Next generation fluidized bed granulator automation

Real-time in-line prediction of drug loading and release rate in the coating process of diclofenac sodium spheres based on near infrared spectroscopy

The preparation of diclofenac sodium spheres by fluidized bed is a common production mode for the pharmaceutical preparations at present, but the critical material attributes in the production process is mostly analyzed off-line, which is time-consuming and laborious, and the analysis results lag behind. In this paper, the real-time in-line prediction of drug loading of diclofenac sodium and the release rate during the coating process was realized by using near infrared spectroscopy. For the best near infrared spectroscopy (NIRS) model of drug loading, R²_cv, R²_p, RMSECV, RMSEP were 0.9874, 0.9973, 0.002549 mg/g, 0.001515 mg/g respectively. For the best NIRS model of three release time points, the R²_cv, R²_p, RMSECV and RMSEP were 0.9755, 0.9823, 3.233%, 4.500%; 0.9358, 0.9965, 2.598%, 0.7939% and 0.9867, 0.9927, 0.4085%, 0.4726% respectively. And the analytical ability of these model was verified. The organic combination of these two parts of work constituted an important basis for ensuring the safety and effectiveness of diclofenac sodium spheres from the perspective of production process.

Near-infrared spectroscopy monitoring and control of the fluidized bed granulation and coating processes-A review

The fluidized bed granulation and pellets coating technologies are widely used in pharmaceutical industry, because the particles made in a fluidized bed have good flowability, compressibility, and the coating thickness of pellets are homogeneous. With the popularization of process analytical technology (PAT), real-time analysis for critical quality attributes (CQA) was getting more attention. Near-infrared (NIR) spectroscopy, as a PAT tool, could realize the real-time monitoring and control during the granulating and coating processes, which could optimize the manufacturing processes. This article reviewed the application of NIR spectroscopy in CQA (moisture content, particle size and tablet/pellet thickness) monitoring during fluidized bed granulation and coating processes. Through this review, we would like to provide references for realizing automated control and intelligent production in fluidized bed granulation and pellets coating of pharmaceutical industry.

Real-time release monitoring for water content and mean particle size of granules in lab-sized fluid-bed granulator by near-infrared spectroscopy

Simultaneous real-time monitoring of water content and mean particle size in the powder bed of a fluidized-bed granulator was performed by near-infrared (NIR) spectroscopy through a window, and the findings were used to evaluate the granular properties.

Application of in-line near infrared spectroscopy and multivariate batch modeling for process monitoring in fluid bed granulation

Fluid bed is an important unit operation in pharmaceutical industry for granulation and drying. To improve our understanding of fluid bed granulation, in-line near infrared spectroscopy (NIRS) and novel environmental temperature and RH data logger called a PyroButton(®) were used in conjunction with partial least square (PLS) and principal component analysis (PCA) to develop multivariate statistical process control charts (MSPC). These control charts were constructed using real-time moisture, temperature and humidity data obtained from batch experiments. To demonstrate their application, statistical control charts such as Scores, Distance to model (DModX), and Hotelling's T(2) were used to monitor the batch evolution process during the granulation and subsequent drying phase; moisture levels were predicted using a validated PLS model. Two data loggers were placed one near the bottom of the granulator bowl plenum where air enters the granulator and another inside the granulator in contact with the product in the fluid bed helped to monitor the humidity and temperature levels during the granulation and drying phase. The control charts were used for real time fault analysis, and were tested on normal batches and on three batches which deviated from normal processing conditions. This study demonstrated the use of NIRS and the use of humidity and temperature data loggers in conjunction with multivariate batch modeling as an effective tool in process understanding and fault determining method to effective process control in fluid bed granulation.

Particle size, moisture, and fluidization variations described by indirect in-line physical measurements of fluid bed granulation

The aim of this study was to evaluate an instrumentation system for a bench scale fluid bed granulator to determine the parameters expressing the changing conditions during the spraying phase of a fluid bed process. The study focused mainly on four in-line measurements (dependent variables): fluidization parameter (calculated by inlet air flow rate and rotor speed), pressure difference over the upper filters, pressure difference over the granules (lower filter), and temperature of the fluidizing mass. In-line particle size measured by the spatial filtering technique was an essential predictor variable. Other physical process measurements of the automated granulation system, 25 direct and 12 derived parameters, were also utilized for multivariate modeling. The correlation and partial least squares analyses revealed significant relationships between various process parameters highlighting the particle size, moisture, and fluidization effect. Fluidization parameter and pressure difference over upper filters were found to correlate with in-line particle size and therefore could be used as estimates of particle size during granulation. The pressure difference over the granules and the temperature of the fluidizing mass expressed the moisture conditions of wet granulation. The instrumentation system evaluated here is an invaluable aid to gaining more control for fluid bed processing to obtain repeatable granules for further processing.

The Characterization of Fluidization Behavior Using a Novel Multichamber Microscale Fluid Bed

In the preformulation stage, there is a special need to determine the process behavior of materials with smaller amounts of samples. The purpose of this study was to assemble a novel automated multichamber microscale fluid bed module with a process air control unit for the characterization of fluidization behavior in variable conditions. The results were evaluated on the basis of two common computational methods, the minimum fluidization velocity, and the Geldart classification. The materials studied were different particle sizes of glass beads, microcrystalline cellulose, and silicified microcrystalline cellulose. During processing, the different characteristic fluidization phases (e.g., plugging, bubbling, slugging, and turbulent fluidization) of the materials were observed by the pressure difference over the bed. When the moisture content of the process air was increased, the amount of free charge carriers increased and the fine glass beads fluidized on the limited range of velocity. The silicification was demonstrated to improve the fluidization behavior with two different particle sizes of cellulose powders. Due to the interparticle (e.g., electrostatic) forces of the fine solids, the utilization of the computational predictions was restricted. The presented setup is a novel approach for studying process behavior with only a few grams of materials.

Characterization of particle sizes in bulk pharmaceutical solids using digital image information

The purpose of this study was to demonstrate a novel method of extracting relevant information from undispersed bulk powder surfaces to be used in particle size analysis. A new surface imaging approach for undispersed powders combined with multivariate modeling was used. Digital surface images of various granule batches were captured using an inventive optical setup in controlled illumination conditions. A descriptor, the gray scale difference matrix (GSDM), which describes the particle size of granular material was generated and extracted from the powder surface image information. Partial least squares (PLS) modeling was used to create a model between the GSDM and the particle size distribution of granules measured with sieving. The use of lateral illumination and the combining of information from 2 surface images strengthened the shading effects on the powder surfaces. The shading effects exposed the topography or the visual texture of the powder surfaces. This textural information was efficiently extracted using the GSDM descriptor. The goodness-of-fit (R2) for the created PLS model was 0.91 and the predicted variation (Q2) was 0.87, indicating a good model. The model covered granule sizes in the size range of approximately 20 to 2500 microm. The extracted descriptor was effectively used in particle size measurement. This study confirms that digital images taken from undispersed bulk powder surfaces contain substantial information needed for particle size distribution analysis. The use of the GSDM enabled the utilization of bulk powder surface information and provided a fast method for particle size measurement.

Dehydration Studies Using a Novel Multichamber Microscale Fluid Bed Dryer with In‐Line Near‐Infrared Measurement

The purpose of this research was to study the effect of two process parameters (temperature and moisture content) on dehydration behavior of different materials using a novel multichamber microscale fluid bed dryer with a process air control unit and in-line near-infrared (NIR) spectroscopy. The materials studied were disodium hydrogen phosphates with three different levels of hydrate water and wet theophylline granules. Measured process parameters of fluid bed drying were logged, including in-line NIR signals. Off-line analyses consisted of X-ray powder diffraction patterns, Fourier transform NIR spectra and moisture contents of studied materials. During fluid bed drying, the stepwise dehydration of materials was observed by the water content difference of inlet and outlet air, the pressure difference over the bed, and the in-line NIR spectroscopy. The off-line analysis confirmed the state of solid materials. The temperature and the moisture content of the process air were demonstrated to be significant factors for the solid-state stability of theophylline. The presented setup is a material and cost-saving approach for studying the influence of different process parameters on dehydration behavior during pharmaceutical processing.

Development of an automation system for a tablet coater

An instrumentation and automation system for a side-vented pan coater with a novel air-flow rate measurement system for monitoring the film-coating process of tablets was designed and tested. The instrumented coating system was tested and validated by film-coating over 20 pilot-scale batches of tablets with aqueous-based hydroxypropyl methylcellulose (HPMC). Thirteen different process parameters were continuously measured and monitored, and the most significant ones were logged for analysis. Laser profilometry was used to measure the surface roughness of the coated tablets. The instrumentation system provided comprehensive and quantitative information on the process parameters monitored. The measured process parameters and the responses of the film-coated tablet batches showed that the coating process is reproducible. The inlet air-flow rate influenced the coating process and the subsequent quality of the coated tablets. Increasing the inlet flow rate accelerated the drying of the tablet surface. At high inlet flow rate, obvious film-coating defects (ie, unacceptable surface roughness of the coated tablets) were observed and the loss of coating material increased. The instrumented and automated pan-coating system described, including historical data storage capability and a novel air-flow measurement system, is a useful tool for controlling and characterizing the tablet film-coating process. Monitoring of critical process parameters increases the overall coating process efficiency and predictability.

Process analysis of fluidized bed granulation

This study assesses the fluidized bed granulation process for the optimization of a model formulation using in-line near-infrared (NIR) spectroscopy for moisture determination. The granulation process was analyzed using an automated granulator and optimization of the verapamil hydrochloride formulation was performed using a mixture design. The NIR setup with a fixed wavelength detector was applied for moisture measurement. Information from other process measurements, temperature difference between process inlet air and granules (T(diff)), and water content of process air (AH), was also analyzed. The application of in-line NIR provided information related to the amount of water throughout the whole granulation process. This information combined with trend charts of T(diff) and AH enabled the analysis of the different process phases. By this means, we can obtain in-line documentation from all the steps of the processing. The choice of the excipient affected the nature of the solid-water interactions; this resulted in varying process times. NIR moisture measurement combined with temperature and humidity measurements provides a tool for the control of water during fluid bed granulation.

Visualization of fluid-bed granulation with self-organizing maps

The degree of the instrumentation of pharmaceutical unit operations has increased. This instrumentation provides information of the state of the process and can be used for both process control and research. However, on-line process data is usually multidimensional, and is difficult to study with traditional trends and scatter plots. The Self-Organizing Map (SOM) is a recognized tool for dimension reduction and process state monitoring. The basics of the SOM and the application to on-line data collected from a fluid-bed granulation process are presented. As a batch process, granulation traversed through a number of process states, which was visualized with SOM as a two-dimensional map. In addition, it is demonstrated how the differences between granulation batches can be studied. The results suggest that SOM together with new in-line process analytical solutions support the in-process control of the pharmaceutical unit operations. Further, a novel research tool for understanding the phenomena during processing is achieved.