Panome Bio, a multi-omics contract research organisation, has launched MassID, a cloud-based computational platform designed to improve how researchers process and interpret untargeted LC/MS metabolomics data.
MassID is described in a new bioRxiv preprint titled “MassID provides near complete annotation of metabolomics data with identification probabilities.”
Untargeted metabolomics is a powerful approach for biological discovery, capable of detecting hundreds to thousands of small molecules that reflect physiology, disease state, and response to treatment. However, its impact has been limited by the complexity of LC/MS datasets. It is challenging for researchers to identify the true metabolite signals hidden amongst the tens of thousands of signals coming from chemical noise and artifacts. This has hindered the ability of researchers to identify all metabolites present in the sample while also generating high-confidence biological interpretations.
MassID was developed to solve this challenge by providing an end-to-end computational pipeline that converts raw LC/MS/MS data into cleaned, normalised, and annotated metabolite profiles—while also introducing probability-based confidence scoring for the metabolite identifications made.
“Metabolomics is capable of incredible biological insight, but the field has been held back by the complexity of LC/MS data and the inability to assign validated confidence to metabolite identifications,” said Gary J. Patti, chief scientific officer of Panome Bio and professor at Washington University in St. Louis.
“MassID changes what’s possible by introducing probabilistic metabolite identification and global false discovery rate control, which brings untargeted metabolomics closer to the statistical rigor of genomics.”
MassID also expands the number of metabolites that can be confidently identified and used for downstream analysis through a 280,000-metabolite database and advanced computational modelling, all executed with scalable cloud infrastructure. In a human plasma dataset, MassID structurally identified more than 4,500 metabolites, including over 1,200 compounds identified at <5% false discovery rate.
“MassID represents a major step forward for metabolomics and reinforces Panome Bio’s commitment to build leading-edge technologies that accelerate biological discovery,” said Edward Weinstein, CEO and co-founder of Panome Bio.
“By increasing both coverage and confidence, MassID helps researchers extract more meaningful insight from metabolomics data and better connect molecular findings to biology, disease, and drug development.”
MassID is now integrated into Panome Bio’s metabolomics service offerings and is available to biopharma, biotech, and academic partners.