Reverse translation of failed treatments can help improving the validity of preclinical animal models.

A major challenge in translational research is to reduce the currently high proportion of new candidate treatment agents for neuroinflammatory disease, which fail to reproduce promising effects observed in animal models when tested in patients. This disturbing situation has raised criticism against the currently used animal models in preclinical research and calls for improvement of these models. This seems a difficult task as the cause of failure is often not known. Here we propose a potentially useful strategy for investigating why a promising strategy fails as a guidance for improving the validity of the animal model(s).