Project Summary This study (DETECT-AD or Digital Evaluations and Technologies Enabling Clinical Translation for AD) objective is to fundamentally asymptomatic improve assessment of meaningful cognitive function in early pre- or Alzheimer's Disease (AD) using largely passive home-based digital assessment methods.To achieve this goal the approach will be tested in a prospective 36-month pre-clinical AD trial simulation using a current, sharable, technology agnostic, home-based assessment platform, continuously generating passive and interactive sensor-derived digital biomarkers (DBs) and metrics of everyday cognition and function (digital indicators of active life status or DIALS). The platform also allows for remote capture of conventional clinical assessments. Participants with defined amyloid status (Aβ-high vs. Aβ-low based on relative amyloid PET burdens) will be enrolled. Aβ-high participants will progress as if they were receiving placebo; those with lower Aβ burdens will have less progression, simulating effective treatment. Participants will be asked to take a daily multivitamin as a study `drug' to mimic trial conditions. The primary outcome will be change in the DBs and composite DIALS from four key domains: mobility (gait speeds), cognition (computer usage), sleep (sleep times), socialization (time out of home). Specific Aims are to: 1) Determine rates of progression of DBs (of mobility, cognition, sleep and social engagement) individually and as an aggregate metric (the DIALS) in FDA stage 1-3 AD (Aβ-high vs. Aβ-low) participants, by establishing early base rates (first months of monitoring) of progression, and then, longitudinal change; 2) Establish the utility of these DBs compared to conventional measures (CDR-SoB, ADCS-PACC) used in trials; and 3) Investigate Exploratory Aims examining several high-value features of these DBs for application in trials and related studies including: 3.1) Correlate DBs and DIALS with conventional imaging and blood-based biomarkers of inflammation, neurodegeneration, vascular risk or injury, and nutritional health; 3.2) Determine the change over time of embedded “cognitive clocks” (time to complete regular weekly online report queries and monthly cognitive tests); 3.3) Establish adverse event fluctuations over time (mood; illness; pain; ER, doctor, hospital visits; injury; non-study medication changes) via weekly remote assessment; and 3.4) Assess the study partner's DBs change relative to the person with AD (mobility, sleep, social engagement). study thus Successful completion of this will provide foundational validated DB and DIALS data improving treatment response readout sensitivity; 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 going forward.

Project Narrative It is difficult to detect early, subtle changes in memory and day-to-day function indicating Alzheimer's disease using current clinic-based tests and questionnaires. Set in a clinical trial environment, DETECT-AD advances the ability to assess real-world change at home using a combination of regular online responses and unobtrusive activity sensors and devices deployed in the homes of people at risk for Alzheimer's disease. Detecting these changes in everyday life can transform the development of therapies for Alzheimer's disease by accelerating the ability to see early-on if a therapy is working in a meaningful way reflective of typical life experience.