GMet’s technology utilizes direct injection of samples on high resolution mass spectrometers to maximize analytical throughput, allowing metabolite discrimination in highly complex mixtures. By avoiding traditional column chromatography, we’re able to exponentially increase sample throughput relative to LCMS approaches, and run extremely large experiments from 1,000 to +40,000 samples with rapid turnaround.

GMet’s non-targeted methods screen for known and unexpected metabolites. Unlike targeted approaches, our non-targeted methods can reveal novel metabolic phenotypes and biomarkers that would otherwise be missed. These tools have helped our clients accelerate therapeutics development, pathway engineering, biomarker discovery and mechanistic cellular research.

We utilize proprietary software tools to enable fully automated data processing and delivery. This includes metabolite abundance and annotation, differential analysis, cohort statistics, and pathway enrichment analysis. 

GMet’s platform enables seamless integration of genomics and metabolomics data sets. Our network-based integration methods find relationships between genes and metabolites to uncover novel biological mechanisms.