Altoida Starts Five-year Study to Validate Disease-predicting App

Margarida Maia, PhD avatar

by Margarida Maia, PhD |

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Altoida is starting a five-year study to feed its app-based Precision Neurology device with data from thousands of patients across all stages of Alzheimer’s, to help validate the device’s ability to diagnose the disease at the earliest phases.

The device will use artificial intelligence (AI) to collect and analyze the results of a series of augmented reality and motor activities that simulate real-world activities of daily living. These activities can be completed on a smartphone or tablet in less than 10 minutes, the company stated.

The study will be conducted in collaboration with Eisai and the Bioinformatics and Human Electrophysiology Laboratory (BiHELab) at Ionian University in Greece.

“We are launching the world’s most comprehensive study ever conducted in Alzheimer’s, and related neurological diseases,” Travis Bond, CEO of Altoida, said in a press release. “This collaboration has the potential to unlock more about the pathology and the progression of Alzheimer’s than has ever been understood before, and to enable a new gold standard with Precision Neurology.”

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The diagnosis of Alzheimer’s disease typically requires a doctor’s assessment of the patient’s history, a physical exam, a mental status test, and additional tests, such as blood and imaging tests. Detection of the accumulation of an abnormal protein called beta-amyloid, and the development of neurofibrillary tangles — both of which are known to characterize Alzheimer’s — is possible on samples of cerebrospinal fluid or using an imaging test called a positron emission tomography scan.

However, some of the early signs of Alzheimer’s are undetectable by standard diagnostic methods. Thus, digital biomarkers of the disease may facilitate early diagnosis, and an early diagnosis means patients can gain earlier access to treatment.

Altoida’s non-invasive device uses AI to look at nearly 800 digital biomarkers that chart to 13 neurocognitive domains — from memory to cognitive processing speed and fine motor coordination — often affected in Alzheimer’s. Measuring and monitoring neurocognitive function could help to diagnose and distinguish Alzheimer’s from other disorders, including mild cognitive impairment.

The company expects to unlock important insights about the development of the disease.

“The insights obtained will not only contribute to supporting dementia patients, but also to informing care for those concerned about developing dementia,” said Keisuke Naito, a vice president and chief ecosystem officer at Eisai.

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Earlier this year, the device was given breakthrough device designation by the U.S. Food and Drug Administration for its potential to predict the likelihood that a person, 55 years or older, with mild cognitive impairment will progress to Alzheimer’s.

“This study has the potential to quantify the contribution of many different parameters, patterns, and signatures in the progression from Mild Cognitive Impairment to Alzheimer’s,” said Panagiotis Vlamos, PhD, scientific director at BiHELab. “With this deeper understanding of Alzheimer’s pathology, we can define and develop comprehensive analytical models to predict disease progression with unprecedented accuracy.”