Moisture assay of an antifungal by near-infrared diffuse reflectance spectroscopy

Near-infrared (NIR) diffuse reflectance spectroscopy was employed in the method development and validation of a moisture assay for the novel antifungal caspofungin acetate. Spectra were obtained over the entire spectral region available (950-1650 nm) using an InGaAs photodiode array detector equipped with a diffuse reflectance probe. No sample pre-treatment was required and the analysis time was less than 1 min. Primary reference data were obtained using a Karl Fischer (KF) titration (coulometric, volumetric or both). The investigated range of water content was 2.6-9.9% (w/w) with a standard error of prediction (SEP) of 0.2%. The predictive capabilities of the partial least-squares (PLS) regression calibration model used in the moisture assay were verified using independent test sets. The NIR predicted values of the developed method were equivalent to the reference method sets and the prediction error was equivalent to the reference method error. These results reveal that the predictive model constructed by means of a PLS regression is valid, rugged and could be used to determine moisture levels on-line in caspofungin acetate drug substance.