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Updated: May 26, 2026

Visualization of Metabolites Identified in the Spatial Metabolome of Traditional Chinese Medicine Using DESI-MSI
Published on: December 16, 2022
Insights From Spatiality: Accelerating Pharmaceutical Research Using Mass Spectrometry Imaging
Yuchen Zou1, Zhiye Yan1, Weiwei Tang1
1State Key Laboratory of Natural Medicines and School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing, China.
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Mass spectrometry imaging (MSI) has emerged as a transformative technology in pharmaceutical research, offering unprecedented capabilities to visualize drug distribution, metabolism, and target engagement in biological tissues. By combining the molecular specificity of mass spectrometry with spatial imaging resolution, this label-free approach enables simultaneous mapping of drugs, metabolites, and endogenous molecules across tissue sections, providing comprehensive insights into drug absorption, distribution, metabolism, excretion, and toxicity properties. Recent technical advances have dramatically enhanced MSI capabilities, achieving spatial resolutions down to the cellular level. The integration of tandem mass spectrometry, ion mobility separation, and dedicated data analysis tools powered by artificial intelligence has further expanded the analytical power of MSI, enabling robust molecular identification and pattern recognition in complex biological matrices. MSI applications span critical areas of drug development, from characterizing blood-brain barrier permeability and CNS drug distribution to mapping tumor microenvironment heterogeneity and evaluating anticancer drug penetration. This technology has proven invaluable for assessing drug disposition in the heart, liver, kidney, lung, as well as the gastrointestinal tract and skin. As drug research increasingly embraces multimodal approaches and single-cell analysis, MSI continues to evolve as an indispensable tool for understanding drug behavior in complex biological systems, ultimately accelerating drug development and reducing clinical failures.
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