Reinventing multiomic data interrogation and biomarker model discovery

The proliferation of biomarker data has created a massive challenge as teams must compile data sets from multiple labs covering several assay types and numerous time points. Today’s multiomic approach demands the harmonization of these data sets as well as relevant clinical annotation for subsequent interrogation.

Simplicity employs a powerful new multivariate approach to address the weaknesses of current methodologies – striking the delicate balance between accuracy and quantity of biomarkers.

Across six cancer datasets, Simplicity achieved an accuracy of 95.83% or higher and exceeded the accuracy of every method it was compared to. But the key to Simplicity’s superiority is not just its exceptional accuracy, it is its ability to constrain the number of variables in each model and provide the results in an intuitive and interpretable interface.