Top 10 Most Influential Articles on FT-IR Spectroscopy in Biomedical Applications (2021–2025)

Abstract

Fourier Transform Infrared (FT-IR) spectroscopy provides rapid, label-free molecular characterization of biological systems through vibrational fingerprints of proteins, lipids, nucleic acids, and metabolites. Recent years have seen a sharp increase in biomedical FT-IR publications, particularly those integrating multivariate analysis and machine learning for disease detection and monitoring. This feature article reviews and synthesizes the ten most influential FT-IR biomedical papers published between 2022 and early 2025. Together, these studies demonstrate FT-IR’s expanding role in tissue and cellular analysis, biofluid diagnostics, live-cell metabolism, immunology, oncology, exercise physiology, and forensic medicine. Trends, analytical challenges, and translational opportunities are discussed.

Introduction

Fourier Transform Infrared (FT-IR) spectroscopy occupies a unique position in biomedical analytics. Unlike targeted biochemical assays, FT-IR interrogates global molecular composition, enabling simultaneous observation of multiple biomolecular classes. Historically constrained by water absorption and limited clinical acceptance, FT-IR has re-emerged due to attenuated total reflectance (ATR) sampling, improved detectors, and sophisticated chemometric modeling.

The past two years, in particular, have produced a cluster of highly cited and conceptually influential publications that demonstrate FT-IR’s maturity as a biomedical tool. These works collectively establish FT-IR as not merely complementary, but in some contexts competitive with conventional diagnostic approaches. The following sections examine the ten most influential contributions shaping this rapidly advancing field.

Top 10 Influential Contributions

1. Comprehensive FT-IR Analysis of Tissues, Cells, and Hair

Al-Kelani and Buthelezi published a landmark review synthesizing FT-IR applications across tissues, cultured cells, and hair samples, with emphasis on dermatological and systemic disease investigations (1). This article is influential because it consolidates disparate biological matrices under a unified spectroscopic framework.

The authors emphasize FT-IR’s ability to resolve molecular fingerprints associated with keratin, lipids, and nucleic acids, demonstrating sensitivity to disease-induced biochemical changes. Hair spectroscopy is particularly noteworthy, as it integrates long-term metabolic information and offers forensic and diagnostic potential.

2. Vibrational Spectroscopy in Clinical Immunology

Callery and Rowbottom provide a rigorous review of vibrational spectroscopy—primarily FT-IR—combined with multivariate analysis in clinical immunology laboratories (2). The paper is influential for articulating analytical requirements for diagnostic adoption, including reproducibility, spectral preprocessing, and validation strategies.

Clinical examples include autoimmune diseases, neurodegenerative disorders, diabetes, and infectious diseases. The review establishes FT-IR as a realistic candidate for high-throughput immunological screening when paired with robust chemometrics.

3. Live-Cell ATR-FTIR for Glucose Metabolism Studies

Poonprasartporn and Chan demonstrated one of the clearest examples of live-cell FT-IR spectroscopy applied to metabolic research (3). Using ATR-FTIR, they monitored glucose metabolism in HepG2 cells under normal and hyperglycemic conditions.

This study is influential because it shows FT-IR can capture dynamic biochemical changes in living cells, including phosphorylated proteins, glycogen, lipids, and ATP-related bands—without labels or destructive preparation.

4. FT-IR Biofluid Analysis for Clinical Screening

Carvalho de Silva and co-workers critically assessed FT-IR spectroscopy for clinical biofluid analysis, focusing on blood, urine, and saliva (4). The paper is influential because it addresses the translation gap between laboratory feasibility and clinical deployment.

Beyond spectral interpretation, the authors discuss instrumentation portability, regulatory considerations, and clinician engagement—issues often neglected in spectroscopy-driven studies.

5. Quantitative FT-IR in Biomedical and Clinical Chemistry

Fahelelbom et al. reviewed quantitative FT-IR methods in pharmaceutical and biomedical analysis, positioning FT-IR as an alternative to chromatographic techniques in selected applications (5). The influence of this work lies in its emphasis on quantitation, not merely classification.

The review highlights FT-IR’s capability for concentration determination in complex biological systems, including cancer diagnostics, with appropriate calibration and validation.

6. Machine Learning-Assisted FT-IR for Blood Serum Diagnostics

Guleken and colleagues applied FT-IR spectroscopy combined with principal components analysis (PCA) and support vector machines (SVM) to dried blood serum from patients with primary myelofibrosis (6). The study demonstrated high classification accuracy and identified disease-specific biochemical alterations.

This paper is influential because it exemplifies clinically relevant ML integration, moving FT-IR beyond exploratory multivariate analysis toward predictive modeling.

7. Saliva-Based FT-IR Diagnosis of Oral Cancer

Falamas et al. explored FT-IR and micro-Raman spectroscopy of saliva for noninvasive diagnosis of oral and oropharyngeal cancer (7). The study identified distinct vibrational biomarkers, including thiocyanate and phosphodiester bands.

Its influence stems from demonstrating that saliva-based FT-IR diagnostics can differentiate cancer patients from controls rapidly and noninvasively.

8. Machine Learning Methods Applied to FT-IR Blood Cell Analysis

Fadlelmoula et al. reviewed machine learning techniques applied to FT-IR spectra of human blood cells (8). Surveying nearly 40 studies, the review documents an explosion of ML-FT-IR research between 2019 and 2023.

This work is influential for framing methodological best practices, identifying pitfalls such as overfitting, and emphasizing the need for standardized datasets.

9. FT-IR Spectroscopy in Exercise and Physical Activity Monitoring

Valente and co-workers published the first systematic review of FT-IR spectroscopy applied to exercise and physical activity (9). The review demonstrates FT-IR’s ability to monitor biochemical responses related to metabolism, fatigue, and cardiovascular stress using urine, saliva, and blood.

This article broadens FT-IR’s biomedical relevance beyond disease diagnostics into sports medicine and physiological monitoring.

10. FT-IR and Vibrational Spectroscopy of Urine Samples

Vigo et al. reviewed vibrational spectroscopy—particularly FT-IR—for urine analysis as a noninvasive diagnostic tool (10). Applications range from drug detection to disease biomarkers and forensic identification.

The paper’s influence lies in establishing urine FT-IR spectroscopy as a mature analytical approach with expanding medical relevance.

Final Summary

Together, these ten publications illustrate a decisive shift in FT-IR biomedical spectroscopy. The technique has moved from proof-of-concept studies toward validated analytical platforms capable of addressing real clinical and physiological questions. Key drivers include ATR sampling, biofluid accessibility, quantitative modeling, and machine-learning integration.

Conclusion

FT-IR spectroscopy is now firmly positioned as a versatile and powerful biomedical analytical technique. The most influential recent studies demonstrate its applicability across tissues, cells, hair, blood, saliva, urine, and even exercise physiology. Future progress will depend on standardization, external validation, and closer collaboration between spectroscopists, clinicians, and data scientists. If these challenges are met, FT-IR is poised to become a routine component of biomedical diagnostics and monitoring.

References

(1) Al-Kelani, M.; Buthelezi, N. Advancements in Medical Research: Exploring Fourier Transform Infrared (FTIR) Spectroscopy for Tissue, Cell, and Hair Sample Analysis. Skin Res. Technol. 2024, 30, e13733. DOI: 10.1111/srt.13733.

(2) Callery, E. L.; Rowbottom, A. W. Vibrational Spectroscopy and Multivariate Analysis Techniques in the Clinical Immunology Laboratory: A Review of Current Applications and Requirements for Diagnostic Use. Appl. Spectrosc. Rev. 2022, 57, 1–29. DOI: 10.1080/05704928.2021.1958337.

(3) Poonprasartporn, A.; Chan, K. L. A. Live-Cell ATR-FTIR Spectroscopy as a Novel Bioanalytical Tool for Cell Glucose Metabolism Research. Biochim. Biophys. Acta Mol. Cell Res. 2021, 1868, 119104. DOI: 10.1016/j.bbamcr.2021.119024

(4) Carvalho de Silva, L. F.; de Lima Morais, T. M.; Nogueira, M. S. Providing Potential Solutions by Using FT-IR Spectroscopy for Biofluid Analysis: Clinical Impact of Optical Screening and Diagnostic Tests. Photodiagn. Photodyn. Ther. 2023, 44, 103753. DOI: 10.1016/j.pdpdt.2023.103753.

(5) Fahelelbom, K. M.; Saleh, A.; Al-Tabakha, M. M.; Ashames, A. A. Recent Applications of Quantitative Analytical FTIR Spectroscopy in Pharmaceutical, Biomedical, and Clinical Fields: A Brief Review. Rev. Anal. Chem. 2022, 41, 21–33. DOI: 10.1515/revac-2022-0030.

(6) Guleken, Z.; Ceylan, Z.; Aday, A.; Bayrak, A. G.; Yönal Hindilerden, İ.; Nalçacı, M.; Jakubczyk, P.; Depciuch, J. Application of Fourier Transform InfraRed Spectroscopy of Machine Learning with Support Vector Machine and Principal Components Analysis to Detect Biochemical Changes in Dried Serum of Patients with Primary Myelofibrosis. Biochim. Biophys. Acta Gen. Subj. 2023, 1867, 130438. DOI: 10.1016/j.bbagen.2023.130438.

(7) Falamas, A.; Faur, C. I.; Ciupe, S.; Chirila, M.; Rotaru, H.; et al. Rapid and Noninvasive Diagnosis of Oral and Oropharyngeal Cancer Based on Micro-Raman and FT-IR Spectra of Saliva. Spectrochim. Acta A 2021, 252, 119477. DOI: 10.1016/j.saa.2021.119477

(8) Fadlelmoula, A.; Catarino, S. O.; Minas, G.; Carvalho, V. A Review of Machine Learning Methods Recently Applied to FTIR Spectroscopy Data for the Analysis of Human Blood Cells. Micromachines 2023, 14, 1145. DOI: 10.3390/mi14061145

(9) Valente, P. A.; Mota, S. I.; Teixeira, A.; Ferreiro, E.; Sarmento, H. Fourier Transform Infrared (FTIR) Spectroscopy as a Tool to Characterize Exercise and Physical Activity: A Systematic Review. Sports Med. 2025, 55, 459–472. DOI: 10.1007/s40279-024-02139-5

(10) Vigo, F.; Tozzi, A.; Disler, M.; Gisi, A.; Kavvadias, V. Vibrational Spectroscopy in Urine Samples as a Medical Tool: Review and Overview on the Current State-of-the-Art. Diagnostics 2023, 13, 27. DOI: 10.3390/diagnostics13010027