This pilot will collect micro-errors from driving behavior and everyday life data and analyze them with machine learning. The goal will be the introduction of digital phenotyping as a tool that can have a potentially powerful role in the early identification of patients with Alzheimer’s disease (AD).
The tool named Alzheimer's Disease Prediction Service (ADPS) can become useful to support research into new treatments for cohorts of patients with AD early in the course of their disease process. It could also provide real-world evidence for the vitally important clinical trials of innovative treatments designed to test whether a new (or old) treatment can be effective in delaying or (at some point) preventing the progress of the disease for an indefinite period of time. This can be a commercially valuable tool in clinical trials, especially as a powerful tool in evaluating the effectiveness of therapy over time—and in the future, making adjustments in treatment based on these data. The first implementation of ADPS as part of a National Dementia Policy is happening in Greece, as part of the Digital Governance Brain Registry and it is offered free of charge.