Project Objectives
- Develop software that computes and compares breeding strategies to identify those that minimise surplus animals.
- Provide visual tools that help researchers understand breeding complexity and outcomes.
- Implement simulation and optimisation modules to support planning and adaptation during breeding.
- Disseminate the software widely to encourage adoption across Swiss and international research communities.
3Rs Impact
- Optimised breeding strategies can directly reduce the number of surplus animals, while poor strategy choice can increase surplus animals by up to 59%.
- Adoption across Swiss institutions could spare tens of thousands of animals annually.
- International use could reduce surplus animal numbers by millions.
Background
Scientists often use genetically modified animals in their research, but this requires complex breeding schemes, which can lead to more animals being born than can be used. Some of these surplus animals do not carry the required traits, and so are usually euthanized. As genetic models become more complex, predicting the number of animals needed becomes increasingly difficult. Although the basic rules of inheritance are well understood, real breeding programmes involve many variables, and researchers often rely on intuition or simple tools that cannot handle this complexity.
This project develops software to help scientists plan rodent breeding more effectively. By modelling different breeding strategies and comparing their outcomes, the tool identifies the approach that produces the fewest surplus rodents. It also allows users to simulate different scenarios, visualise the breeding process and adjust plans when unexpected results occur.
By giving researchers clearer insight into how their breeding decisions affect animal numbers, the software supports more ethical and efficient research. It has the potential to significantly reduce unnecessary breeding in Switzerland and internationally.
