Influence of particle size and blender size on blending performance of bi-component granular mixing: A DEM and experimental study.

The effect of particle size enlargement and blender geometry down-scaling on the blend uniformity (BU) was evaluated by Discrete Element Method (DEM) to predict the blending performance of a binary granular mixture. Three 10 kg blending experiments differentiated by the physical properties specifically particle size were performed as reference for DEM simulations. The segregation behavior observed during the diffusion blending was common for all blends, while the sample BU, i.e., standard deviation of active ingredient content % was different among the three blends reflecting segregation due to the particle size differences between the components. Quantitative prediction of the sample BU probability density distribution in reality based on the DEM simulation results was successfully demonstrated. The average root mean square error normalized by the mean of the mean sample BU in the blends was 0.228. Beside the ratio of blender container to particle size, total number of particles in the blender and the number of particles in a sample were confirmed critical for the blending performance. These in-silico experiments through DEM simulations would help in setting a design space with respect to the particle size and in a broader sense with respect to the physical properties in general.

Selection of a round convex tablet shape that mitigates the risk of chipping and capping based on systematic evaluation by utilizing multivariate analysis.

Selecting a tablet shape that minimizes the risk of chipping and capping during manufacture is important in pharmaceutical industry. Here, the selection was performed based on systematic evaluation for the first time. Abrasion and stress relaxation time were utilized as indices of the occurrences of chipping and capping, respectively. Partial least square regression models that used tablet shape parameters to estimate the tablet's abrasion and stress relaxation time were utilized to develop response surface plots of the effect of the tablet shapes on the occurrence of chipping and capping systematically, and to identify an optimum tablet shape that is expected to have a low occurrence of chipping and capping. A verification study using commercial scale facilities proved that the optimum tablet shape had a lower occurrence of chipping and capping compared to suboptimum examples as speculated by their abrasion and stress relaxation time. The observed mathematical relationship between the tablet shapes and the occurrence of chipping and capping were consistent with the previous studies based on the comparison of limited number of tablet shapes using different formulations. Consequently, it is expected to be applicable to other formulations beyond the evaluated formulation in the present study.

Void forming index: A new parameter for detecting microstructural transformation caused by powder agglomeration.

As powder agglomeration during storage causes a decrease in the performance of dry powder inhalers (DPIs), it is important to understand the properties of powder agglomeration in developing DPIs. Generally, powder agglomeration is caused by capillary force and crystalline transformation in conditions of higher humidity. It is, however, difficult to correlate crystalline transformation and powder agglomeration, especially when the crystalline transformation is limited. In this study, we focused on the application of inverse gas chromatography (iGC) to detect powder agglomeration directly. There was a slight change between the powder state and lactose agglomerates using powder X-ray diffraction, and dynamic vapor sorption. On the other hand, a change in pressure drop was found during measurement of lactose using iGC. After measurement by iGC, powdered lactose agglomerated. This finding suggests that a pressure drop is related to powder agglomeration and can be employed to detect the onset of powder agglomeration. Based on these findings, we propose a novel index-the Void Forming Index (VFI)-which is related to the pressure drop with iGC. The VFI is a useful index in the evaluation of powder agglomeration, and will be especially useful during DPI development.

Design and evaluation of an extended-release matrix tablet formulation; the combination of hypromellose acetate succinate and hydroxypropylcellulose.

The purpose of this study was to develop an extended-release (ER) matrix tablet that shows robust dissolution properties able to account for the variability of pH and mechanical stress in the GI tract using a combination of enteric polymer and hydrophilic polymer. Hypromellose acetate succinate (HPMCAS) and hydroxypropylcellulose (HPC) were selected as ER polymers for the ER matrix tablet (HPMCAS/HPC ER matrix tablet). Oxycodone hydrochloride was employed as a model drug. Dissolution properties of the HPMCAS/HPC ER matrix tablets were evaluated and were not affected by the pH of the test medium or paddle rotating speed. In a USP apparatus 3 (bio-relevant dissolution method), dissolution profiles of the HPMCAS/HPC ER matrix tablets containing oxycodone hydrochloride were similar to that of the reference product (OxyContin). Moreover, in vivo performance after oral administration of the HPMCAS/HPC ER matrix tablets to humans was simulated by GastroPlus based on dissolution profiles from the USP apparatus 3. The plasma concentration-time profile simulated was similar to that of the reference product. These results suggest that the combination of HPMCAS and HPC shows a robust dissolution profile against pH and paddle rotating speed and indicates the appropriate extended-release profile in humans.

Setting the process parameters for the coating process in order to assure tablet appearance based on multivariate analysis of prior data.

Designing efficient, robust process parameters in drug product manufacturing is important to assure a drug's critical quality attributes. In this research, an efficient, novel procedure for a coating process parameter setting was developed, which establishes a prediction model for setting suitable input process parameters by utilizing prior manufacturing knowledge for partial least squares regression (PLSR). In the proposed procedure, target values or ranges of the output parameters are first determined, including tablet moisture content, spray mist condition, and mechanical stress on tablets. Following the preparation of predictive models relating input process parameters to corresponding output parameters, optimal input process parameters are determined using these models so that the output parameters hold within the target ranges. In predicting the exhaust air temperature output parameter, which reflects the tablets' moisture content, PLSR was employed based on prior measured data (such as batch records of other products rather than design of experiments), leading to minimal new experiments. The PLSR model was revealed to be more accurate at predicting the exhaust air temperature than a conventional semi-empirical thermodynamic model. A commercial scale verification demonstrated that the proposed process parameter setting procedure enabled assurance of the quality of tablet appearance without any trial-and-error experiments.

A Novel Scale Up Model for Prediction of Pharmaceutical Film Coating Process Parameters.

In the pharmaceutical tablet film coating process, we clarified that a difference in exhaust air relative humidity can be used to detect differences in process parameters values, the relative humidity of exhaust air was different under different atmospheric air humidity conditions even though all setting values of the manufacturing process parameters were the same, and the water content of tablets was correlated with the exhaust air relative humidity. Based on this experimental data, the exhaust air relative humidity index (EHI), which is an empirical equation that includes as functional parameters the pan coater type, heated air flow rate, spray rate of coating suspension, saturated water vapor pressure at heated air temperature, and partial water vapor pressure at atmospheric air pressure, was developed. The predictive values of exhaust relative humidity using EHI were in good correlation with the experimental data (correlation coefficient of 0.966) in all datasets. EHI was verified using the date of seven different drug products of different manufacturing scales. The EHI model will support formulation researchers by enabling them to set film coating process parameters when the batch size or pan coater type changes, and without the time and expense of further extensive testing.

Tablet Velocity Measurement and Prediction in the Pharmaceutical Film Coating Process.

The purpose of this study was to measure the tablet velocity in pan coating machines during the film coating process in order to understand the impact of the batch size (laboratory to commercial scale), coating machine type (DRIACOATER, HICOATER® and AQUA COATER®) and manufacturing conditions on tablet velocity. We used a high speed camera and particle image velocimetry to measure the tablet velocity in the coating pans. It was observed that increasing batch sizes resulted in increased tablet velocities under the same rotation number because of the differences in circumferential rotation speeds. We also observed the tendency that increase in the filling ratio of tablets resulted in an increased tablet velocity for all coating machines. Statistical analysis was used to make a tablet velocity predictive equation by employing the filling ratio and rotation speed as the parameters from these measured values. The correlation coefficients of predicted value and experimental value were more than 0.959 in each machine. Using the predictive equation to determine tablet velocities, the manufacturing conditions of previous products were reviewed, and it was found that the tablet velocities of commercial scales, in which tablet chipping and breakage problems had occurred, were higher than those of pilot scales or laboratory scales.

Comparisons of Aluminum and Silica Elution from Various Glass Vials.

To understand the risk of particle formation in glass vials, we investigated the correlation between vial surface condition and alminum (Al) or silicon (Si) elution using various suppliers' vials with or without surface treatment. The elution of Si, which can also be an indicator of Al elution, consists of two phases; the first phase is influenced by roughness of the glass surface at the time of filling, and the second phase is dependent on the fundamental elution rate from the glass tube. When vials were filled with citrate buffer at pH 7, vials with varied surface conditions showed the most obvious differences in Al and Si elution. Sulfur-treated vials showed slightly lower Al and Si elution than the non-treated vials. It is considered that this effect of the sulfur treatment on elution is due to the surface being smoothed during heat treatment after the washing process. Different from the sulfur treatment, silicon dioxide (SiO2)-coated vials hardly showed any Al elution as long as the surface was fully coated with the SiO2 layer. It was found that the protective effect of the SiO2 layer against Al elution is more effective in a vial filled with a solution having a lower pH, due to the lower Si dissolving rate occurring at a lower pH. As shown above, pre-measuring the Si and Al present in a citrate buffer at pH 7 placed within a glass container can be a useful tool for selecting the appropriate container for liquid drugs.

Spectral fluctuation dividing for efficient wavenumber selection: application to estimation of water and drug content in granules using near infrared spectroscopy.

In process analytical technology (PAT) based on near infrared (NIR) spectroscopy, wavenumber selection is crucial to develop an accurate and robust calibration model. The present research proposes new efficient spectral dividing and wavenumber selection methods to significantly reduce the computational load required by conventional wavenumber selection methods such as interval partial least squares (iPLS). The proposed method, named spectral fluctuation dividing (SFD), divides a whole spectrum into multiple spectral intervals at local minimum points of the spectral fluctuation profile, which consists of the standard deviation of absorbance at each wavenumber in a calibration set. SFD is combined with PLS (SFD-PLS) to select the spectral intervals at which input variables have significant influence on a target response. The usefulness of SFD-PLS was demonstrated through its application to the problems of estimating water and drug content in granules. PLS models based on SFD-PLS achieved higher estimation accuracy than those based on conventional methods including iPLS, PLS-beta, and variable influence on projection (VIP). In addition, SFD-PLS was more than 10 times faster than the conventional variable selection methods including PLS-beta and VIP; in particular, SFD-PLS was more than 25 times faster than iPLS. Consequently, the proposed SFD-PLS is a promising wavenumber selection method.