More Than Meets the Eye: Using Eye Movements in Drug Development for Neurodegenerative Diseases

Drug development for neurodegenerative diseases is struggling with one of its most intractable barriers: the slow, variable, and subjective nature of clinical endpoints Traditional assessment scales, whether in Parkinson’s disease (PD), amyotrophic lateral sclerosis (ALS), or multiple sclerosis (MS), and Alzheimer disease (AD), often miss subtle or early changes, leading to long, costly trials that delay patient access to urgently needed therapies. These limitations force pharma companies to recruit larger cohorts, extend study durations, and absorb high attrition risk, resulting in increased trials’ costs.

A promising solution may be hiding in plain sight. Eye movements offer a fast, objective, and highly sensitive way to capture changes throughout CNS disease progression. With today’s technology, they can be measured in minutes on a standard laptop or webcam, making them a feasible tool for clinical trials. Importantly, these measures can be easily integrated into existing trial workflows, providing an accurate, reliable and objective tool to measure disease progression over time.

Eye movements have been known for decades as “the window to the brain”, as they are tightly coupled to neural circuitry. Saccades and antisaccades reflect frontal and subcortical control of attention and inhibition; smooth pursuit engages cortical–cerebellar networks; fixation stability draws on widespread cortical and brainstem systems. As such, they can reflect changes in patients’ status over time, which was widely demonstrated by abnormalities in these different oculometric measures  in disorders like Parkinson’s disease, ALS, and MS. Due to recent technological development, measuring eye movements no longer requires specialized labs or designated equipment. Today, a short test using a laptop and webcam can be used, utilizing computer vision algorithms to quantify movement parameters automatically, with minimal site burden, especially relevant in multicenter trials. 

During the last years, several approaches have been described using different devices, in order to enable measuring eye movements outside the lab, used in several trials. Recently, our team developed a short test using only a laptop and a webcam, utilizing computer vision algorithms to quantify movement parameters automatically, with minimal site burden, especially relevant in multicenter trials. This technology has been already used in several trials in differernt CNS diseases, with publication of promising results. In Parkinson’s for example, replacing a 21-month motor scale endpoint with a nine-month oculomotor measure reduced the required sample size per arm from 360 to 140. In ALS, longitudinal results of a Phase IIb trial revealed progressive fixation instability aligned with disease worsening over 12 months. These examples underscore that eye movements can be highly relevant as an additional endpoint, improving trial efficiency and serving as a promising biomarker to detect progression over time. 

The regulatory environment is increasingly supportive of looking into additional endpoints in CNS trials, among them digital health technologies (DHT). The FDA’s guidance on DHT explicitly highlights the importance of creating a framework for integrating tools which can serve as validated reliable endpoints like eye movements into clinical trials. This creates a clear pathway for sponsors to introduce oculometric endpoints as an exploratory endpoint day, with the potential for future qualification.

Simultaneously, the trial landscape is shifting. Various biomarkers are being adopted to complement traditional scales and generate richer datasets. As a part of this shift, eye movement measures are especially well positioned: they are highly objective, accurately measured, easy-to-use and scalable across diverse trial environments. This convergence of regulatory openness along with operational innovation makes now the right moment to integrate eye movement biomarkers into CNS development.

The path forward can be done gradually. As a first step, sponsors begin to involve eye movements as a biomarker by adding oculometric endpoints to early-phase studies, capturing them alongside standard scales. This dual collection builds the evidence base while mitigating risk. A core set of oculometric measures, which are tailor-made per indications, e.g. saccades, pursuit, and fixation tasks, ensures comparability across sites and studies. In addition, predefined workflows enable reproducible extraction of metrics, with robust governance for storage and analysis. Per the needs of the specific trial, sponsors should pre-specify hypotheses about how eye-movement metrics are clinically relevant, as they correlate with clinical anchors, stratify participants, and detect early disease progression. Finally, transparent engagement with regulators can smooth the pathway from exploratory use to accepted endpoint.

A year from now, clinical sites can involve eye movements in drug trials as an endpoint, with streamlined workflows, short oculometric assessments and reproducible setups. For participants, the experience will feel seamless, as there are no burdensome devices and no lengthy procedures.

Regulators and payers will begin to see integrated evidence packages that combine established scales with objective eye-movement measures. These packages will not only support trial claims but also inform real-world coverage decisions by demonstrating sensitivity to disease progression. The broader research community will gain access to richer datasets, accelerating secondary analyses and cross-disease insights. This vision is achievable within existing trial infrastructures, provided stakeholders commit to integrating eye-movement endpoints now rather than later.

The CNS field urgently needs biomarkers that are sensitive, objective, and practical. Eye-movement measures are ready to fill this gap, not as distant innovations, but as tools available today. By incorporating eye movement assessments as exploratory endpoints, sponsors can shorten timelines, reduce sample sizes, de-risk trials, and improve decision-making. Sites can enhance efficiency, regulators can receive stronger evidence, and patients can gain faster access to effective therapies. The industry should treat oculometric measures as the missing piece in CNS trials: scientifically grounded, simple to implement, and aligned with current regulatory frameworks. Broader adoption could reshape the pace of drug development and bring life-changing treatments to patients sooner.

Photo: Jay_Zynism, Getty Images

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