Transforming precision medicine and diagnostics with virtual biomarkers

Biomarker detection is vital to the development of precision medicines.

20%

of the world's population will be diagnosed with cancer

35%

of which will be treated with precision medicine

80%

of precision medicine relies on biomarker identification

ViewsML harnesses the power of AI for virtual diagnostics, discovering deeper insights and enabling better patient outcomes

Receiving biomarker results from a diagnostic lab can take weeks.

Interpretation of results can vary by up to 30% between pathologists.

Manual IHC

ViewsML uses deep learning to eliminate manual staining, delivering virtual results in seconds at a fraction of the cost, all the while fitting into existing workflows.

Virtual IHC

Any Biomarker.
Any Therapeutic Area.
Any Species.

Preclinical Research

EXPEDITE

Discovery, toxicity and safety studies

Translational Research

EXPAND

Spatial biology insights of rare tissues with virtual multiplexing

Clinical Research

SCREENING

Better patient selection, increase patient enrollment efficiency

Virtual Diagnostics Assays

TRIAGING

Patient stratification, triaging, and companion diagnostics

Contract Research Organizations

QUICKLY

Improve project turnaround times, provide richer data sets

Any Biomarker.
Any Therapeutic Area.
Any Species.

  • Preclinical Research

    EXPEDITE

    Discovery, toxicity and safety studies

  • Translational Research

    EXPAND

    Spatial biology insights of rare tissues with virtual multiplexing

  • Clinical Research

    SCREENING

    Better patient selection, increase patient enrollment efficiency

  • Virtual Diagnostics Assays

    TRIAGING

    Patient stratification, triaging, and companion diagnostics

  • Contract Research Organizations

    QUICKLY

    Improve project turnaround times, provide richer data sets

Advantages of Virtual Staining

  • Easily integrated into preclinical & clinical workflows

  • Eliminates time and cost constraints associated with traditional IHC and IF

  • Multiplexing allows for greater biomarker characterization

  • Preserves scarce tissue samples

  • Consistent and reproducible immunostaining, every time

  • May be trained to any biomarker across any disease type and species