betaSENSE - iRS Technology for Parkinson's Diagnosis
The advancement of the iRS technology from betaSENSE represents a significant innovation in the field of Parkinson's disease diagnostics. This technology addresses the critical unmet medical needs in accurately diagnosing Parkinson's and distinguishing between idiopathic and atypical cases. While there have been notable improvements in Parkinson's treatment, existing therapies often fall short, particularly in addressing non-motor symptoms such as cognitive impairments, depression, and autonomic dysregulations. iRS technology enhances diagnostic precision by identifying specific biomarkers, namely alpha-synuclein misfolding, involved in Parkinson's and related synucleinopathies. This method paves the way for future use in early detection and patient stratification, potentially supporting the development of disease-modifying therapies that could slow or halt disease progression. As a spin-off from Ruhr University Bochum, betaSENSE is at the forefront of certified diagnostic technology innovation, working to improve outcomes for individuals affected by Parkinson's.
betaSENSE's iRS technology enables highly sensitive and specific analysis of disease-relevant misfolding of alpha-synuclein directly from cerebrospinal fluid samples.
Unmet medical need in Parkinson's diagnosis
Despite significant advances in the treatment of Parkinson's disease, the disease continues to pose a significant medical challenge. The term "unmet medical need" in this context describes the gaps in current care and therapy that are not adequately covered by existing diagnostics, medications, or interventions.
While some therapies alleviate many motor symptoms, they often become less effective as the disease progresses and cause complications themselves. Furthermore, non-motor symptoms—such as cognitive impairment, depression, sleep disturbances, and autonomic dysfunction—often remain inadequately treated. There is an urgent need for disease-modifying therapies that can slow or halt disease progression.
The basic prerequisite for this is a precise test that identifies the disease with high accuracy and distinguishes it from others.
iRS enables first approaches to patient stratification
Initial subgroup analyses demonstrate the potential of iRS technology to differentiate between idiopathic and atypical Parkinson's cases.
High diagnostic accuracy in Parkinson's and MSA using iRS
The iRS analysis achieved an AUC of 0.90 and identified Parkinson's and MSA cases with 97% sensitivity and 92% specificity.
Direct detection of misfolding paves the way for the future
In the future, this test should also be able to be used for early detection.