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Scailyte’s proprietary and best-in-class analytical platform ScaiVisionTM is at the altruistic core of our company. It enables us to integrate and interpret single-cell multi-omics and clinical data for identifying complex multidimensional signatures and associated genes and cell populations. While using a convolutional neural network, ScaiVision™ looks for these signatures in the unknown sample cohorts and classifies them for the phenotype of interest. Key benefits are:

  • Entirely agnostic to indications of interest
  • Data augmentation enables the identification of ultra-accurate signatures from a limited number of datasets
  • Scalable analysis of datasets up to hundreds of millions of cells without sub-sampling
  • Retains single-cell resolution throughout the interpretation stage & calculates the clinical endpoint-associated score for every single-cell
  • Flexible integration of other omics data types

ScaiVision analysis workflow

ScaiVision analysis workflow

ScaiVision® performs best-in-class at sample class prediction, read more:

Single-cell discovery & Data analytics

Single-cell discovery

Our biomarker discovery platform is based on machine learning algorithms to find predictive patterns in high-dimensional single-cell data. By analyzing millions of individual cells with an unbiased approach, we can identify the precise molecular profiles of individual cells pinpointing their biological “state”, deviation from healthy physiological pathways or their biological response to a therapeutic at a high level of sensitivity.

We are currently applying our discovery engine to the following single-cell technologies, with additional innovations in development: mass cytometry (CyTOF), single-cell transcriptomics.

The applications of our technology are manyfold: we help drug developers increase the probability of success of their molecules and reduce R & D cycle times by:

  • analysing the MoA of drug candidates on a single-cell and multi-omics level,
  • identifying predictive markers of response for patient stratification and smarter clinical trial design,
  • finding predictive markers of toxicity for improved patient management,
  • co-developing a companion diagnostic assay,
  • and many other applications.
Helping you speed up your therapy development and increase your success rate