Our Technology
General Metabolics’ proprietary technology platform for metabolomics is uniquely suited for delivering deep biological insight at an unprecedented speed and scale.

Ultra-High Throughput
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.

Broad Unbiased Coverage
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.

Automated Data Generation

Comparative Analysis
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.

Integrated Multi-Omics
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.
Interested to read more about how GMet technology is being used to advance and scale metabolomics research and bring new insights to industry?
Following are selected peer-reviewed publications with General Metabolics founders and advisors.
Regulatory mechanisms underlying coordination of amino acid and glucose catabolism in E. coli.
Nature Communications, 2019
Diabetes, 2019
Science Translational Medicine, 2018
Immunity, 2018
Molecular Systems Biology, 2018
Modulation of Myelopoiesis Progenitors Is an Integral Component of Trained Immunity.
Cell, 2018
Nature Methods, 2017
Genomewide landscape of gene–metabolome associations in Escherichia coli.
Molecular Systems Biology, 2017
Cell Metabolism, 2017
Metabolic control of TH17 and induced Treg cell balance by an epigenetic mechanism.
Nature, 2017

