Thermo Fisher Scientific at Metabolomics 2026
Join us at the Thermo Fisher Scientific booth #P5 during the 2026 Metabolomics Conference in Buenos Aires, Argentina. We look forward to welcoming you to explore our latest breakthrough solutions for metabolomics and lipidomics, connect with our experts, and discover what is new.
Be sure to join us for our lunchtime seminar on Tuesday, June 23, from 12:20 p.m. to 1:20 p.m. Seating is limited, so we encourage you to arrive early. Lunch will be available while supplies last.
Lunchtime seminar
- Tuesday, June 23, 12:20 pm –1:20 pm
Debating the dark metabolome: Technologies to illuminate the unknown
Despite major advances in analytical sensitivity and metabolome coverage by mass spectrometry, a significant proportion of detected features in metabolomics studies remain unidentified, often referred to as the “dark metabolome.” What is holding us back?
We will host a panel discussion to explore the underlying causes, from incomplete spectral libraries and limited availability of chemical standards to biological context dependence and biases in extraction and ionization.
By debating strategic priorities and highlighting enabling technologies, such as enhanced dynamic range (eDR) and the multiple fragmentation modes of the Thermo Scientific Orbitrap Tribrid mass spectrometers, this seminar aims to illuminate the dark metabolome and push metabolomics toward a more comprehensive, and mechanistic science.
Join us for a brief introduction to the latest Thermo Scientific solutions designed to tackle these challenges, followed by a thought-provoking panel discussion with leading voices in the field:
- Rick Dunn, University of Liverpool
- Yasin El Abied, BOKU University
- Jennifer Kirwan, University of Veterinary Medicine Vienna
- Nicola Zamboni, ETH Zurich
Register now to reserve your spot. Seating is limited. Lunch will be available while supplies last.
Software demonstrations
Metabolomics datasets are only getting larger and more complex, making powerful data analysis software essential for turning raw data into real biological insight. From feature extraction and quantitation to statistics and compound identification, our software solutions are designed to help researchers confidently manage the entire workflow.
Join us at our software station to learn more about Compound Discoverer 3.4 software, TraceFinder software, and Mass Frontier Spectral Interpretation software, and how these tools can help simplify analysis, speed discovery, and make sense of complex metabolomics experiments.
Oral presentation
- Presenting Author: Susan S. Bird, PhD
- Session: 14. Real-Time Analysis
- Date and Time: Tuesday, June 23 1:30 p.m. - 3:00 p.m.
Software, hardware and intelligent acquisition strategies for guided unknown metabolite characterization
The field of metabolomics has advanced significantly in converting mass spectrometry signals into confident and reproducible chemical identities. However, challenges remain due to the complexity of MS data, where a single metabolite can produce multiple signals, alongside interference from contaminants and in-source fragmentation. While spectral library matching enables reliable identification of known compounds, a large portion of small molecules remains uncharacterized, requiring more intelligent acquisition and analysis strategies.
Advanced MS/MS approaches, such as the AcquireX Deep Scan workflow, improve data quality by excluding background ions and iteratively targeting relevant precursors across replicate injections. When combined with enhanced dynamic range techniques, researchers can attenuate highly abundant species and uncover lower-abundance metabolites typically obscured by ion suppression. Molecular networking further supports structural insights by linking related compounds and revealing shared substructures. In addition, Real-Time Library Search (RTLS) enables adaptive ddMSn experiments, guiding data acquisition in real time to confirm known compounds and characterize unknowns through targeted ddMS3 analysis.
Join our session to learn how the enhanced workflow generates high-confidence, defensible metabolite annotations, reduce false positives, and support alignment with community-driven small molecule identification frameworks.
