FEB 08, 2017 1:30 PM PST

Characterization of Niemann Pick Type C mutant mice using automated cage monitoring systems

Speaker

Abstract

DATE: February 8, 2017
TIME: 1:30pm PT, 4:30pm ET

Perlara PBC, is a public benefit company committed to discovering small molecule therapeutics for rare genetic diseases. Our approach consists of the use of simple, whole animal models such as yeast, worm, flies in drug discovery screens. Molecules that pass successfully through our screens are validated in patient cells before advancing into higher animal models of the disease.  Niemann Pick Type C (NPC) is a devastating lysosomal storage disease with high mortality rates. As part of our pipeline for advancing promising candidates for NPC disease from our screen into NPC mutant mice, Perlara partnered with Vium Inc. to validate an NPC knockout mouse model (NPCnih) for preclinical studies on their proprietary automated platform. Vium incorporates sensorized cages, automated image capture and processing algorithms to deliver high resolution data with minimal human intervention. 

The first goal of this project was to confirm that automated recording could be used to recapitulate previously published findings on NPC mutant mice. Using this approach, we validated the following previously published findings: a) NPC KO mice show significant weight loss relative to age-matched WT littermates, b) once weekly subcutaneous dosing of 4000mg/kg cyclodextrin normalized the weight loss observed in NPC KO to WT levels. Previous studies have also highlighted that NPC KO mice suffer from compromised pulmonary function. Unexpectedly, the automated data capture methods of Vium enabled us to identify two secondary endpoints of the disease, namely decrease in respiration and circadian motion. These metrics were correlated to the onset of disease pathology. We also compared NPC KO mice with WT littermates on traditional behavioral assays such as balance beam tests and accelerated rotarod assays. While baseline performance on these assays on postnatal day 35 did not differ between age-matched WT and KO, NPC KO mice showed significant decreases in performances on both behavioral assays by postnatal day 50. This is consistent with previously reported data. In conclusion, using automated data capture methods, Perlara was able to validate previously published data on NPC KO mice as well as identify two new metrics by which to benchmark disease progression. Future studies will focus on assessing the effect of Perlara’s ‘hit’ compounds on NPC KO mice. 


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FEB 08, 2017 1:30 PM PST

Characterization of Niemann Pick Type C mutant mice using automated cage monitoring systems


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Animal Models

Animal Sciences

Animal Research

Cell Culture

Molecular Biology

Immunology

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