Metris and the 3 R's
Because animal experiments are still needed for drug development it is crucial to reduce the number of experiments and refine animal experimenting. Metris as found solutions to support this witout compromizing the results from the experiments.
LABORAS, SONOTRACK and SmartChamber offer non-evasive, homecage based, real "night condition" experiments that not only improve quality of research but also enable you to combine presently known outdated experiments into a single experiment! This has resulted in avoiding needless use of animals.
All Metris systems require a minimal amount of handling and do not require humans to be in the experimental room, significantly reducing stress in the animals.
The British Coalition for Medical Progress already indicated in 2003 that users of LABORAS were able to refine and reduce their animal experiments. More information can be found in their publication (page 7)
"Animals in Biomedical Research Today: An introduction to the 3R's" (October 2003).
Several other organizations in the Animal Welfare field acknowledge the reduction of animals by using Laboras in animal experiments, such as:
- FRAME (Fund for the Replacement of Animals in Medical Experiments)
- NCR3 (National Centre for Replacement, Refinement and Reduction of Animals in Research
Reduction of experiments is not only accomplished because we offer the highest number of relevant parameters per animal, but also because raw data remains accessible even after many years (with a typical usage, raw LABORAS data of 1 year can be stored on an USB memory stick!). LABORAS experiments are unique as they can be re-done using existing raw data on different behavior modules. No need for experiment approval filling, test-session preparation, use of new animals.
Refinement has been experienced because the fast analysis tools enabled the researchers to alter the course of the experiment based on preliminary results of the first test-sessions. Early decision making by management helps to reduce useless experiments that do not provide the expected insights.
To find out more about our RRR objectives and possibilities, please contact us:
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