Methods

What are the three Rs of animal research?

Answer: The “Three Rs” of animal research refer to replacement, reduction, and refinement.

three Rs of research

Scientists who study the brain often make use of animal models. However, using animals in scientific research requires that the animals are used as ethically as possible. The “Three Rs” were first described by William Russell and Rex Burch in 1959 in their publication The Principles of Humane Experimental Technique. Collectively, the three Rs are in place to both improve animal welfare as well as scientific rigor.

Replacement: Whenever possible, avoiding the use of animals is preferable to using animals. It must be justified that an experiment cannot be performed using some of the other available techniques, including computer mathematical modeling, bacteria, cell cultures, or sections of tissue. Originally, Replacement was defined as strictly vertebrates, implying that doing the experiments in invertebrates would be an improvement.

Reduction: Researchers should strive to use as few animals as possible. Most of these techniques center around getting as much information from each experimental animal. For example, planning the timeline of experiments to minimize a wasted animal due to time constraints, or to use each animal for multiple experiments are two methods to reduce animal use.

Refinement: In experiments where animal use is a necessity, the issue of refinement is raised. Refinement refers to minimizing the amount of distress that the animal experiences. For example, using non-invasive techniques (non surgical) is preferable to one that requires the animal to undergo anesthesia and the injury that surgery entails. Using the right anesthesia can minimize the pain, which is an important aspect of refinement. Also, it may be possible to train animals to comply with the experiment paradigm, such as blood draws.

The Three Rs of animal research, when performed properly, can greatly reduce our impact on the test animals. Additionally, they have the added benefit of improving the results of the data.