The determination of plasma voriconazole concentration by surface-enhanced Raman spectroscopy combining chemometrics.

In this study, a simple detection method was constructed using gold nanoparticles as a substrate in surface-enhanced Raman scattering that combined chemometrics to measure plasma voriconazole concentration. In this application, an adaptive, iteratively reweighted, penalized least squares (air-PLS) method was utilized to deduct matrix background and correct baseline spectral drift. A moving window partial least squares (MWPLS) method was used to select the optimal wavelength combination to construct a concentration prediction model. Evaluation of the results demonstrated that the final model had an excellent capability for prediction of plasma voriconazole concentration, applicable over the concentration range 3 × 10−3–200 μg/mL with a correlation coefficient of above 0.99. In conclusion, using surface enhanced Raman spectroscopy with chemometrics, we propose a novel and efficient approach that plasma voriconazole concentration can be measured in tens of seconds with a simple pretreatment. • We built a simple quantification of VOR plasma concentration by SERS combining chemometrics. • The concentration prediction model was constructed by AIR-PLS and MWPLS methods. • The model is applicable in the VOR concentration range of 3 × 10−3–200 μg/mL by the correlation coefficient above 0.99. • The method just needs tens of seconds with simple pretreatments to detect VOR plasma concentration. [ABSTRACT FROM AUTHOR]