variational embeddings of animal motion. Commun Biol 2022; 5(1): 1267. doi: 10.1038/s42003-022-04080-7
Mah KM, Torres-Espín A, Hallworth BW, et al. Automation of training and testing motor and related tasks in pre-clinical behavioural and rehabilitative neuroscience. Exp Neurol 2021; 340: 113647. doi: 10.1016/j.expneurol.2021.113647
Mathis MW, Mathis A. Deep learning tools for the measurement of animal behavior in neuroscience. Curr Opin Neurobiol 2020; 60: 1-11. doi: 10.1016/j.conb.2019.10.008
Mellor DJ, Beausoleil NJ, Littlewood KE, et al. The 2020 five domains model: Including human–animal interactions in assessments of animal welfare. Animals (Basel) 2020; 10(10): 1870. doi: 10.3390/ani10101870
Mingrone A, Kaffman A. The promise of automated home-cage monitoring in improving translational utility of psychiatric research in rodents. Front Neurosci 2020; 14: 618593. doi: 10.3389/fnins.2020.618593
Miranda C, Oliveira L, Carmo AM, Olsson IAS, Franco NH. Contactless body temperature assessment for signalling humane endpoints in a mouse model of sepsis. Anim Welf 2025; 34: e13. doi: 10.1017/awf.2025.10
Moore JL, Kennedy J, Hassan A-A. Automated home cage monitoring of an aging colony of mice—Implications for welfare monitoring and experimentation. Front Neurosci 2024; 18: 1489308. doi: 10.3389/fnins.2024.1489308
Mösch L, Kunczik J, Breuer L, et al. Towards substitution of invasive telemetry: an integrated home cage concept for unobtrusive monitoring of objective physiological parameters in rodents. PloS One 2023; 18(9): e0286230. doi: 10.1371/journal.pone.0286230
Murray J, Bauer C, Vilminot N, Turner PV. Strengthening workplace well-being in research animal facilities. Front Vet Sci 2020; 7: 573106. doi: 10.3389/fvets.2020.573106
Namati E, Thiesse J, Sieren JC, Ross A, Hoffman EA, McLennan G. Longitudinal assessment of lung cancer progression in the mouse using in vivo micro‐CT imaging. Medical Phys 2010; 37(9): 4793-805. doi: 10.1118/1.3476454
Percie du Sert N, Hurst V, Ahluwalia A, et al. The ARRIVE guidelines 2.0: Updated guidelines for reporting animal research. PLoS Biol 2020; 18(7): e3000410. doi: 10.1371/journal.pbio.3000410
Pereira TD, Tabris N, Matsliah A, et al. Publisher Correction: SLEAP: a deep learning system for multi-animal pose tracking. Nat Methods 2022; 19(4): 486-95. doi: 10.1038/s41592-022-01495-2
Pernold K, Iannello F, Low BE, et al. Towards large scale automated cage monitoring–Diurnal rhythm and impact of interventions on in-cage activity of C57BL/6J mice recorded 24/7 with a non-disrupting capacitive-based technique. PLoS One 2019; 14(2): e0211063. doi: 10.1371/journal.pone.0211063
Powell SB, Newman HA, McDonald TA, Bugenhagen P, Lewis MH. Development of spontaneous stereotyped behavior in deer mice: effects of early and late exposure to a more complex environment. Dev Psychobiol 2000; 37(2): 100-8.
Rabasa C, Askevik K, Schéle E, Hu M, Vogel H, Dickson SL. Divergent metabolic effects of acute versus chronic repeated forced swim stress in the rat. Obesity 2019; 27(3): 427-33. doi: 10.1002/oby.22390
Rinwa P, Eriksson M, Cotgreave I, Bäckberg M. 3R-Refinement principles: elevating rodent well-being and research quality. Lab Anim Res 2024; 40(1): 11. doi: 10.1186/s42826-024-00198-3
Robertson TL, Ellis M, Bratcher-Petersen N, et al. An integrated and scalable rodent cage system enabling continuous computer vision-based behavioral analysis and AI-enhanced digital biomarker development. bioRxiv 2025: 2024.12.18.629281. doi:10.1101/2024.12.18.629281
Russell A, Copio JN, Shi Y, Kang S, Franklin CL, Ericsson AC. Reduced housing density improves statistical power of murine gut microbiota studies. Cell Rep 2022; 39(6): 110783. doi: 10.1016/j.celrep.2022.110783
Russell WMS, Burch RL. The principles of humane experimental technique. London: Methuen,1959.
Sandgren R, Grims C, Waters J, Hurst JL. Using cage ladders as a handling device reduces aversion and anxiety in laboratory mice, similar to tunnel handling. Scand J Lab Anim Sci 2021; 47: 31-41. doi: 10.23675/sjlas.v47i0.1083
Singer P, Tse YF. AI ethics: the case for including animals. AI and Ethics. 2023;3(2):539-51. doi: 10.1007/s43681-022-00187-z
Singh S, Bermudez-Contreras E, Nazari M, Sutherland RJ, Mohajerani MH. Low-cost solution for rodent home-cage behaviour monitoring. PLoS One 2019; 14(8): e0220751. doi: 10.1371/journal.pone.0220751
Sneddon LU, Halsey LG, Bury NR. Considering aspects of the 3Rs principles within experimental animal biology. J Exp Biol 2017; 220(17): 3007–16. doi: 10.1242/jeb.147058
Sun R, Gaerz M-C, Oeing C, Mai K, Brachs S. Accurate locomotor activity profiles of group-housed mice derived from home cage monitoring data. Front Neurosci 2024; 18: 1456307. doi: 10.3389/fnins.2024.1456307
Swan J, Boyer S, Westlund K, Bengtsson C, Nordahl G, Törnqvist E. Decreased levels of discomfort in repeatedly handled mice during experimental procedures, assessed by facial expressions. Front Behav Neurosci 2023; 17: 1109886. doi: 10.3389/fnbeh.2023.1109886
Terry S, Gommet C, Kerangueven A-C, Leguet M, Thévenin V, Berthelot M, et al. Activity in group-housed home cages of mice as a novel preclinical biomarker in oncology studies. Cancers (Basel) 2023; 15(19: 4798. doi: 10.3390/cancers15194798
Thanos PK, Cavigelli SA, Michaelides M, et al. A non-invasive method for detecting the metabolic stress response in rodents: characterization and disruption of the circadian corticosterone rhythm. Physiol Res 2008; 58(2): 219–28. doi: 10.33549/physiolres.931434
Tschöp MH, Speakman JR, Arch JR, et al. A guide to analysis of mouse energy metabolism. Nat Methods 2011; 9(1): 57-63. doi: 10.1038/nmeth.1806
Tuyttens F, de Graaf S, Heerkens JL, et al. Observer bias in animal behaviour research: can we believe what we score, if we score what we believe? Anim Behav 2014; 90: 273–80.
Ueno H, Takahashi Y, Murakami S, et al. Effect of simultaneous testing of two mice in the tail suspension test and forced swim test. Sci Rep 2022; 12(1): 9224. doi: 10.1038/s41598-022-12986-9
Voelkl B, Altman NS, Forsman A, et al. Author Correction: reproducibility of animal research in light of biological variation. Nat Rev Neurosci 2020; 21(7): 394. doi: 10.1038/s41583-020-0326-y
Voelkl B, Vogt L, Sena ES, Würbel H. Reproducibility of preclinical animal research improves with heterogeneity of study samples. PLoS Biol 2018; 16(2): e2003693. doi: 10.1371/journal.pbio.2003693
Voikar V, Gaburro S. Three pillars of automated home-cage phenotyping of mice: novel findings, refinement, and reproducibility based on literature and experience. Front Behav Neurosci 2020; 14: 575434. doi: 10.3389/fnbeh.2020.575434
Wooden JI, Spinetta MJ, Nguyen T, O’Leary CI, Leasure JL. A sensitive homecage-based novel object recognition task for rodents. Front Behav Neurosci 2021; 15: 680042. doi: 10.3389/fnbeh.2021.680042
Zorman Rojs O, Dovč A, Hristov H, et al. Welfare assessment of commercial layers in Slovenia. Slov Vet Res 2020; 57(3): 133–43. doi: 10.26873/SVR-971-2020
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