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Related Experiment Video

Updated: Nov 1, 2025

Large Scale Non-targeted Metabolomic Profiling of Serum by Ultra Performance Liquid Chromatography-Mass Spectrometry UPLC-MS
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Acoustic Mist Ionization Mass Spectrometry for Ultrahigh-Throughput Metabolomics Screening.

Matthew J Smith1, Delyan P Ivanov2, Ralf J M Weber1

  • 1School of Biosciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, U.K.

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Early drug safety screening is accelerated by acoustic mist ionization mass spectrometry (AMI-MS). This ultrahigh-throughput metabolomics workflow enables rapid analysis of thousands of samples, significantly reducing lead candidate failures in drug discovery.

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Area of Science:

  • Pharmacology
  • Analytical Chemistry
  • Biotechnology

Background:

  • Early integration of safety data in drug discovery minimizes costly failures.
  • Metabolomics predicts toxicity but current methods lack high sample throughput.
  • Acoustic mist ionization mass spectrometry (AMI-MS) offers rapid metabolite analysis from well plates.

Purpose of the Study:

  • To develop and validate a signal processing and data analysis workflow for high-quality AMI-MS metabolomics.
  • To demonstrate the application of this workflow for drug safety screening.
  • To achieve ultrahigh-throughput metabolomics screening for accelerated drug development.

Main Methods:

  • Adapted and optimized a direct infusion mass spectrometry workflow for AMI-MS.
  • Developed algorithms for pulsed scan data extraction, optimizing parameters for signal quality and feature detection.
  • Implemented normalization, batch correction, and cell phenotype filtering for robust data analysis.

Main Results:

  • Successfully processed AMI-MS data from metabolite standards, HepG2 cell lysates, and a toxicity study.
  • Demonstrated the workflow on a large HepG2 toxicity dataset (2772 samples, 16 drugs, 9 concentrations) in under 5 hours.
  • Identified metabolic phenotypes and metabolite changes associated with specific drug modes of action.

Conclusions:

  • The developed AMI-MS workflow enables ultrahigh-throughput metabolomics screening.
  • This approach increases sample analysis rates by approximately 100-fold.
  • Facilitates rapid drug safety assessment and reduces lead candidate attrition in drug discovery pipelines.