LANDSCAPE ANALYSIS OF BIOMETRIC MONITORING DEVICES (BMDS) UTILIZED IN ASSESSING COGNITION, SLEEP AND MOBILITY IN ALZHEIMER’S DISEASE AND OTHER AGE-RELATED NEUROLOGICAL DISEASES

Abstract

The general public and collective biomedical research enterprise are increasingly embracing local and remote monitoring technologies, mobile smartphone apps, and portable/wearable devices into their activities of daily living. Many view these devices as future path to provide a deeper understanding of disease processes, patients’ cognitive and functional status, and quality-of-life assessments. Biometric Monitoring Devices (BMDs) refer to the use of a biosensor(s) to continuously collect objective data on a biological recognition element (glucose, hormone levels, etc.), or integrated physiological parameters (blood pressure, mobility/motor, memory/processing, speech/sleep patterns, social engagement, etc.). BMDs utilize algorithms to transform data into a format that is interpretable as a specific measure, or, an aggregate functional outcome. Health platforms using BMDs are providing clinicians real-time evidence that allows efficient and continuous collection of data and assessments to monitor clinically meaningful parameters. The Coalition Against Major Diseases (CAMD), a nonprofit organization that aims to convene diverse stakeholders (academia, advocacy groups, industry, regulators) to create new Drug Development Tools (DDTs) that can accelerate the drug development process, conducted a landscape analysis of BMDs utilized in assessing sleep, cognition, and mobility in Alzheimer's disease (AD) and other age-related neurological diseases. CAMD convened workshops to gather and unify the research community, subject-matter experts, device developers, standard development organizations, and regulators around the identification of existing gaps and challenges, a common lexicon, assessments of existing devices in use, and use-cases for potential integration into clinical trial tools across neurological diseases. Because BMDs represent a paradigm shift in developing evidence of biomarker changes or clinical endpoints for clinical trials, they will require an innovative approach to data standardization, data integration and data analytics. This presentation aims to summarize the workshop results, share lessons-learned, and provide recommendations for validation approaches. The volume and quality of studies of BMD data generation/validation/interpretation, the comparability among studies, and the pathway to overcome the challenges confronting the successful use and acceptance of BMDs for clinical research in CNS diseases must be improved. BMD's are promising, but as yet unproven, DDTs to advance innovative treatments for various stages of AD and other neurodegenerative diseases.