Reimagining Drug Development with the Digitalization of Toxicology Studies

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The Challenge: De-Risking Preclinical Toxicology Studies 

Preclinical toxicology studies face a significant challenge: animal models cannot self-report side effects. This limitation proves particularly problematic when evaluating treatments for which subtle behavioral changes often serve as critical indicators of a drug’s safety profile. Moreover, traditional animal assessments frequently miss less severe side effects, such as nausea, headaches, dizziness, and fatigue, factors that can significantly influence drug tolerability in human patients.

To tackle this, researchers resort to acute and episodic in-person monitoring, manually assessing in mice behaviors like grip strength, tremors, gait, and coat condition. However, these methods have downsides: they are limited in scope, episodic, and disruptive to the animals, potentially compromising data accuracy. Ripe for innovation, a new solution has been developed by The Jackson Laboratory: applying advanced machine learning algorithms to digitalize behavioral monitoring components of toxicology studies.

The Power of Digital Home-Cage Monitoring

Digital health technologies offer promising solutions. Drawing inspiration from clinical advancements that use wearable devices for continuous monitoring of patient biomarkers and early disease detection, the preclinical world is now seeing the emergence of digital solutions that are changing the toxicology landscape.

JAX Envision Computer Mock
Credit: The Jackson Laboratory

At the frontline of this digital revolution is The Jackson Laboratory’s latest innovation, Envision™. This sophisticated software platform delivers integration of behavioral tracking technology within the home-cage environment, allowing for continuous monitoring of individual animals in group-housed settings. Powered by advanced machine learning routines, Envision processes raw video data into meaningful digital measures to reduce subjectivity, ultimately ensuring more complete and reproducible preclinical data.

Digitalizing toxicology studies by tracking animal behavior and physiological functions, like activity levels and locomotion, provides precise, objective data around the clock. This improves the reliability of behavioral endpoints and can reveal subtle drug effects, identifying toxicities and safety concerns earlier. Additionally, remote monitoring through Envision reduces animal stress by minimizing handling and creating a more natural environment.

Giving Researchers Tools to Ask New Questions

The Envision platform’s unique extensibility allows research teams to design custom digital measures on top of its core framework. Alongside prebuilt, validated digital measures, researchers can leverage Envision’s advanced modeling capabilities to create proprietary measures tailored to specific phenotypes. To support these efforts, JAX offers contract development services, drawing on its deep expertise in behavioral characterization and model validation. This flexible, powerful platform provides core technology for developing new algorithms, meeting the precise needs of preclinical toxicology and other specialized research areas.

Transforming the Overall Preclinical Toxicology Workflow

With its cloud-based infrastructure,
Envision promotes efficiency and scalability across multiple functional teams. Envision facilitates collaboration and alignment across groups with virtual study design, rare event labeling, and annotation tools. This system allows multiple studies to run concurrently, securely store data, and share views of all animals in real time. Users can easily add guests to share data in real time and discuss insights and study progress.

By integrating computer vision and machine-learning algorithms into the home-cage environment, all on top of a software framework that can be continuously augmented with novel digital measures, researchers can now conduct continuous, noninvasive monitoring of animal models, providing an alternative to traditional episodic, manual, and cage-side methods. Through comprehensive, objective, and continuous data, JAX Envision paves the way for more accurate, reliable, and efficient preclinical drug safety assessments.

 

The Jackson Laboratory November 2024 issue QR Code

 

Learn more at jax.org/envision.