With a time-to-diagnosis of close to 10 years, endometriosis is a common disease which can be severely debilitating. ScaiVision helped discover novel biomarkers which have the potential to facilitate this diagnosis using a simple blood draw.
Continue readingMass cytometry and machine learning delineate tumor-defining cells in Sézary syndrome to allow discrimination from benign erythroderma (European Journal of Cancer)
Sezary syndrome is a cutaneous (skin) lymphoma which can be hard to distinguish from atopic dermatitis, a common skin condition. Our platform was able to identify rare tumor-related cells in blood from patients with early stages of Sezary syndrome enabling the rapid and sensitive diagnosis of this life-threatening condition.
Continue readingDLBCL white paper (potential)
While cell therapies have driven a paradigm shift in cancer treatments, they are also associated with dangerous side effects. ScaiVision helps guide treatment decisions by predicting the likelihood of neurotoxicity in patients receiving CAR-T cells to treat their lymphoma.
Continue readingGM-CSF and CXCR4 define a T helper cell signature in multiple sclerosis (Nature Medicine)
Using the core machine learning algorithm underlying ScaiVision, our co-founder Prof. Claassen and coworkers were able to identify a novel T-cell population involved in multiple sclerosis expressing specific markers which allows them to attack the central nervous system. This discovery could help drive faster diagnosis and future targeted therapies.
Continue readingComparative immune profiling of acute respiratory distress syndrome patients with or without SARS-CoV-2 infection (Cell Reports Medicine)
In this study, exploiting ScaiVision’s unique sensitivity, we were able to identify an immune population strongly linked to the development of complications from COVID associated with a high mortality rate.
Continue readingSensitive detection of rare disease-associated cell subsets via representation learning (Nature Communications)
Original manuscript establishing the framework which laid the groundwork for our biomarker discovery platform ScaiVision. Initially designed for CyTOF data, we have now extended this framework for the integrative analysis of a large variety of data modalities enabling true multimodal analyses crucial for precision medicine.
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