Surface-Enhanced Raman Spectroscopy for Quantitative Analysis of Anesthetic Agents: Toward Personalized Drug Monitoring in Anesthesia

Accurate and rapid identification of anesthetic drug levels in patients for tailored drug administration remains a critical challenge in clinical surgery. This study presents a novel method utilizing surface-enhanced Raman spectroscopy (SERS) for both the qualitative and quantitative analysis of anesthetic drugs. Employing methanol enhances the substrate's resistance to biomolecular interference, improving drug solubility. The resulting uniformly mixed microextraction system promotes specific drug recognition by silver nanoparticles, amplifying the characteristic Raman signals. This technique was used to obtain Raman fingerprint profiles of 10 anesthetic drugs and to accurately identify each drug molecule using the dimensionality reduction technique. The detection limit of fentanyl among opioids was 50 ng mL–1, while the detection thresholds of tramadol and dizocin were both 50 pg mL–1, which proved the method's high sensitivity. Application of the technique to clinical blood samples from eight patients and a healthy volunteer shows consistent results comparable to ultra-high performance liquid chromatography–mass spectrometry/mass spectrometry (UHPLC-MS/MS). Notably, the SERS approach identifies individual drug peaks, even in the presence of multiple agents. Moreover, the adaptability of SERS allows for real-time monitoring, offering opportunities for personalized anesthetic management based on patient-specific requirements. These findings highlight the potential of this assay for therapeutic drug monitoring (TDM) in anesthesia, promising improved patient care, and optimized drug dosing strategies.