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Background: Pharmaceutical manufacturing is moving towards real-time release of the products. This objective can only be achieved by clearly understanding the process and by implementing suitable technologies for manufacturing and for process control. Near-infrared (NIR) spectroscopy is one technology that has attracted lot of attention from the pharmaceutical industry since it can analyze bulk solids without any pretreatment, therefore reducing or eliminating wet chemistry analysis. NIR spectroscopy is a powerful tool for the monitoring unit operations were bulk material is involved i.e. blending of powders. Blending of powders is a complex and poorly understood unit operation. In the pharmaceutical industry blending has been performed batchwise and controlled by thief sampling. Thief sampling is an invasive process which is tedious and tends to introduce bias; therefore an alternative sampling method was highly needed. Here is where NIR found a perfect match with blend uniformity monitoring, thus NIR implementation offers several advantages: thief sampling is avoided, the process is continuously monitored, detection of blend-end point, and fast identification of process deviations. NIR spectral data need to be correlated with the parameter of interest (physical or chemical). These computations are done by multivariate data analysis (MVDA). MVDA and NIR are a powerful combination for in-process control and their use has been promoted by the health authorities through the Process Analytical technology (PAT) initiative by the FDA. Purpose: This thesis is focused on the study of powder blending, which is an essential unit operation for the manufacture of solid dosage forms. The aim was to develop two quantitative methods for the monitoring of the active ingredient concentration. One method was developed for blend uniformity monitoring of a batch mixing process, and a second method for a continuous mixing process. This study also tackles the relevance of the physical presentation of the powder on the final blend quality, by studying the influence of the particle size and the effect of the previous manufacturing steps on the NIR spectral data. Methods: Particle size was studied by NIR in diffuse reflectance mode, using Kubelka-Munk function and the transformation of reflectance of absorbance values, in order to focus the analysis on the physical properties. Furthermore, an off-line NIR model was developed for the quantification of the mean particle size. Segregation tendencies due to particle size incompatibilities were studied. Blend uniformity monitoring of a batch pharmaceutical mixing was achieved through a NIR off- line calibration method, which was used for the in-line drug quantification of a production scale mixing process. NIR in diffuse reflectance mode was used in the study of a continuous blending system. The effect of the process parameters, i.e. flow rate and stirring rate, was analyzed. Moreover, a NIR method for the in-line drug quantification was developed. NIR was implemented in a powder stream, in which the mass of powder measured by NIR was estimated. Results and discussion: Regarding particle size, incompatibilities due to different particle size ranges between the formulation ingredients lead to severe segregation. Particle size and cohesion determined the quality of the powder blend; slight cohesion and broader particle size distribution improved the robustness of the final blend. NIR showed high sensitivity to particle size variations, thus it was possible to develop a quantitative model for the mean particle size determination with a prediction error of 16 micrometers. Concerning batch mixing, an off-line calibration was generated for the quantification of two active ingredients contained in the formulation. The prediction errors varied from 0.4 to 2.3% m/m for each of the drugs respectively. Special emphasis was given on the proper wavelength selection for the quantitative analysis in order to focus the analysis on the active ingredients quantification. In relation to continuous blending of particulate material, a quantitative NIR model was developed for the in-line prediction of the active ingredient concentration. The NIR model was tested under different process conditions of feeding rate and stirring rate. High stirring rates produce higher scattering of the NIR predictions. This was directly associated with the acceleration of the particles at the outlet of the blender affecting the dwell time of the particles with the NIR probe. The NIR model showed to be robust to moderate feed rate increments; however the NIR model under-predicted the drug concentration under moderate feed rate reductions of 30 kg/h. Furthermore, the continuous blending phases were clearly identified by principal component analysis, moving block of standard deviation, and relative standard deviation, all of them giving consistent results. NIR measurements in a powder stream involved the scanning of powder flowing in a chute. The flow of bulk solids is a complex phenomenon in which powder moves at a certain velocity. The motion of particles produces changes in the density and distribution of the voids. In this study, the velocity of the powder sliding down an inclined chute was measured and used for the estimation of the NIR measured mass. The mass observed during one NIR measurement was estimated to be less than one tablet. Conclusions: This study proved the feasibility of applying NIR spectroscopy for the blend uniformity monitoring of batch and continuous powder mixing. Understanding the critical parameters of powder mixing lead to a robust process and reliable analytical methods. NIR proved to be a valuable and versatile analytical tool in the measurement of bulk solids. |
