FEB 13, 2019 1:30 PM PST

Precision Medicine for Mice: Digital Biomarkers Transforming Drug Discovery

C.E. Credits: RACE
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

    Preclinical drug discovery is at the edge of a major transformation that promises to improve translation to the clinic through enhanced acquisition and advanced analysis of data. While an important part of the drug development process, currently preclinical studies do not always predict drug failure or success in the clinic. Limited predictive power is attributed to many factors including limited measurable parameters on a single animal, infrequent collection, and small sample sizes that are often captured under conditions that have the potential to alter the animal’s physiologic state and confound data interpretation. Digital biomarkers, captured continuously without handling, provide objective, sensitive, and clinically meaningful methods of monitoring disease and response to therapeutic interventions. This webinar reviews the the current state of digital biomarkers in preclinical studies and discusses the challenges and opportunities for more widespread adoption to improve translation of preclinical studies to the clinic.

    Learning Objectives: 

    1. Define digital biomarkers and current state in drug development
    2. Examine how high frequency capture of digital biomarkers provides objective, sensitive, and meaningful readouts of disease state and compound efficacy that may be more translatable to the clinic.
    3. Discuss challenges and opportunities for the future capture and analysis of digital biomarkers in preclinical studies


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