Process analysis of fluidized bed granulation

A Novel Method for Rapid Particle Size Analysis of Ibuprofen Using Near-infrared Spectroscopy

Particle size distribution (PSD) is often considered as critical material attribute for active pharmaceutical ingredients (APIs), and the need for regular evaluation stands as an important quality control parameter in the pharmaceutical industry. Near-infrared (NIR) spectroscopy, used routinely for API identification, was introduced as analytical tool for simultaneous determination of particle size of ibuprofen. The demonstrated potential was highlighted by the development of rapid, robust, and noninvasive method coupled with multivariate data analysis (MVA), which can be easily transferred in QC laboratories for routine analysis. Principal component analysis (PCA) and partial least squares (PLS) regression analyses were performed on a calibration set of 61 ibuprofen samples, which differed in their median particle size Dv(50). The score scatterplots revealed evident clustering of ibuprofen samples according to their particle size, as well as occurrence of a distinctive outlying group of ibuprofen samples originating from one manufacturer. Further testing by means of mid-infrared spectroscopy, X-ray powder diffraction, and particle morphology analysis pinpointed particle morphology being responsible for the observed outlying group. Consequently, PLS class modeling based on particle morphology was introduced, which delivered two separate PLS regression models: one for blade-like ibuprofen crystals and another for irregular plate-like ibuprofen crystals. The former regression model exhibited high correlation coefficients and satisfactory predictive power (R²X = 0.999, R²Y = 0.917, Q² = 0.901), whereas the latter demonstrated lower statistical indicators (R²X = 0.99, R²Y = 0.72, Q² = 0.55). Additionally, the study underlines the importance of particle shape evaluation and sample classification according to particle morphology similarity prior to building NIRS-based regression models for PSD determination.

Product Development, Manufacturing, and Packaging of Solid Dosage Forms Under QbD and PAT Paradigm: DOE Case Studies for Industrial Applications

An integrated approach based on QbD and PAT provides a systematic and innovative framework for product development, manufacturing, and quality risk management. In this context, the significance of the outcome of design of experiments (DOEs) to the selection of the product design, robust commercial manufacturing process, design space, and overall control strategy remains vital for the success of a drug product throughout its life cycle. This paper aims at discussing selected recent DOE case studies conducted during QbD-based and integrated QbD/PAT-based development of solid oral formulations and process improvement studies. The main focus of this paper is to highlight the rationales and importance of design selection during development and applications of mathematical models and statistical tools in analyzing DOE and PAT data for developing a design space, control strategy, and improved process monitoring. A total of 25 case studies (includes 9 PAT application studies) have been discussed in this paper which cover 11 manufacturing processes commonly utilized for solid dosage forms. Two case studies relevant to selection of packaging design for solid dosage forms are also briefly discussed to complete the scope. Overall, for a successful modern QbD approach, it is highly important that DOEs are conducted and analyzed in a logical sequence which involves designs that are phase-appropriate and quality-driven and facilitate both statistical and chemometric thinking at each development stage. This approach can result into higher regulatory flexibility along with lower economic burden during life cycle of a product, irrespective of regulatory path used (NDA or ANDA).

Additive manufacturing of prototype elements with process interfaces for continuously operating manufacturing lines

Rapid prototyping based on in silico design and 3D printing enables fast customization of complex geometries to multiple needs. This study utilizes, additive manufacturing for rapid prototyping of elements for continuously operating mixing geometries including interfaces with process analytical technology (PAT) tools, to show that 3D printing can be used for prototyping of both parts of production line and PAT interfacing solution. An additional setup was designed for measuring the dynamic calibration samples for a semi-quantitative near infrared (NIR) spectroscopic model. The powder was filled in a small calibration chamber and in-line NIR spectra of calibration samples were collected from moving material while mimicking the powder flow dynamics in a typical continuous mixer. This dynamic powder mixing system was compared with a static powder calibration model where the NIR probe was placed at different positions on a static sample. Principal component analysis (PCA) revealed that the 3D printed device with dynamic measurement of the NIR spectra had more potential for quantitative analysis. With the prototype continuous mixer, two differently placed process interfaces for NIR spectroscopic monitoring of the powder mixing were evaluated. With this approach, the importance of positioning the process analytical tools to assess the blend uniformity could be demonstrated. It was also observed that with the longer mixing geometry, a better mixing result was achieved due to a larger hold up volume and increased residence time.

PAT-Based Control of Fluid Bed Coating Process Using NIR Spectroscopy to Monitor the Cellulose Coating on Pharmaceutical Pellets

Current endeavor was aimed towards monitoring percent weight build-up during functional coating process on drug-layered pellets. Near-infrared (NIR) spectroscopy is an emerging process analytical technology (PAT) tool which was employed here within quality by design (QbD) framework. Samples were withdrawn after spraying every 15-Kg cellulosic coating material during Wurster coating process of drug-loaded pellets. NIR spectra of these samples were acquired using cup spinner assembly of Thermoscientific Antaris II, followed by multivariate analysis using partial least squares (PLS) calibration model. PLS model was built by selecting various absorption regions of NIR spectra for Ethyl cellulose, drug and correlating the absorption values with actual percent weight build up determined by HPLC. The spectral regions of 8971.04 to 8250.77 cm^-1, 7515.24 to 7108.33 cm^-1, and 5257.00 to 5098.87 cm^-1 were found to be specific to cellulose, where as the spectral region of 6004.45 to 5844.14 cm^-1was found to be specific to drug. The final model gave superb correlation co-efficient value of 0.9994 for calibration and 0.9984 for validation with low root mean square of error (RMSE) values of 0.147 for calibration and 0.371 for validation using 6 factors. The developed correlation between the NIR spectra and cellulose content is useful in precise at-line prediction of functional coat value and can be used for monitoring the Wurster coating 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.

On-line monitoring of fluid bed granulation by photometric imaging

This paper introduces and discusses a photometric surface imaging approach for on-line monitoring of fluid bed granulation. Five granule batches consisting of paracetamol and varying amounts of lactose and microcrystalline cellulose were manufactured with an instrumented fluid bed granulator. Photometric images and NIR spectra were continuously captured on-line and particle size information was extracted from them. Also key process parameters were recorded. The images provided direct real-time information on the growth, attrition and packing behaviour of the batches. Moreover, decreasing image brightness in the drying phase was found to indicate granule drying. The changes observed in the image data were also linked to the moisture and temperature profiles of the processes. Combined with complementary process analytical tools, photometric imaging opens up possibilities for improved real-time evaluation fluid bed granulation. Furthermore, images can give valuable insight into the behaviour of excipients or formulations during product development.

In silico modeling of in situ fluidized bed melt granulation

Fluidized bed melt granulation has recently been recognized as a promising technique with numerous advantages over conventional granulation techniques. The aim of this study was to evaluate the possibility of using response surface methodology and artificial neural networks for optimizing in situ fluidized bed melt granulation and to compare them with regard to modeling ability and predictability. The experiments were organized in line with the Box-Behnken design. The influence of binder content, binder particle size, and granulation time on granule properties was evaluated. In addition to the response surface analysis, a multilayer perceptron neural network was applied for data modeling. It was found that in situ fluidized bed melt granulation can be used for production of spherical granules with good flowability. Binder particle size had the most pronounced influence on granule size and shape, suggesting the importance of this parameter in achieving desired granule properties. It was found that binder content can be a critical factor for the width of granule size distribution and yield when immersion and layering is the dominant agglomeration mechanism. The results obtained indicate that both in silico techniques can be useful tools in defining the design space and optimization of in situ fluidized bed melt granulation.

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.

Design space approach in optimization of fluid bed granulation and tablets compression process

The aim of this study was to optimize fluid bed granulation and tablets compression processes using design space approach. Type of diluent, binder concentration, temperature during mixing, granulation and drying, spray rate, and atomization pressure were recognized as critical formulation and process parameters. They were varied in the first set of experiments in order to estimate their influences on critical quality attributes, that is, granules characteristics (size distribution, flowability, bulk density, tapped density, Carr's index, Hausner's ratio, and moisture content) using Plackett-Burman experimental design. Type of diluent and atomization pressure were selected as the most important parameters. In the second set of experiments, design space for process parameters (atomization pressure and compression force) and its influence on tablets characteristics was developed. Percent of paracetamol released and tablets hardness were determined as critical quality attributes. Artificial neural networks (ANNs) were applied in order to determine design space. ANNs models showed that atomization pressure influences mostly on the dissolution profile, whereas compression force affects mainly the tablets hardness. Based on the obtained ANNs models, it is possible to predict tablet hardness and paracetamol release profile for any combination of analyzed factors.

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.

In-line monitoring of granule moisture in fluidized-bed dryers using microwave resonance technology

This is the first report on in-line moisture measurement of pharmaceutical products by microwave resonance technology. In order to meet the FDA's PAT approach, a microwave resonance sensor appropriate for pharmaceutical use was developed and implemented into two different fluidized-bed dryers. The novel sensor enables a continuous moisture measurement independent from the product density. Hence, for the first time precise real time determination of the moisture in pharmaceutical granules becomes possible. The qualification of the newly developed sensor was performed by drying placebo granules under experimental conditions and the validation using drug loaded granules under real process conditions. The results of the investigations show good correlations between water content of the granules determined by the microwave resonance sensor and both reference methods, loss on drying by infrared light exposure and Karl Fischer titration. Furthermore, a considerable time saving in the drying process was achieved through monitoring the residual water content continuously by microwave resonance technology instead of the formerly used discontinuous methods.

Process analytical technology case study part I: feasibility studies for quantitative near-infrared method development

This article is the first of a series of articles detailing the development of near-infrared (NIR) methods for solid-dosage form analysis. Experiments were conducted at the Duquesne University Center for Pharmaceutical Technology to qualify the capabilities of instrumentation and sample handling systems, evaluate the potential effect of one source of a process signature on calibration development, and compare the utility of reflection and transmission data collection methods. A database of 572 production-scale sample spectra was used to evaluate the interbatch spectral variability of samples produced under routine manufacturing conditions. A second database of 540 spectra from samples produced under various compression conditions was analyzed to determine the feasibility of pooling spectral data acquired from samples produced at diverse scales. Instrument qualification tests were performed, and appropriate limits for instrument performance were established. To evaluate the repeatability of the sample positioning system, multiple measurements of a single tablet were collected. With the application of appropriate spectral preprocessing techniques, sample repositioning error was found to be insignificant with respect to NIR analyses of product quality attributes. Sample shielding was demonstrated to be unnecessary for transmission analyses. A process signature was identified in the reflection data. Additional tests demonstrated that the process signature was largely orthogonal to spectral variation because of hardness. Principal component analysis of the compression sample set data demonstrated the potential for quantitative model development. For the data sets studied, reflection analysis was demonstrated to be more robust than transmission analysis.

Monitoring the fluidized bed granulation process based on S-statistic analysis of a pressure time series

Pressure fluctuation measurements collected during the fluidized bed granulation of pharmaceutical granule have been analyzed using the attractor comparison technique denoted as the S-statistic. Divergence of the bed state from the reference during granulation is followed by a return to a condition statistically similar to the original state of the dry fluidized ingredients on drying. This suggests insensitivity of the S-statistic technique to the changes in particle size distribution occurring during the granulation process. Consequently, the monitoring of pressure fluctuations alone may provide an easily implemented technique for the tracking of granule moisture and process end-point determination.

Application of on-line Raman spectroscopy for characterizing relationships between drug hydration state and tablet physical stability

Experiments were conducted to elucidate the relationship between risedronate sodium (RS) hydration state and the physical stability of tablets containing RS. The RS crystal lattice contains channels occupied by water, which is removed by drying processes at temperatures below the boiling point of water, causing a reversible contraction of the crystal lattice. In this study, risedronate sodium was wet granulated followed by fluid bed drying to final granulation moisture contents between 1 and 7%, and then compressed into tablets. During drying, the RS solid-state form was continuously monitored using on-line Raman spectroscopy. Raman spectra acquired in these experiments enabled direct monitoring of changes in the RS crystal lattice, due to dehydration, which provided key information relating RS solid-state form characteristics to final granulation moisture content. Final granulation moisture was found to have a significant effect on the change in RS hydration state measured by Raman spectroscopy. As the final granulation moisture decreased, the amount of RS dehydrated form increased. The largest Raman spectral changes were in the CH stretching region and the region including the 3-picoline ring and PO2- stretches. These changes are indicative of substantial changes in the RS solid-state structure. Final granulation moisture also had a significant effect on the change in tablet thickness over time. Lower final granulation moisture caused a greater increase in tablet thickness as the RS rehydrated. In addition, the change in RS hydration state during fluid bed drying, measured by on-line Raman, was correlated to the increase in tablet thickness and subsequent loss of tablet integrity. Raman spectroscopy allowed direct RS hydration state monitoring, rather than inference from a bulk moisture measurement. Development of a Process Analytical Technology (PAT), specifically Raman, to monitor RS solid-state during drying enabled establishment of relationships between fundamental hydration dynamics associated with RS and final product performance attributes.