Lecture
Surface-enhanced Raman spectroscopy (SERS) sensing in complex biomatrices - drug monitoring and biomarker detection
- at -
- ICM Saal 4b
- Type: Lecture
Lecture description
Dana Cialla-May, Jena/Germany, Jürgen Popp, Jena/Germany
Surface-enhanced Raman spectroscopy (SERS) has emerged as a powerful analytical tool for biomedical and bioanalytical applications due to its exceptional molecular specificity and ultra-trace sensitivity. [1] Its practical deployment in clinical settings,
however, is often hindered by substrate instability, oxidation, and limited reproducibility, particularly when analyzing complex biological matrices such as blood-based materials. Within this contribution, SERS-based clinically relevant detection strategies for drugs and biomarkers are addressed.
We report on silver dendritic nanostructures that exhibit outstanding SERS sensitivity and long-term stability as robust platform enabling therapeutic drug monitoring in blood plasma matrices. [2] Here, sulfate ions act as growth-directing and mild capping agents, resulting in passivated metallic surfaces with enhanced resistance to oxidation and signal degradation, as confirmed by SEM, TEM, XRD, and XPS analyses. These substrates enable sub-femtomolar detection of 4-mercaptobenzoic acid and maintain consistent SERS performance for more than seven months. The sensitive detection of clinically relevant drugs, i.e. ceftriaxone, 6-thioguanine, methotrexate, erlotinib, doxorubicin, and moxifloxacin in human blood plasma, following methanol-based
protein precipitation, achieving detection limits in the sub-nanomolar to therapeutically relevant concentration ranges, is demonstrated.
Beyond drug monitoring, we explored SERS to non-invasive biomarker detection in human cerumen samples. A multimodal vibrational spectroscopic analysis of cerumen using Raman, SERS, CARS, SRS, and optical photothermal infrared spectroscopy
reveals lipids and proteins as its dominant components and highlights its diagnostic potential. [3] By coupling SERS measurements of cerumen with machine-learning analysis (PCA-LDA), we established a rapid screening method for head and neck cancer, achieving a classification accuracy of 87.2%. [4]
Acknowledgement: The Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) supported this work under grant 465289819.
Literature:
[1] D. Cialla-May et al., Chem. Soc. Rev., 53, 8957-8979 (2024).
[2] A. Dwivedi et al., Advanced Science, accepted.
[3] E. Farnesi, M. Calvarese et al., Analyst, 149, 5381-5393 (2024).
[4] E. Farnesi et al., npj Biosensing, 2, 14 (2025).
Surface-enhanced Raman spectroscopy (SERS) has emerged as a powerful analytical tool for biomedical and bioanalytical applications due to its exceptional molecular specificity and ultra-trace sensitivity. [1] Its practical deployment in clinical settings,
however, is often hindered by substrate instability, oxidation, and limited reproducibility, particularly when analyzing complex biological matrices such as blood-based materials. Within this contribution, SERS-based clinically relevant detection strategies for drugs and biomarkers are addressed.
We report on silver dendritic nanostructures that exhibit outstanding SERS sensitivity and long-term stability as robust platform enabling therapeutic drug monitoring in blood plasma matrices. [2] Here, sulfate ions act as growth-directing and mild capping agents, resulting in passivated metallic surfaces with enhanced resistance to oxidation and signal degradation, as confirmed by SEM, TEM, XRD, and XPS analyses. These substrates enable sub-femtomolar detection of 4-mercaptobenzoic acid and maintain consistent SERS performance for more than seven months. The sensitive detection of clinically relevant drugs, i.e. ceftriaxone, 6-thioguanine, methotrexate, erlotinib, doxorubicin, and moxifloxacin in human blood plasma, following methanol-based
protein precipitation, achieving detection limits in the sub-nanomolar to therapeutically relevant concentration ranges, is demonstrated.
Beyond drug monitoring, we explored SERS to non-invasive biomarker detection in human cerumen samples. A multimodal vibrational spectroscopic analysis of cerumen using Raman, SERS, CARS, SRS, and optical photothermal infrared spectroscopy
reveals lipids and proteins as its dominant components and highlights its diagnostic potential. [3] By coupling SERS measurements of cerumen with machine-learning analysis (PCA-LDA), we established a rapid screening method for head and neck cancer, achieving a classification accuracy of 87.2%. [4]
Acknowledgement: The Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) supported this work under grant 465289819.
Literature:
[1] D. Cialla-May et al., Chem. Soc. Rev., 53, 8957-8979 (2024).
[2] A. Dwivedi et al., Advanced Science, accepted.
[3] E. Farnesi, M. Calvarese et al., Analyst, 149, 5381-5393 (2024).
[4] E. Farnesi et al., npj Biosensing, 2, 14 (2025).
