ETH Zurich launches 3R Hub to establish methods that improve animal experiments
The new Hub is a point of contact for researchers with questions about the 3Rs – the three foundational principles of animal experimentation to which the ETH is committed: Replace, Reduce and Refine. The 3R Hub raises awareness among researchers and the public about compassionate animal research.
Launched in March, the 3R Hub will pool all of ETH Zurich’s 3R activities and knowledge relating to 3R methods. The aim of concentrating all these activities in one place is to highlight and establish effective, 3R technologies within ETH Zurich. This also includes training for researchers. All 3R Hub activities and methods will be focused on improving animal welfare.
Oliver Sturman heads the 3R Hub. Originally from the UK, Sturman researches at the Institute for Neuroscience. Over the past few years, his postdoc work has included coordinating a major collaboration with Roche, where he implemented advanced, animal-friendly behavioural analysis techniques.
Tapping synergies and consolidated knowledge
The 3R Hub is attached to the Molecular and Behavioural Neuroscience research group led by Professor Johannes Bohacek. There is a particularly good reason for this: part of the Institute for Neuroscience, this research group has a wealth of 3R experience. Its researchers are currently working on three projects funded by the external page Swiss 3R Competence Centre (3RCC). One of these projects concerns a external page modernised, AI-assisted method for compiling behavioural profiles of rodents.
This project, which is about developing a more efficient method of behavioural analysis through video monitoring (see box), is using existing synergies between behavioural neuroscience and artificial intelligence in the interests of animal welfare. “We need this kind of behavioural analysis for our own research,” Bohacek says. “Why not make it available to others as well?”
This is exactly the purpose of the 3R Hub: to develop new methods that minimise the burden on laboratory animals as well as reduce the number of animals required for each experiment, and then make these methods available to other research laboratories as well.
The 3R principles are by no means a new arrival at ETH Zurich – the university has taken a responsible approach to animal experiments for many years and conducts its own research in this area. “Now, with the new Hub, we’re intensifying the exchange of ideas as well as pooling and imparting 3R knowledge and expertise. And we’re identifying tailored solutions to make research as comfortable as possible for laboratory animals in many fields,” Bohacek explains. Up to now, each individual research group has been responsible for making sure it complied with the 3R principles and has managed this topic on its own. “But now, with the 3R Hub, we have one single entity that develops 3R methods, makes findings available to others and actively establishes these methods in other labs without having to clear administrative hurdles.”
A win for researchers and animals alike
What the new Hub gives researchers is a central point of contact for accessing information about 3R standards and methods, as well as help when adapting new 3R methods to meet their own research requirements. The Hub also provides a platform for exchanging expertise and best practices. “Researchers who are already applying a 3R technique that could prove useful to other researchers should definitely get in touch,” says Sturman, who heads the 3R Hub.
At the same time, the 3R Hub serves the interests of animal welfare by striving to improve conditions for laboratory animals overall. “Applying our outstanding standard of research and our own high expectations, we wish to establish techniques that minimise the burden on animals,” Bohacek says. “Moreover, we want to reduce the number of laboratory animals required by maximising the amount of information gained from each experiment.”
Naturally, animal models are to be replaced entirely wherever and whenever possible. In many areas of scientific enquiry, however, animal experiments remain indispensable (read more about this topic in the article “Support for animal experiment research and reinforcement of the 3R principles”).
Preserving valuable knowledge
In its pilot phase, the 3R Hub is focusing on behavioural research – and on the simplified video-based behavioural analysis offered by Bohacek’s research group (see box). A large laboratory is being set up for the 3R Hub at the University of Zurich’s Irchel campus. This will serve as a workshop for producing and testing equipment for automated behavioural analysis before it is installed in other labs. It also provides a venue for testing and reproducing new techniques adopted from other research areas.
Beyond the pilot phase, the Hub’s long-term goal is to consolidate the various 3R approaches applied at ETH Zurich and make the techniques and expertise available to others, Bohacek says. “Perhaps someday a group will announce that it can, say, model the blood-brain barrier on a chip. Then we’d no longer need to use mice to screen whether or not a drug crosses this barrier.” Through this Replacement strategy for animal experiments, the Hub could then have one person train in this area with a view to establishing this method and sharing the know-how with other labs.
The 3R Hub is a vehicle for sharing valuable knowledge and preserving it over the long term to benefit the various research groups at ETH Zurich. “Since many of our employees are on fixed-term contracts, our labs have a high turnover of staff. When researchers leave, at least a portion of their knowledge leaves with them,” Bohacek says. In light of this situation, he adds, it makes sense for ETH Zurich to fund this kind of hub and train experts with a view to ensuring the technology is available long-term and to as many people as possible.
Expanding the platform
Soon, the 3R Hub web page will be expanded to include more information on 3R and ongoing projects. “Over the next few months, we’ll be putting together a picture of the various 3R-related topics in play at ETH Zurich,” Bohacek says.
The 3R Hub is starting life as Sturman’s one-man show, the progress of which will be reviewed after a two-year pilot phase. Bohacek says that the mid-term goal is growth. “If our model proves successful, we’ll one day be able to employ one or two technicians capable of understanding, testing and implementing the individual research projects, and transplanting them into the labs.”
Successive growth is in keeping with the vision for the 3R Hub held by Christian Wolfrum, Vice President for Research: “We want to further promote 3R methods at ETH Zurich. And the most effective way of doing this is when our researchers themselves develop and disseminate new methods. The aim of the 3R Hub is to increase the number of researchers using this valuable approach.”
Fewer experiments, more animal-friendly methods
Initially, the 3R Hub will focus on the first two R’s – Reduce and Refine – which involves maximising the amount of data generated from each experiment while minimising the impact on the animals. The integration of R number three – Replace – remains a goal, albeit one that will be hard to achieve within the next few years. “There have already been numerous efforts to replace animal experiments wherever possible, but in basic research it’s often simply not an option,” Wolfrum says. “That’s why we’re committed to improving experiment facilities and methods and at least reducing the number of animals required.”
Maximising data from each experiment
As the researchers in the Molecular and Behavioural Neuroscience research group examine psychological conditions such as stress-induced anxiety disorders, they are dependent on observations of laboratory animals: “Studying behaviour is a complex business. An anxiety disorder, for example, can’t be diagnosed at the molecular level,” Johannes Bohacek says. “A person can fill out a questionnaire, but assessing animals requires testing their behaviour.” Today, such behavioural analyses are still carried out in a distinctly conventional manner: “We take a mouse, put it in a box and observe it with regard to one or two aspects, for instance how fast it moves and whether it remains in a particular place or explores its surroundings.” Bohacek adds that this is a wasteful approach to animal experiments. Using modern technology, it’s possible to gather much more data on the laboratory animal’s behaviour from each individual experiment.
The research group’s solution is entirely in keeping with the 3R principles of Reduce and Refine: existing tools from the fields of computer vision and machine learning – both forms of artificial intelligence – are used to perform detailed behavioural analysis. Here, the mouse in the box is filmed from above by a camera. By analysing the overall movements of the animal as well as of individual body parts such as its head or tail, the software can detect, for example, that the mouse is sitting in the corner cleaning its face, which can indicate that it is feeling anxious. Or the system might recognise that the mouse is standing against the wall moving its head either rapidly or slowly. In the past, such behaviours – if discernible at all – had to be noted down laboriously by hand, which is inefficient, imprecise and susceptible to error. “There are plenty of tiny nuances that machine learning can pluck from this data,” Bohacek says. “We assume – and this is partly still a hypothesis that we’re testing – that it’s possible to say much more about an animal’s condition using these techniques than it is with the minimalistic analyses that are currently still commonplace in most research labs.”
The Molecular and Behavioural Neuroscience group at the University of Zurich’s Irchel campus is one of only a few in the world that deals with this kind of automated behavioural analysis. “Time and again, we hear from other labs that would like to automate their behavioural analyses rather than sit in front of the mouse box keeping a tally of when the animal exhibits signs of this or that behaviour.”
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