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SUMMARY:Unbiased preclinical phenotyping for neuroprotective compounds - E
 dward Harding\, Clinical Biochemistry
DTSTART:20241202T123000Z
DTEND:20241202T130000Z
UID:TALK224875@talks.cam.ac.uk
CONTACT:Sam Nallaperuma-Herzberg
DESCRIPTION:Animal models are essential for assessing the preclinical effi
 cacy of candidate drugs\, but animal data often fails to replicate in huma
 n clinical trials. This translational gulf is due in part to strategies th
 at 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 neurodegenera
 tive disease with unbiased and machine learning-assisted behavioural pheno
 typing. This approach is able to 1) measure subtle\, stereotyped\, and pro
 gressive changes in motor behaviour over the disease time and 2) correlate
 s with the earliest detectable histopathological changes in the mouse brai
 n. We aim remove human expert opinion from therapeutic assessment and prov
 ide a basis for truly standardised and sharable platform for pre-clinical 
 validation
LOCATION:FW11\, Willam Gates building (Department of Computer Science and 
 Technology)
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