ANLIVA Eye Movement as a potential digital biomarker

Eyetracking unlocks new potential digital biomarkers of Parkinson’s disease
Today, diagnosis of Parkinson’s disease and subsequent treatment decisions are primarily based on subjective ocular assessments of the cardinal motor symptoms, such as tremors, bradykinesia and rigidity. This often leads to longer times for finding individualized effective treatments which can lead to the disease progressing faster and lower quality of life for the patient. Digital biomarkers based on sensor measurements and mathematical modeling have the opportunity to aid in making more objective and equal clinical decisions.

Eye movement abnormalities occur frequently in people with Parkinson’s disease. One type of eye movements commonly affected is known as smooth pursuit, which are eye movements we use to track and keep our gaze focused on moving objects. Instead of tracking the moving objects smoothly, people with Parkinson’s often shifts into using saccades, which are much faster, ballistic eye movements, more commonly used to quickly shift one’s focus from one object to another. Saccades used to “catch up” with a smooth pursuit target, is therefore commonly called “catch up saccades”.
ANLIVA® Eye Movement makes use of modern eyetracker hardware to capture and quantify eye movements of a user that is viewing a smooth pursuit stimulus on a computer screen. The aim is to provide a new set of eye movement biomarkers, including frequency and magnitude of catch up saccade events, modeling of the smooth pursuit dynamics and statistical references to different human populations.

ANLIVA® Eye Movement is currently in clinical trials and being co-developed together with the Dartmouth-Hitchcock clinic in the USA. In these trials, the eye movement biomarkers are being evaluated for their significance in relating to the disease state and treatment response in people with Parkinson’s disease. The goal is to file for FDA 510(k) clearance by the end of 2025, targeting a release on the US market.

Animation above shows the captured gaze of a patient with Parkinson’s disease (PD) viewing a visual smooth pursuit stimulus. A probability distribution of a healthy control (HC) baseline is also shown. The gaze of the PD patient often lags behind the stimulus and the patient shifts into using catch up saccades to keep up. This type of movement frequently falls outside of the HC baseline.