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ScaiVision® performs best-in-class at sample class prediction!

ScaiVision® performs as the best-in-class algorithm at identifying molecular biomarkers, which accurately predict clinical status of the samples

ScaiVision performs as the best-in-class algorithm at identifying molecular biomarkers

About Scailyte

Scailyte is an ETH Zürich spin-off with a best-in-class artificial intelligence platform for the discovery of complex disease patterns from single-cell data. Our solution provides unprecedented insight into the disease and patients’ biology and enables the discovery of new clinically-relevant biomarker signatures by uncovering human’s hidden “single-cell” secrets. 

Scailyte’s proprietary best-in-class data analysis platform ScaiVision™ associates multimodal single-cell datasets (RNA-/TCR-/BCR-seq, proteomics, etc.) with clinical endpoints, such as disease diagnosis, progression, severity, treatment response, and toxicity response to identify ultra-sensitive biomarker signatures and cell functionality states. The performance and clinically-relevant applications of Scailyte’s platform ScaiVision have been demonstrated in well established CAR-T cell therapies and various clinical projects in Oncology and Immunology.

For more information, visit www.scailyte.com and connect on social media @LinkedIn and @Twitter.

Scailyte™ and ScaiVision™ are registered trademarks proprietary to Scailyte AG.

ScaiVision® v1.0.0 was released internally and benchmarked in a massive experiment, outperforming all competitor algorithms. ScaiVision performs as the best-in-class algorithm at identifying molecular biomarkers,
which accurately predict the clinical status of the samples. Analysis with ScaiVision unlocks an unparalleled level of high-resolution and clinically relevant discoveries in single-cell datasets. ScaiVision attains a mean AUC of 0.96 across all 10 cross-validation splits.

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