Moisture and drug solid-state monitoring during a continuous drying process using empirical and mass balance models.

Classically, the end point detection during fluid bed drying has been performed using indirect parameters, such as the product temperature or the humidity of the outlet drying air. This paper aims at comparing those classic methods to both in-line moisture and solid-state determination by means of Process Analytical Technology (PAT) tools (Raman and NIR spectroscopy) and a mass balance approach. The six-segmented fluid bed drying system being part of a fully continuous from-powder-to-tablet production line (ConsiGma™-25) was used for this study. A theophylline:lactose:PVP (30:67.5:2.5) blend was chosen as model formulation. For the development of the NIR-based moisture determination model, 15 calibration experiments in the fluid bed dryer were performed. Six test experiments were conducted afterwards, and the product was monitored in-line with NIR and Raman spectroscopy during drying. The results (drying endpoint and residual moisture) obtained via the NIR-based moisture determination model, the classical approach by means of indirect parameters and the mass balance model were then compared. Our conclusion is that the PAT-based method is most suited for use in a production set-up. Secondly, the different size fractions of the dried granules obtained during different experiments (fines, yield and oversized granules) were compared separately, revealing differences in both solid state of theophylline and moisture content between the different granule size fractions.

Real-time assessment of critical quality attributes of a continuous granulation process.

There exists the intention to shift pharmaceutical manufacturing of solid dosage forms from traditional batch production towards continuous production. The currently applied conventional quality control systems, based on sampling and time-consuming off-line analyses in analytical laboratories, would annul the advantages of continuous processing. It is clear that real-time quality assessment and control is indispensable for continuous production. This manuscript evaluates strengths and weaknesses of several complementary Process Analytical Technology (PAT) tools implemented in a continuous wet granulation process, which is part of a fully continuous from powder-to-tablet production line. The use of Raman and NIR-spectroscopy and a particle size distribution analyzer is evaluated for the real-time monitoring of critical parameters during the continuous wet agglomeration of an anhydrous theophylline- lactose blend. The solid state characteristics and particle size of the granules were analyzed in real-time and the critical process parameters influencing these granule characteristics were identified. The temperature of the granulator barrel, the amount of granulation liquid added and, to a lesser extent, the powder feed rate were the parameters influencing the solid state of the active pharmaceutical ingredient (API). A higher barrel temperature and a higher powder feed rate, resulted in larger granules.

Rapid solid-state analysis of freeze-dried protein formulations using NIR and Raman spectroscopies.

Noninvasive near-infrared (NIR) and Raman spectroscopies were applied to provide a fast and efficient insight into the formation of different mannitol solid forms occurring in freeze-dried formulations. Multivariate data analysis clearly showed the formation of δ-mannitol in the presence of protein, whereas ß-mannitol was observed in the absence of protein.The multivariate analysis of the NIR spectra also gave an indication for the formation of mannitol hemihydrate in the absence of protein. Spectroscopic techniques in combination with multivariate analysis can be applied for fast screening and identification of excipient solid-state properties in pharmaceutical formulations.

Towards a robust water content determination of freeze-dried samples by near-infrared spectroscopy.

The possibility for determination of the water content in pharmaceutical samples by near-infrared (NIR) spectroscopy has been more widely investigated in the past few years. However, many studies claim that changes in sample composition will require the establishment of a new method. The aim of this study was several fold: firstly to investigate validation aspects of water content determination in samples with varying composition and furthermore to see if a model based solely on freeze-dried mannitol-sucrose mixtures can be established that will be able to predict water contents for samples containing proteins, excipients or having a lower density of freeze-dried solids. Samples were measured by NIR, standard normal variate (SNV) corrected and the obtained spectra were compared with the results from a conventional Karl-Fischer titration by means of multivariate analysis, namely principal component analysis (PCA) and partial least square regression (PLS). For the overall sample set, a highly linear correlation between the NIR and the Karl-Fischer method with a slope of 1.00, an R(2) value of 0.98 and a root mean square error of cross-validation (RMSECV) of 0.15% were found. In a second step samples solely consisting of mannitol and sucrose mixtures were used to build a calibration set, which resulted in a RMSECV of 0.16%. The prediction of the remaining samples, which included protein or excipient containing samples, as well as lower density samples, resulted in a root mean square error of prediction (RMSEP) of 0.19%. Thus the present study demonstrated, that a general model for the determination of the water content by NIR could be established, within the limits investigated.