Solvemed Showcases PuRe™ Pupillometer at International Stroke Conference (ISC) 2025

Showcasing AI-Driven Pupillometry at ISC 2025

Solvemed participated at the International Stroke Conference (ISC) 2025, a meeting that brings together the most influential voices in stroke research and clinical innovation. Across three days, our team engaged with neurologists, intensivists, nurses, and hospital leaders who are actively shaping the future of acute stroke care. The focus of our presence was the PuRe Pupillometer, an AI-driven neurodiagnostic device that advances smartphone-based pupillometry from a simple measurement tool into a clinically meaningful component of acute neurological assessment.

Throughout the conference, clinicians expressed strong interest in the ability of the PuRe Pupillometer to introduce consistency, high precision, and rapid interpretation into an area of bedside neurology that has struggled with variability for decades. Those conversations reinforced a clear trend. Stroke teams are seeking practical solutions that strengthen early detection and triage, support dynamic monitoring in intensive care, and reduce gaps between bedside assessment and actionable neurodiagnostic data.

AI-Driven Quantitative Pupillometry with PuRe Pupillometer

The PuRe Pupillometer represents a modern approach to neurodiagnostics by pairing high-resolution imaging with artificial intelligence trained to evaluate subtle dynamics of the Pupillary Light Reflex. Its smartphone-based design enables millisecond timing precision and submillimeter measurement accuracy, bringing a level of uniformity to pupillometry that has historically been difficult to achieve in busy clinical environments.

AI-driven interpretation mitigates inter-observer variability and transforms pupillary reactivity into structured clinical data that stroke care teams can rely on when assessing neurological status or tracking changes over time. This is particularly valuable in acute settings where rapid clinical decisions depend on accurate, repeatable assessments that reflect evolving intracranial physiology. By embedding these capabilities into a device that fits naturally into workflows, the PuRe Pupillometer supports clinicians without adding procedural complexity.

Value of Quantitative Pupillometry in Stroke Care

The role of objective pupillometry in stroke care continues to expand as evidence accumulates around its ability to detect early neurological changes. The Pupillary Light Reflex offers information that extends beyond pupil size and captures dynamic physiologic responses linked to intracranial pathology.

Osman and colleagues in 2019 demonstrated a meaningful correlation between quantitative pupillometry metrics such as constriction velocity and the degree of midline shift in acute ischemic and hemorrhagic stroke. Notably, the relationship did not hold for pupil diameter alone, which underscores the diagnostic value of reactivity parameters rather than static measurements. Giamarino et al. in 2021 reinforced this interpretation by identifying significant correlations between the Pupillary Light Reflex, anisocoria, and midline shift at both the septum pellucidum and the pineal gland.

These findings align with broader trends in neurocritical care. As described by Zanier et al. in 2024, continuous neuromonitoring techniques, including pupillometry, contribute to more individualized management by identifying early deviation from expected neurological trajectories. When subtle changes in pupillary reactivity precede clinical deterioration, care teams gain an opportunity to intervene before the patient’s condition worsens. This advantage is particularly relevant in stroke, where timely action influences outcomes more than in nearly any other acute neurological disorder.

The Future of AI-Driven Neurodiagnostics in Critical Care

Solvemed’s presence at ISC 2025 highlighted a growing recognition that AI-driven pupillometry belongs among the essential tools for modern stroke care. Clinicians who evaluated the PuRe Pupillometer pointed to its potential to close long-standing diagnostic gaps and to provide a reproducible method for monitoring neurological status in high-acuity settings.

Our scientific posters presented at the conference provided additional depth, outlining clinical outcomes and research findings derived from quantitative pupillometry in stroke populations. This work adds to a broader movement in which machine learning and advanced neurodiagnostic algorithms are reshaping the way clinicians capture, interpret, and respond to neurological change.