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Related Experiment Video

Updated: Jun 9, 2026

An Integrated Raman Spectroscopy and Mass Spectrometry Platform to Study Single-Cell Drug Uptake, Metabolism, and Effects

An Integrated Raman Spectroscopy and Mass Spectrometry Platform to Study Single-Cell Drug Uptake, Metabolism, and Effects

Published on: January 9, 2020

Surface-Enhanced Raman Spectroscopy: A Game Changer for Metabolomics Research.

Xinyuan Bi¹, Xing Yi Ling^2,3, Jian Ye^1,4,5,6

¹School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200240, P. R. China.

|June 8, 2026

Summary

This summary is machine-generated.

Surface-enhanced Raman spectroscopy (SERS) shows promise for metabolic detection, but challenges remain for true metabolomics. Advances in nanomaterial interactions and AI are paving the way for SERS to become a powerful metabolomic platform.

Keywords:

artificial intelligence biomedicine metabolomics plasmonic nanomaterials surface-enhanced Raman spectroscopy

Related Experiment Videos

Last Updated: Jun 9, 2026

An Integrated Raman Spectroscopy and Mass Spectrometry Platform to Study Single-Cell Drug Uptake, Metabolism, and Effects

An Integrated Raman Spectroscopy and Mass Spectrometry Platform to Study Single-Cell Drug Uptake, Metabolism, and Effects

Published on: January 9, 2020

Area of Science:

Analytical Chemistry
Spectroscopy
Biotechnology

Background:

Metabolomics offers systems-level biological insights but faces unmet detection demands.
Surface-enhanced Raman spectroscopy (SERS) is a developing platform for metabolic detection with limitations for comprehensive metabolomics.

Purpose of the Study:

To review fundamental principles of SERS for metabolomic detection.
To identify limitations of current SERS techniques for metabolomics.
To highlight key technical advances enabling SERS for advanced metabolomic applications.

Main Methods:

Review of fundamental principles of SERS (specificity, sensitivity, near-field compatibility, nondestructiveness).
Analysis of limitations in current SERS techniques for metabolomics.
Discussion of advancements: digital SERS, SERSome, molecule-resolvable SERSome, probe-functionalized nanomaterials, AI-assisted analysis.

Main Results:

SERS principles are outlined for metabolomic detection.
Gaps between SERS and true metabolomics are identified.
Key advances enabling targeted detection, phenotypic profiling, and emerging metabolomics are highlighted.

Conclusions:

SERS has evolved for metabolic detection, with recent advances addressing limitations.
Developments like digital SERS and AI-assisted analysis enhance SERS capabilities.
Future work aims to advance SERS into a true metabolomic platform for biological system decoding.