Utilization of laser headspace and near-infrared (NIR) methods provides rapid and non-destructive approaches for moisture detection of lyophilized drug products to facilitate lyophilization formulation characterization and process development. In the present study, the NIR method was developed based on a partial least square regression (PLSR) model calibrated and validated with Karl Fisher (KF) data, whereas the laser headspace method was developed with aid of dynamic vapor sorption (DVS) method so that the water vapor pressure measured from the headspace of a lyophilized drug product vial can be converted directly to water content value through the water vapor sorption isotherm of the lyophilized drug product bypassing KF calibration. The water contents of lyophilized samples obtained from both methods agreed well with KF data, with a root mean squared error of prediction (RMSEP) of less than 0.15%. The pros and cons of NIR and laser headspace method were evaluated. The results suggest that traditional off-line KF method can be potentially replaced by at-line laser headspace method combined with water sorption isotherm data from DVS. Further studies may be needed to evaluate the quantitation limit and generality of this method to a variety of lyophilized formulations.
Keywords: Laser headspace; Lyophilization; Moisture detection; NIR.
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