Partnership aims to develop next-generation data-driven models for personalized deep brain stimulation (DBS) targeting, expanding clinical applications from Parkinson’s disease and essential tremor to dystonia and severe pediatric dystonia with global scalability potential.
Rebrain, a French Medtech company specializing in data-driven brain stimulation planning, has announced a strategic collaboration with an International University Hospital to develop a new generation of precision models targeting the globus pallidus internus (GPi). The initiative builds on data in severe dystonia, including rare and disabling pediatric forms.
This collaboration marks a significant expansion of Rebrain’s clinical scope: first, it enables Rebrain data–based personalized targeting to broaden its application to dystonia cases; and second, it allows the platform to extend to a wider range of movement disorders, including Parkinson’s disease (a dyskinesia-predominant phenotype) and essential tremor.
Addressing a Complex and Heterogeneous Neurological Disorder
Dystonia represents a highly heterogeneous group of movement disorders, including genetic forms, such as DYT1 which is the most common cause of inherited isolated dystonia (Charlesworth and al., 2013). Pediatric dystonia alone is estimated to affect between 1 and 5 per 100,000 children (Stephen and al., 2023). In its most severe forms, it can become profoundly disabling, progressively locking children into abnormal postures and relentless involuntary contractions that severely compromise mobility, communication, and daily functioning, often leading to complete loss of independence and in the most extreme cases, potentially contributing to life-threatening complications.
In these advanced pediatric cases, DBS targeting the GPi is increasingly preferred over alternative targets, due to its more stable modulation of involuntary muscle contractions, improvements in posture and motor function, as well as a broader positive impact on quality of life. However, the clinical response to GPi stimulation remains highly variable depending on disease etiology. Therefore, targeting precision remains a key determinant of both efficacy and side-effect profiles, including speech impairment, gait disturbances, and subtle cognitive effects.
Completion of the Parkinson’s Disease Offering
In the U.S., DBS is widely adopted across more than 600 centers. In this context, the GPi target is used for the treatment of adult patients with Parkinson’s disease. Increasing clinical demand, combined with limited neurologist availability, has accelerated interest in standardized, technology-assisted targeting solutions. However, at a broader international level, the subthalamic nucleus (STN) remains the predominant DBS target, accounting for approximately 60–80% of cases, followed by the globus pallidus internus (GPi) at around 20–40%, while the ventral intermediate nucleus (VIM) is used in less than 10% of cases (Mao et al., 2019).
This collaboration aims to support a broader adoption of GPi targeting strategies by expanding the capabilities of smaller U.S. centers, improving access to expert-level decision-making, and contributing to the emergence of international standards in neuromodulation. In this sense, Rebrain completes and strengthens its existing offering in Parkinson’s disease.
Toward Scalability and Standardization in the U.S.
This collaboration seeks to address one of the key limitations in DBS therapy: the lack of standardized, patient-specific targeting strategies. Current practice remains highly dependent on expert centers, with only an estimated 150–250 highly specialized GPi DBS centers worldwide, resulting in significant geographic disparities in access to care. By leveraging clinical datasets and advanced computational modeling, the partnership aims to identify neural targeting patterns associated with optimal clinical outcomes and to develop predictive algorithms capable of guiding individualized DBS planning. The ambition is to shift GPi stimulation from expert-dependent decision-making toward scalable, data-driven precision medicine, thereby reducing variability in outcomes and potentially limiting adverse effects. In the U.S., this approach is particularly aligned with a healthcare environment characterized by growing procedural demand and limited specialist availability. It responds to an increasing need for standardized, technology-assisted decision support tools in functional neurosurgery.
By integrating predictive modeling into DBS planning workflows, the initiative supports broader adoption of optimized GPi targeting strategies, enhances access to expert-level decision-making, and contributes to the emergence of international standards in neuromodulation therapies.
“This collaboration represents an opportunity to move toward more structured, data-informed targeting strategies that could significantly improve both efficacy and safety, particularly in complex pediatric cases”, declares Emmanuel Cuny, Functional Neurosurgeon, Co-founder, CMO and Chairman of Rebrain.
Impact and Future Perspectives
The collaboration is expected to generate both scientific and clinical advancements in the field of functional neurosurgery, particularly in understanding variability in DBS response across dystonia subtypes. From an industrial perspective, the project positions Rebrain within a rapidly growing segment of digital neurosurgery, where demand for scalable, evidence-based targeting solutions is increasing, particularly in high-volume U.S. DBS centers. If successful, the model could serve as a reference framework for standardized GPi targeting, paving the way for broader applications across other movement disorders and DBS indications.
