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August 17, 2025Natural Product Communications22 citationsOpen Access

Metabolomics-Driven Standardization of Herbal Medicine: Advances, Applications, and Sustainability Considerations

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EAEsther Ugo AlumVMV ManjulaDUDaniel Ejim Uti

Key Points

  • Metabolomics enables effective identification of bioactive compounds for quality assurance in herbal medicine, transforming traditional practices.
  • Advanced analytical tools like LC-MS and GC-MS ensure high-detail metabolic profiling, promoting therapeutic consistency and quality.
  • Integration with AI and machine learning facilitates automated metabolite identification, enhancing the rapid assessment of herbal products.
  • This review emphasizes the need for interdisciplinary collaboration to align regulatory efforts with evidence-based standards for herbal formulations.

Abstract

Standardizing traditional herbal formulations poses significant challenges due to inherent variability in plant sources, environmental conditions, and processing methods. This narrative review explores how metabolomics a powerful high-throughput analytical approach for comprehensive chemical profiling addresses these issues by enabling the identification and quantification of bioactive compounds in complex herbal mixtures. Advanced analytical tools such as nuclear magnetic resonance (NMR), liquid chromatography–mass spectrometry (LC-MS), and gas chromatography–mass spectrometry (GC-MS) provide detailed metabolic fingerprints that underpin quality control and therapeutic consistency. Emerging techniques including desorption electrospray ionization–mass spectrometry (DESI-MS), direct analysis in real-time mass spectrometry (DART-MS), single-cell metabolomics, and stable isotope ratio analysis (SIRA) enhance spatial and geographical specificity, offering rapid and minimally invasive profiling capabilities. Integration of metabolomics with chemometric tools such as principal component analysis (PCA) and partial least squares–discriminant analysis (PLS-DA), facilitates authentication and batch-to-batch consistency. Furthermore, artificial intelligence (AI) and machine learning (ML) algorithms are increasingly employed to automate metabolite identification, predict pharmacological properties, and accelerate biomarker discovery. These advances collectively support evidence-based standardization and sustainability of herbal medicines, contributing to global healthcare integration. Key outcomes of this review include: identification of metabolomics as a cornerstone for quality assurance and authenticity of herbal products, evaluation of emerging analytical platforms for improving formulation reproducibility, and recommendations for interdisciplinary collaboration and regulatory alignment. Literature included in this study was sourced from peer-reviewed articles published over the past decade in databases such as PubMed, Scopus, and Web of Science. Overall, the review underscores the pivotal role of metabolomics in transforming traditional herbal practices into standardized, scalable, and personalized therapeutic interventions.

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Cite This Study

Alum et al. (2025) studied this question.

synapsesocial.com/papers/68a36a3f0a429f797332ea1fhttps://doi.org/10.1177/1934578x251367650
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