Articles and Insights About Wearables for Clinical Trials

Research scientist Shelby Bachman, PhD, spoke at the Roche Digital Biomarkers in Clinical Trials Summit on the prospects for wearable sensors for measuring health-related quality of life in cancer survivors.

At the a2 National Symposium: Empowering Innovation in AI/Tech + Aging, Senior Research Scientist Jen Blankenship, PhD, presented our ongoing work with the Center for Human Health and Performance at the University of Massachusetts Amherst to develop digital clinical measures that capture how patients with Alzheimer’s disease function in their real-world environments. 

Movement and mobility-related information collected passively and continuously from digital health technologies (DHTs) as patients go about their daily lives can significantly advance our understanding of patient functioning. The Best 6-Minute Effort (B6ME)™ is a novel outcome measure that captures the maximum effort exerted by a patient as they go about their typical daily life, providing insight into their lived experience.

Here's an overview of what B6ME™ is and how it augments the 6MWT to provide additional granularity of patient functioning and novel movement and mobility-related outcomes.

Physical function and mobility are relevant to virtually all clinical indications and are significant determinants of an individual’s quality of life. Because of this, function and mobility are often assessed in clinical trials using subjective questionnaires or in-clinic performance tests, but these assessments may not reflect a patient’s lived experience. Wearable sensors provide an opportunity to move assessments of function into the real world to measure how patients feel and function in their everyday environments.

We really like validation: in fact, you might say we take it personally. It’s the foundation of everything we do. We are excited to report that we’re nearing the completion of a study that we believe will greatly expand the possibilities of digital outcome measures in clinical trials.

The research includes steps 1 and 2 of the V3 framework, verification and analytical validation. The outcome will be validated, machine learning algorithms to derive novel, real-world measures of physical function and mobility from wearable kinematic sensors (e.g., accelerometers, gyroscopes). Here’s an overview of our approach to the study and development efforts.