Digital biomarker company Altoida which is focused on using augmented reality and machine learning to identify neurological conditions, said that new research from the RADAR-AD consortium shows the promise of using augmented reality (AR)-based cognitive assessment for early identification and assessment of people with Alzheimer’s disease (AD).
The findings, published today in Nature Digital Medicine, show that the Altoida AR app could distinguish healthy controls from individuals with preclinical AD and prodromal AD both with in-clinic and with at-home tests and preformed at a level that is currently unattainable with standard cognitive tests.
“There is huge potential of digital devices and sensor technologies to enable objective and continuous monitoring of Alzheimer’s disease symptoms,” said RADAR-AD academic leader Prof. Dag Aarsland, chair of Old Age Psychiatry, King’s College London. “Altoida’s AR cognitive assessment seems to be one of the most promising emerging technologies in this field, and the RADAR-AD study results indicate that Altoida’s test can detect subtle cognitive and functional changes in individuals with AD even before they manifest any deficits. With the emergence of new disease-modifying Alzheimer’s drugs, early diagnosis is now more important than ever.”
The study applied Altoida’s AR app in amyloid beta negative healthy controls, amyloid-beat positive cognitively normal preclinical AD participants, and prodromal AD participants. Altoida AR is an investigational test that assesses motor and AR tasks. For the motor tasks, participants participate in short exercises to assess fine motor skills, visual abilities and reaction times assessed against personalize reference values. The AR are built to simulate instrumental activities of daily living (IADL) activity such as a “place-and-find” task a kind of hide and seek activity requiring users to hide, then find virtual objects by following specific instructions.
Study results showed Altoida AR was able to distinguish the healthy controls from people with both preclinical and prodromal AD. The Altoida AR tasks were administered in the clinic alongside a standard neuropsychological assessment battery, currently used for assessment of AD. Participants in the study also used the app independently on a weekly basis for up to eight weeks.
“The RADAR-AD data underscores Altoida’s key near-term goal: facilitating the rapid identification of suitable study participants for AD treatment developers, monitoring their cognitive and functional responses throughout the study, and collecting relevant data to support both our partner’s and Altoida’s regulatory filings,” said Marc Jones, Altoida CEO. “Altoida is dedicated to ongoing innovation and enhancement across all aspects of the Altoida AR app to achieve this important goal.”
The RADAR-AD (Remote Assessment of Disease And Relapse—Alzheimer’s Disease) study is assessing the functioning of people with AD and how existing, widely used technologies can be used to measure and assess even subtle changes in a person’s function to provide early identification of Alzheimer’s disease. The Altoida AR app is one such technology that employs a machine learning model that has been trained to differentiate between people who are cognitively normal from those people exhibiting some level of impairment. It collects data using device sensors to identify digital biomarkers from study data.
The company’s technology has piqued the interest of a handful of pharma companies who are actively developing drugs for AD and other neurologic conditions, including a deal in October 2021 with Japanese pharma Esai for a five-year study of AD.
