Using AI to Accelerate the Speed of Biomarker Discovery
With an unprecedented amount of data being collected in life science research today, the analysis of large multi-omic datasets for biomarker discovery has become a challenge.
Sifting through a treasure trove of biological data now requires that research teams hire programming and biostatistics expertise, slowing the discovery process and adding significant costs.
Recognizing the opportunity to bring artificial intelligence-driven predictive modeling to complement the data provided by our CyTOF™, Imaging Mass Cytometry™ and SomaScan™ platforms, Standard BioTools collaborated with Stanford University startup, Surge, to create a solution. The collaboration, initiated in 2024, began by creating a scientific co-pilot that could rapidly analyze data and identify sparse and reliable biomarkers.
This early effort evolved into Biomics, an AI-powered data analysis service built on validated machine learning and peer-reviewed science to accelerate the path from data to biomarker discovery. There are three parts to the SBI services offering:
Panel design: The Standard BioTools™ Services Lab can consult on study objectives, keeping the project streamlined with ready-to-use panel kits and customized targets.
Data acquisition and analysis: We also offer an in-house lab and team of experts to process samples and produce meaningful datasets using state-of-the-art omics platforms.
Advanced AI analysis: Powered by Surge’s technology, the Biomics platform provides comprehensive reporting with methods and figures, interpretable models and metrics, and reliable biomarker signatures, integrating CyTOF, Imaging Mass Cytometry and SomaScan data to quickly deliver clear biological insights.
“This partnership represents a major advance in the integration of AI and biomedical research. We believe that our combined expertise is paving the way for unprecedented advancements in biomarker discovery.”
- Brice Gaudilliere, MD, PhD
Surge Co-Founder and Associate Professor of Anesthesiology,
Perioperative and Pain Medicine at Stanford University
