Top 10 Most Influential Articles on Raman Spectroscopy in Biomedical Applications (2021–2025)

Abstract

Raman spectroscopy has matured into a versatile analytical platform for biomedical applications due to its non-invasive nature, rich molecular specificity, and compatibility with advanced data analytics. Herein, we critically summarize ten leading review publications (2021–2025) that explore the breadth of Raman methodologies—standard Raman, SERS, near-infrared (NIR) SERS probes, coherent Raman imaging, and hybrid optical systems—in biological and medical contexts. Key domains include clinical diagnostics, drug distribution imaging, chemical biology tagging strategies, and deep tissue sensing. Collectively, these works illuminate the transformative potential of Raman technologies in clinical translation and precision medicine.

Introduction

Raman spectroscopy, based on inelastic light scattering, reveals the vibrational “fingerprints” of molecules, making it inherently suited for biomolecular identification and structural analysis. Its biomedical utility arises from the ability to detect biochemical changes without labels, enabling both fundamental research and translational diagnostic applications. Emerging variants—SERS, CRS (such as stimulated Raman scattering and coherent anti-Stokes Raman scattering), and multimodal optical spectroscopies—expand sensitivity and functional scope, addressing challenges like weak native Raman signals and in vivo access. This article integrates insights from 10 authoritative reviews, illustrating progress and convergence across disciplines.

Top 10 Influential Contributions

1. Raman Spectroscopy: Principles and Biomedical Rationale

Raman spectroscopy’s core advantage is chemical fingerprinting based on molecular vibrational modes, requiring minimal sample preparation and no external labeling. Its utility in biomedical systems stems from sensitivity to biochemical changes associated with disease states and phenotypic transformations, supported by advanced multivariate and machine learning analysis frameworks that enhance diagnostic reliability (1).

This paper is influential because it establishes the fundamental physical and biochemical rationale for using Raman spectroscopy as a label-free molecular fingerprinting tool in biomedical diagnostics.

2. Broad Review of Biomedical Applications

The comprehensive review by Qi et al. details Raman’s application across a spectrum of clinical contexts—cancers, infectious diseases, and neurodegeneration—with specific emphasis on state-of-the-art implementations such as SERS, resonance Raman, and tip-enhanced Raman techniques. These approaches improve signal specificity and expand analytical depth in tissue and biofluid diagnostics (2).

This review is influential for synthesizing diverse clinical Raman applications into a unified framework that demonstrates the technique’s breadth, maturity, and translational potential across major disease classes.

3. Classical and Multivariate Analysis in Clinical Contexts

Siraj, Bwambok, Brady, and colleagues provide a detailed examination of Raman combined with multivariate regression analyses, demonstrating how chemometric models enable pattern recognition and classification in complex biological samples. They underscore the criticality of robust models for clinical translation, especially for disease classification and spectral feature extraction (3).

This work is influential because it clearly demonstrates how chemometrics and multivariate modeling are essential for extracting clinically meaningful information from complex Raman spectra.

4. Surface-Enhanced Raman Spectroscopy (SERS) for Biomedical Use

Lin et al. (2025) highlight advancements in SERS substrates, including hotspot engineering, nanotag innovations, and improved spectral analysis methods, which have catalyzed the use of SERS for nucleic acid detection, protein profiling, metabolomics, and single-cell monitoring. The review also addresses signal processing and emerging wearable and deep-tissue platforms (4).

This paper is influential for defining modern SERS substrate engineering and analytical strategies that enabled ultrasensitive biomolecular detection and expanded Raman into practical biomedical platforms.

5. Near-Infrared SERS Probes for Biosensing and Bioimaging

Chen et al. provide a detailed examination of SERS probes optimized for NIR biological windows, enabling deeper tissue penetration with minimal background interference. These NIR SERS strategies have been applied to sensitive pathogen detection, intracellular biomolecule imaging, and guided surgical diagnostics (5).

This study is influential because it established near-infrared SERS probes as a viable solution for deep-tissue biosensing and bioimaging with reduced fluorescence interference.

6. Raman in Chemical Biology: Tags and Probes for Functional Imaging

The seminal perspective by Dodo, Fujita, and Sodeoka (2022) describes advances in Raman “tags”—such as alkyne-based labels—that markedly increase imaging contrast in chemical biology. These next-generation Raman reporters enable label-free and tagged imaging of cellular components with high specificity, circumventing spectral crowding limitations of traditional fluorescent probes (6).

This perspective is influential for introducing Raman tags as a transformative chemical biology strategy that overcomes spectral congestion and enables highly specific functional imaging.

7. Rastering Drug Distribution: Coherent Raman Microscopy

Dunnington et al. review the rapidly growing use of Raman imaging—particularly stimulated Raman scattering (SRS) and coherent anti-Stokes Raman scattering (CARS)—for quantifying drug distribution and cellular response during drug discovery. These coherent techniques provide high spatial and chemical resolution, essential for real-time mapping of pharmacodynamics (7).

This review is influential because it positioned coherent Raman microscopy as a quantitative, real-time tool for mapping drug distribution and cellular response in pharmaceutical research.

8. Multimodal Raman Systems

Integrated optical platforms combining Raman with other modalities (for example, optical coherence tomography) boost diagnostic performance by leveraging complementary contrast mechanisms. Schie, Stiebing, and Popp illustrate how multimodal combinations help overcome Raman’s limited depth penetration and throughput constraints, particularly in diagnostic applications across oncology and cardiovascular disease (8).

This work is influential for demonstrating that multimodal optical systems can overcome intrinsic Raman limitations by combining molecular specificity with structural and functional imaging.

9. Raman in Diagnostic Medicine

Clinical applications reviews emphasize Raman’s role in rapid, non-destructive disease detection. Paraskevaidi et al. focus on cancer and infectious disease diagnostics, highlighting how vibrational spectra from biofluids and tissues can reflect pathological changes, suggesting potential for point-of-care applications and cost-efficient testing (9).

This review is influential because it consolidates clinical evidence showing Raman spectroscopy’s feasibility for rapid, non-destructive disease diagnosis in real-world medical settings.

10. Future Outlook: Machine Learning and Clinical Translation

Across several reviews, the integration of machine learning with Raman spectral data emerges as a key trend. Algorithms such as convolutional neural networks and multivariate classification models significantly enhance disease discrimination accuracy, mitigate data complexity, and ultimately accelerate clinical adoption (10).

This contribution is influential because it identifies machine learning as the critical enabler for scaling Raman spectroscopy from experimental studies to reliable clinical decision-support systems.

Final Summary

The past few years have witnessed Raman spectroscopy advanced from a primarily research instrument into an increasingly clinical and translational tool. Enhancements in sensitivity (SERS, NIR probes), imaging speed (CRS techniques), chemical specificity (Raman tags), and analytical sophistication (multivariate/machine learning models) collectively broaden its utility. These developments underscore Raman’s potential to impact diagnostics, therapeutic monitoring, and drug development.

Conclusions

Raman spectroscopy’s expanding biomedical portfolio confirms its value in both foundational and translational research. Continued progress in probe design, computational analytics, and hybrid imaging will be essential for routine clinical integration. Future efforts should prioritize standardized clinical trials and multicenter validation to fully realize Raman’s promise in precision medicine.

References

(1) Qi, Y.; Chen, E. X.; Hu, D.; Yang, Y.; Wu, Z.; Zheng, M.; Sadi, M. A.; Jiang, Y.; Zhang, K.; Chen, Z.; Chen, Y. P. Applications of Raman Spectroscopy in Clinical Medicine. Food Frontiers 2024, 5 (2), 392–419. DOI: 10.1002/fft2.335

(2) Siraj, N.; Bwambok, D. K.; Brady, P. N.; Taylor, M.; Baker, G. A. Raman Spectroscopy and Multivariate Regression Analysis in Biomedical Research, Medical Diagnosis, and Clinical Analysis. Appl. Spectrosc. Rev. 2021, 56, 615–672.DOI: 10.1080/05704928.2021.1913744

(3) Lin, L.; Alvarez-Puebla, R. A.; Liz-Marzán, L. M. Surface-Enhanced Raman Spectroscopy for Biomedical Applications: Recent Advances and Future Challenges. ACS Appl. Mater. Interfaces 2025, 17, 16287–16379. DOI: 10.1021/acsami.4c17502

(4) Chen, H.; Cheng, Z.; Zhou, X.; Wang, R.; Yu, F. Emergence of Surface-Enhanced Raman Scattering Probes in Near-Infrared Windows for Biosensing and Bioimaging. Anal. Chem. 2022, 94, 143–164. DOI: 10.1021/acs.analchem.1c03646

(5) Dodo, K.; Fujita, K.; Sodeoka, M. Raman Spectroscopy for Chemical Biology Research. J. Am. Chem. Soc. 2022, 144, 19651–19667. DOI: 10.1021/jacs.2c05359

(6) Dunnington, E. L.; Wong, B. S.; Fu, D. Innovative Approaches for Drug Discovery: Quantifying Drug Distribution and Response with Raman Imaging. Anal. Chem. 2024, 96. 2024, 96, 7926–7944. DOI: 10.1021/acs.analchem.4c01413

(7) Schie, I. W.; Stiebing, C.; Popp, J. Looking for a Perfect Match: Multimodal Combinations of Raman Spectroscopy for Biomedical Applications. J. Biomed. Opt. 2021, 26 (8), 080601. DOI: 10.1117/1.JBO.26.8.080601

(8) Paraskevaidi, M.; Baker, M. J.; Butler, H. J.; et al. Clinical Applications of Infrared and Raman Spectroscopy in the Fields of Cancer and Infectious Diseases. Appl. Spectrosc. Rev. 2021, 56 (8–10), 804–868. DOI: 10.1080/05704928.2021.1946076

(9) Allakhverdiev, E. S.; Khabatova, V. V.; Kossalbayev, B. D.; Ivanova, E. V.; Zharmukhamedov, S. K. Raman Spectroscopy and Its Modifications Applied to Biological and Medical Research. Cells 2022, 11 (3), 386. DOI: 10.3390/cells11030386

(10) Lin, C.; Li, Y.; Peng, Y.; Zhao, S.; Xu, M.; Zhang, L. Recent Development of Surface-Enhanced Raman Scattering for Biosensing. J Nanobiotechnol 2023, 21, 149. DOI: 10.1186/s12951-023-01890-7