Better science with less animal experimentation

*Which new technologies could make scientific tests completely animal-free in the future?
It is about how to be innovative and able to develop a sustainable and more humane science for the near future. *

This course will consist of five modules, all of which focus on a different aspect of research and innovation in animal-free methods. The course will include regulatory and communication aspects. During this course, you will focus on innovations in animal-free methods including advanced in vitro (cell culture) and in silico (computational) approaches. The course will highlight the unique advantages of human-derived cells, such as induced pluripotent stem cells, organoids and multi-organ-on-chip devices. You will discover and discuss core topics related to the transition to a more humane science with the help of ethics, statistics and philosophy experts. You will dive in critical data interpretation in order to enhance your understanding of science. A group of experts will teach you the methodology of systematic reviews of scientific studies.

The veterinary students are advised to register for the 2 extra weeks (in total 5 weeks).
During the 2 extra weeks the student will have the possibility to dive into the technology related to advanced in vitro models. During the last two weeks of the course, the participants in groups will conduct an independent research within the most promising current lines of research at different departments. At the end of the final 2 weeks the student will present their research assignment.

https://youtu.be/ZMbb2Q3yShs

Students from TU/e and WUR can register for this challenge via EduXchange.nl

The main goal of this course is to develop critical thinking supporting the choice, creation, development, validation, and use of alternatives to animals in research

Je wordt ingeschreven voor deze cursus door de administratie van de opleiding van de cursus.

A BSc in life sciences, basic knowledge in the structure of research projects. Some experience in data interpretation is expected.