JUN 26, 2018 9:00 AM PDT

Automated In Vivo Efficacy Assessment in Preclinical Lung Disease Models

Sponsored by: Vium
C.E. Credits: P.A.C.E. CE Florida CE
Speaker
  • Chief Scientific Officer, Vium
    Biography
      Laura Schaevitz has more than 20 years of experience with In vivo animal studies. As Chief Scientific Officer at Vium, she oversees the development of animal models and draws upon her experiences as a molecular and behavioral neuroscientist to direct the application of Vium's digital metrics to the animal models. In past experiences, Laura utilized a broad spectrum of mouse models including transgenic and nutrition-induced models of neurodevelopmental disorders such as autism, schizophrenia, Rett syndrome, and blindsight. Laura received her PhD in Neuroscience at Stanford University in 2006.

    Abstract

    DATE: June 26, 2018
    TIME: 09:00AM PDT, 12:00PM EDT

    Treatments for respiratory diseases represent an enormous, unmet medical need with limited therapies currently approved for use. Despite many compounds demonstrating beneficial effects in animals models, very few translate into successful therapies. To improve translational efficacy of respiratory animal models, researchers are calling for the development of new druggable targets, better biomarkers and the use of more clinically relevant endpoints in preclinical animal studies. This presentation will describe a novel technology platform that allows for non-invasive real-time monitoring of lung function in preclinical studies of respiratory disease and will present several use cases demonstrating how automated longitudinal monitoring provides insight into disease biology in animal models of Idiopathic Pulmonary Fibrosis (IPF) and Pneumonia.
     
    In this webinar you will:
    • Review method for automated collection of breathing data and comparison of data collection to traditional techniques
    • Demonstrate how automated longitudinal monitoring of breathing provides insight into disease biology in preclinical lung disease models
     

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