Abstract

Animal models are essential for assessing the preclinical efficacy of candidate drugs, but animal data often fails to replicate in human clinical trials. This translational gulf is due in part to strategies that do not capture sensitive, disease-relevant measures and a reliance on human expert assessment for complex endpoints. To address these we combine a model that recapitulates the key common features of human neurodegenerative disease with unbiased and machine learning-assisted behavioural phenotyping. This approach is able to 1) measure subtle, stereotyped, and progressive changes in motor behaviour over the disease time and 2) correlates with the earliest detectable histopathological changes in the mouse brain. We aim remove human expert opinion from therapeutic assessment and provide a basis for truly standardised and sharable platform for pre-clinical validation