CNS Trials with Sensors to Capture Patient Data

More than one in three people worldwide are affected by neurological conditions, driving a high demand for new treatments. Yet many central nervous system (CNS) trials still rely on endpoints that offer only a limited view into patients’ lived experiences — potentially delaying innovation and regulatory progress.

Advances in sensors and wearable devices are now enabling continuous, objective measurement of subtle cognitive, physiological and physical changes that often go undetected by traditional endpoints.

Including a use case in Alzheimer’s disease, this webinar will explore how validated digital endpoints from sensor data can enhance CNS trial efficiency, improve patient monitoring and accelerate regulatory confidence in novel measures.

Register for this webinar to learn how sensor-based data can address the main challenges that hinder traditional endpoint measurement in CNS clinical trials.

Speakers

Melissa Ceruolo, VP Engineering & Biomarker Analytics, Medidata Solutions

Melissa Ceruolo is an experienced engineering executive specializing in software engineering and biomarker analytics. Currently serving as VP of Engineering & Biomarker Analytics at Medidata Solutions since October 2020, Melissa previously held the position of VP of Software Engineering and Data Products at MC10 Inc., where key achievements included the commercialization of innovative medical devices and leadership of interdisciplinary teams in software development. Earlier experience includes roles in project management and technical innovation within various engineering firms, contributing to product development and regulatory compliance in the medical device and biopharmaceutical sectors. Melissa holds an MS in Engineering and Management from the Massachusetts Institute of Technology and a BS in Mechanical Engineering from Carnegie Mellon University.

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Brett Meyer, Senior Data Scientist, Medidata Solutions

Brett Meyer is a Senior Data Scientist at Medidata Solutions, where he focuses on the analysis and creation of digital endpoints across various conditions. Holding a PhD in Data Science and Complex Systems from the University of Vermont, Brett’s research since 2019 has significantly emphasized Central Nervous System (CNS) diseases. His work extensively explores the application of wearable sensors alongside advanced machine learning and signal processing techniques to better understand and address health challenges, particularly in balance and mobility assessment, while aiming to reduce patient burden.

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