Alzheimer’s study looks to BYOD tech

Alzheimer-s-study-looks-to-BYOD-tech.jpg
(Image: Getty/Ocskaymark) (Getty Images/iStockphoto)

Datacubed Health’s mobile platform has been selected to support a longitudinal Alzheimer’s study aimed at better understanding the disease and finding effective treatments.

The global studies will involve those at risk of Dominantly Inherited Alzheimer’s Disease (DIAD), a rare form of early-onset Alzheimer’s Disease.

Datacubed’s Linkt platform will be used to collect real-time data on sleep, diet, and other biomarkers using a “bring your own device” (BYOD) study model, according to the company.

“Datacubed Health’s tools allow researchers and study coordinators to enroll participants, monitor real-time progress and compliance dashboards, manage incentives, and review study data, and link these with detailed information collected during traditional in-person research assessments,” said Eric McDade, Principal Investigator for the DIAN Expanded Registry.

The study will include individuals with confirmed or suspected DIAD in their families and is being conducted by scientists at the Dominantly Inherited Alzheimer Network (DIAN) at the Washington University School of Medicine in Saint Louis.

“In Alzheimer's, it is critical to move scheduling information and tasks remotely so that patient burden can be minimized and the adoption of real-world settings can be realized,” said David Kiger, Datacubed Health CCO.

The research will incorporate an observational study, clinical drug trials, a research registry, as well as other, smaller, ancillary studies.

McDade told us, “The goals of the study are to collect relevant information from participants in DIAN related studies that can help in understand the disease and lead to effective treatments.”

Moving forward the study will examine additional outcomes, “such as those input by caregivers for collateral sources to report on research participants,” said McDade. Researchers also will track additional data, like sleep measure, and identify alternative ways to remotely collect trial data.