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Summary

Researchers using animal models frequently encounter variability in their study results due to limitations in data collection methodologies. These methods often require human interpretation of behavioral and physiological cues through direct observation or handling of mice, leading to lack of replicability that can be further exacerbated when different researchers conduct the same study.

In this webinar, Dr. Michael Saul, Computational Scientist at The Jackson Laboratory, will discuss recent studies using the Envision™ platform that show how AI-powered, digital home cage-monitoring of mice with minimal disturbance creates opportunities to reduce study variability. Dr. Saul will guide attendees through datasets demonstrating how Envision helps research cut through the "noise" to uncover key study outcomes that influence decision-making.

What you will learn:

Essential aspects of preclinical study design that drive effective decision-making
How digital home cage monitoring transforms preclinical mouse studies
Results from a multisite mouse behavioral phenotyping study highlighting the Envision platform's robustness

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JAX™ Webinars are complimentary.
No fees will be charged for registering.

Webinars are 45-50 minutes long, followed by a Q&A session.

When registering, please use an institutional (e.g. work, university, etc.) email address or contact our event staff to request an exception. Thank you.

Addressing the Preclinical Reproducibility Crisis Using Digital Home Cage Monitoring

When registering, please use an institutional (e.g. work, university, etc.) email address or contact our event staff to request an exception. Thank you.