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Highly sensitive instrumentation for metabolite and lipid quantitation

RECORD | Already taken place Tu, 16.9.2025
Discover SQUAD exposomics, advanced fragmentation, and optimized LC-MS workflows for metabolomics and lipidomics to achieve sensitive, robust, and reproducible results.
Go to the webinar
Thermo Fisher Scientific: ASMS 2025 Metabolomics Workshop
Thermo Fisher Scientific: ASMS 2025 Metabolomics Workshop

Explore new approaches in metabolomics applications including SQUAD (Simultaneous Quantitation and Discovery) exposomics, and alternative fragmentation methods enhancing small molecule characterization. This session delved into how these innovative techniques are improving the identification and quantification of small molecules, offering greater precision and depth in research. Gained valuable insights into how these advancements are transforming the landscape of small molecule analysis for metabolites and lipids, improving our understanding of metabolism across various scientific disciplines.

Learning points:
  • How to design end-to-end quantitative workflows for metabolites and lipids—covering sample prep, chromatographic separation to resolve isomers, acquisition setup, and calibration with internal standards.
  • Practical tactics to push sensitivity and dynamic range (reducing matrix effects, optimizing scan parameters) for confident low-abundance quantitation and reproducibility across batches.
  • Data processing and QA essentials for metabolomics/lipidomics: peak detection, normalization and batch correction, QC samples, and reporting practices that stand up to review.
Who should attend:
  • Metabolomics & Lipidomics Scientists: Researchers quantifying small molecules/lipids who need higher sensitivity, robustness, and reproducibility in targeted or untargeted assays.
  • LC–MS Method Developers/Analytical Chemists: Professionals optimizing separations and acquisition (e.g., full-scan + MS/MS, PRM/DIA) for accurate quantitation.
  • Data Analysts in Life Sciences: Teams responsible for processing large metabolomics datasets, implementing QC/normalization, and producing decision-ready reports.

If you cannot attend this webinar please register to receive a link to the On Demand version the following day. 

Presenter: Tong Shen Ph.D. (Project Scientist, West Coast Metabolomics Center, UC Davis)

Presenter: Justin Elliott (Graduate Student, Texas A&M University-Corpus Christi)

Presenter: Olivia Murtagh (Graduate Student, Department of Chemistry, University of Texas at Austin)

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LabRulez s.r.o. All rights reserved. Content available under a CC BY-SA 4.0 Attribution-ShareAlike