Digital Evaluations and Technologies Enabling Clinical Translation for AD

Alzheimer Disease, Early Onset

The DETECT-AD study (stands for Digital Evaluations and Technologies Enabling Clinical Translation for Alzheimer's Disease) is a new study designed to improve clinical trials for early Alzheimer's disease. DETECT-AD uses specialized home-based digital devices (electronic scale, electronic pill box, under-the-mattress sleep sensor, motion activity sensors, wrist watch activity tracker, driving sensor, and computer software) to see if the devices will improve clinical trial assessments. This 36- month-long study will simulate a clinical trial to determine how well the home system detects clinically meaningful changes. Participants in DETECT will receive a brain scan to assess their risk for developing Alzheimer's Disease. After the scan, homes will be outfitted with the devices\*. Participants will be asked to simply go about their daily routines while data is collected in the background by the digital devices. The scientists will see if there is a change in the digital assessments in four key areas of life activity: mobility (walking speed), cognition (computer use), sleep (sleep times), and socialization (time spent out of home). Participants will be asked to take a daily multivitamin as a study 'drug' to mimic clinical trial conditions. Using these methods, the DETECT study will produce outcome measures that reflect real-world everyday function. Establishing the superiority of these novel methods compared to conventional methods (for example, exams in a clinic) will provide a potential new pathway for speeding the development of muchneeded new treatments for Alzheimer's

To achieve this objective, we propose the DETECT-AD (Digital Evaluations and Technologies Enabling Clinical Translation for AD) Study. DETECT-AD is a prospective trial simulation study using a current, extensible, sharable, technology agnostic, and home-based assessment platform that continuously generates DBs and metrics of everyday cognition and function (or Daily Indicators of Active Life - 'DIALS'). The platform also allows for remote capture of conventional clinical assessments as well. A simulated trial study design is used, as there are no current established therapies that will reliably improve meaningful function in stage 1-3 AD10 patients to a degree that one can directly test the sensitivity of DBs or DIALS to treatment mediated change. In short, if there is no change over time in the proposed measure, one would not know if it was a failure of the measure or the treatment. Hence, the use of the simulation paradigm. In this trial, participants with known CNS amyloid (Aβ) status (SUVR-based PET positive or negative) will be enrolled. In the simulation, Aβ positive (higher amyloid burden) patients will predictably progress, as if they were receiving placebo; those with less amyloid (Aβ negative) will have less progression, simulating effective treatment. Primary outcomes will be the change in DBs and DIALS composed of measures in 4 key domains: mobility, cognition, sleep, and socialization. Exploratory analyses of the relationship of the DBs with contemporary imaging (MRI) and blood-based biomarkers related to inflammation, neurodegeneration, vascular risk or injury, and nutritional health will also be conducted. Impact: Successful completion of this study will provide foundational validated DB and DIALS data improving treatment response readout sensitivity, thus advancing AD clinical trial capability and capacity. The intent is to not only validate a single app or device, but to advance ecologically valid multi-domain assessment, as well as an entire trials-environment specific, DB-facilitated protocol that could be adapted and shared for use by any clinical trial or related study going forward.

United States