Diagnose a neurodegenerative disease in ten minutes. The statement is almost provocative, in a field where diagnosis is still largely based on clinical observation and the experience of the practitioner. With this promise, NeuroClues is part of a medicine that attempts to convert complex biological signals into measurable and usable data.
A diagnosis that comes too late
Parkinson’s disease remains emblematic of current limits. Motor symptoms (tremors, rigidity, slowness) only appear at an advanced stage. At the time of diagnosis, a significant proportion of dopaminergic neurons are already destroyed.
Added to this is persistent uncertainty, with a significant proportion of patients still subject to diagnostic errors. The neurologist must deal with clinical signs that are sometimes ambiguous, evolving, and difficult to assess. In this context, the challenge is not only to go faster, but to see sooner and measure better.
The eye as a neurological entry point
The NeuroClues approach is based on a known principle but little exploited on a large scale, namely that eye movements reflect the activity of the nervous system.
The device captures, via high-frequency infrared sensors, micro-movements of the eye during simple visual tasks. This data is then analyzed by artificial intelligence algorithms, which identify characteristic anomalies.
Where diagnosis used to be based on visible symptoms, it now relies on invisible, but quantifiable, biomarkers.
Ten minutes, but under what conditions?
The promise of a rapid test immediately raises the question of its validity, because in medicine, speed only has value if it is accompanied by reliability.
Three parameters structure the credibility of the approach here:
- the robustness of the oculomotor biomarker
- the quality and size of the datasets used to train the models
- large-scale clinical validation
In neurology, variability is the rule. Faced with overlapping symptoms, disease trajectories differ and diagnoses evolve over time. Reducing this complexity to a single signal constitutes both a methodological advance and a gamble.
Standardize without oversimplifying
This type of technology is part of the trend of standardization of diagnosis, with the aim of reducing the amount of subjectivity and limiting errors.
But this standardization has a cost; it requires transforming a complex biological reality into measurable variables. The question then becomes methodological: how far can we simplify without losing clinical relevance?
The risk is not so much the raw error as the reduction. A poorly interpreted signal, or one that is insufficiently contextualized, can guide the diagnosis in an inadequate manner.
A support tool more than a substitute
In its current form, the technology does not replace the neurologist, it acts as an additional layer of analysis, intended to objectify certain signals and reduce uncertainty. The interest is to improve early detection and provide quantified support for medical decisions.
The role of the doctor is evolving accordingly. It is no longer just a matter of interpreting clinical signs, but of combining instrumented data with an expert reading of the patient.
Towards broader screening
The portability and speed of the device open up perspectives beyond the hospital setting. A test that can be carried out in a few minutes could, ultimately, be integrated into broader care pathways, or even into community medicine.
This development is part of an underlying trend: that of more distributed medicine, less dependent on heavy infrastructure, and more oriented towards early detection. It also poses new questions, particularly in terms of overdiagnosis, management of false positives and organization of patient pathways.
A promise still under construction
Diagnosing Parkinson’s in ten minutes is a promise currently being validated, which is based on real technological advances, but still subject to field testing. It remains to be seen how far this logic can extend in a field where biological complexity resists, by nature, any excessive simplification.
10 million euros to scale up
Founded in 2020 and based in Brussels, NeuroClues is developing a wearable medical device to analyze eye movements to detect neurological abnormalities via artificial intelligence algorithms. CE certified since the beginning of 2025, the company has already deployed several dozen systems in healthcare establishments in Europe, relying in particular on clinical collaborations with reference centers. On April 9, 2026, NeuroClues raised €10 million in Series A from Teampact Ventures, White Fund and the European Innovation Council (EIC) fund, bringing the total capital raised to €25 million. This financing should enable it to accelerate its clinical deployment in Europe and prepare for its entry into the American market.
