DIVA to Present at the 75th Annual AALAS Meeting on Enhancing Animal Studies with Digital Biomarkers 

Next week, the Digital In Vivo Alliance (DIVA) is thrilled to take part in the 75th Annual Meeting of the American Association for Laboratory Animal Science (AALAS), a prominent gathering of professionals in laboratory animal science. This event attracts thousands of researchers, veterinarians, and industry leaders dedicated to advancing animal care, research, and management, making it a perfect platform for DIVA to share its work in digital biomarkers. 

DIVA was established by a team of scientists focused on the transformative potential of digital sensors, artificial intelligence (AI), and machine learning (ML) in animal research. Over the past few years, DIVA has worked toward a unified strategic direction, nominated key digital measures that could benefit drug developers, and designed studies to create and validate ML-based algorithms. This collaboration has resulted in a robust validation framework and tangible outcomes we are excited to discuss with the broader research community. 

Here’s a sneak peek into what you can expect from the session, being led by DIVA Chair, Dr. Brian Berridge: 

Session Overview: Leveraging ML-Based Digital Biomarkers in Animal Research 
November 6, 2024 
8 – 10 am Room 207 

Drug development ideally moves seamlessly from basic research to preclinical models and eventually to human studies. Today, the use of digital wearables in clinical settings is reshaping our understanding of human health and disease, offering precise insights and real-time monitoring. DIVA’s work in preclinical digital biomarkers aims to bring similar advancements to animal studies by using home cage-based monitoring and analysis. By applying these digital measures, we hope to improve translational relevance, reproducibility, generalizability, and promote the 3Rs (Replacement, Reduction, Refinement) impact in preclinical research. 

DIVA’s multi-disciplinary collaboration advances digital biomarkers through a comprehensive approach, from development and validation to regulatory acceptance. Our studies include models of drug-induced neuroactivity, Amyotrophic Lateral Sclerosis, Friedreich’s Ataxia, and Dravet Syndrome, allowing us to refine digital biomarkers of activity, locomotion, and seizure. These efforts contribute to training and validating ML algorithms that enhance study reproducibility across sites and settings. This session will share our findings through proof-of-concept vignettes that highlight the advantages of digital biomarkers and DIVA’s unique approach. 

Our seminar will be valuable for researchers, veterinarians, data scientists, vivarium managers, and anyone interested in how digital biomarkers can enhance the reproducibility, generalizability, and ethical standards of animal studies. Below is an outline of the seminar topics and speakers: 

DIVA Seminar Topics and Speakers: 

  • Advancing Animal Research Through Innovation: Building Confidence in Computer-Vision-Derived Digital Biomarkers 
    Presenter: Vivek Kumar, Associate Professor, Center for Addiction Biology, The Jackson Laboratory 
  • Enhancing In Vivo Toxicology Studies with ML-Informed Digital Biomarkers for Improved Sensitivity and Translation 
    Presenter: Brian Berridge, DIVA Chair 
  • Addressing Challenges in Preclinical Neuroscience Research through Home Cage Digital Measures 
    Presenter: Jenny Leedy, In Vivo Scientist, BioMarin 
  • Understanding Cross-Site Reproducibility Challenges in Home Cage Digital Measures 
    Presenter: Michael Saul, Computational Scientist, The Jackson Laboratory 

Sessions sponsored in part by The Jackson Laboratory 

This seminar underscores DIVA’s commitment to harnessing the power of digital measures for robust, reliable, and ethical animal research. We look forward to an engaging session and hope to inspire more researchers and stakeholders to explore the potential of digital measures in their work. We hope we’ll see you there! 

Natalie Bratcher-Petersen
Manager of Digital In Vivo Alliance

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