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Over the past decade, continuous wet granulation has been emerging as a promising technology in drug product development. In this paper, the continuous high-shear mixer granulator, Lӧdige CoriMix® CM5, was investigated using a low-dose formulation with acetaminophen as the model drug. Design of experiments was deployed in conjunction with multivariate data analysis to explore the granulator design space and comprehensively understand the interrelation between process parameters and critical attributes of granules and tablets. Moreover, several complementary imaging techniques were implemented to unveil the underlying mechanisms of physical and chemical microstructure in affecting the tablet performance. The results indicated that L/S ratio and impeller speed outweighed materials feeding rate in modifying the granule and tablet properties. Increasing the degree of liquid saturation and mechanical shear input in the granulation system principally produced granules of larger size, smaller porosity, improved flowability and enhanced sphericity, which after compression generated tablets with slower disintegration process and drug release kinetics due to highly consolidated physical microstructure. Besides, in comparison to batch mixing, continuous mixing integrated with a conical mill enabled better powder de-agglomeration effect, thus accelerating the drug dissolution with increased surface area.

This study describes how near infrared (NIR) spectroscopy can be used to predict the dissolution of bilayer tablets as a non-destructive approach. Tablets in this study consist of two active pharmaceutical ingredients (APIs) physically separated in layers and manufactured under three levels of hardness. NIR spectra were individually acquired for both layers in diffuse reflectance mode. Reference dissolution profile values were obtained using dissolution apparatus & HPLC. A multivariate partial least squares (PLS) calibration model was developed for each API relating its dissolution profile to spectral data. This calibration model was used to predict dissolution profiles of an independent test set and results of the prediction were compared using model free approaches i.e. dissimilarity (f1) & similarity (f2) factors to assure similarity in dissolution performance.

Process analytical technologies (PAT) are identified as an essential element in the Quality by Design framework, providing the cornerstone to implement continuous pharmaceutical manufacturing. This study is concerned with employing three in-line PATs: Eyecon™ 3D imaging system, Near-infrared spectroscopy (NIRS) and Raman spectroscopy (RS), in a continuous twin-screw granulation process to enable real-time monitoring and prediction of critical quality attributes of granules. The Thermo Scientific™ Pharma 11 twin-screw granulator was used to manufacture granules from a low-dose formulation with caffeine anhydrous as the model drug. A 30-run full factorial design including three critical process parameters (liquid to solid ratio, barrel temperature and throughput) was conducted to evaluate the performance of each analytical tool. Eyecon™ successfully captured the granule size and shape variation from different experimental conditions and demonstrated sufficient sensitivity to the fluctuation of size parameter D10 in the presence of process perturbations. The partial least square regression (PLSR) models developed using NIRS showed small relative standard error of prediction values (less than 5%) for most granule physical properties. In contrast, the RS-based PLSR models revealed higher prediction errors towards granule drug concentration, potentially due to the inhomogeneous premixing of raw materials during calibration model development.

Residence time distribution (RTD) is a probability density function that describes the time materials spend inside a system. It is a promising tool for mixing behavior characterization, material traceability, and real-time quality control in pharmaceutical manufacturing. However, RTD measurements are accompanied with some degree of uncertainties because of process fluctuation and variation, measurement error, and experimental variation among different replicates. Due to the strict quality control requirements of drug manufacturing, it is essential to consider RTD uncertainty and characterize its effects on RTD-based predictions and applications. Towards this end, two approaches were developed in this work, namely model-based and data-based approaches. The model-based approach characterizes the RTD uncertainty via RTD model parameters and uses Monte Carlo sampling to propagate and analyze the effects on downstream processes. To avoid bias and possible reduction of uncertainty during model fitting, the data-based approach characterizes RTD uncertainty using the raw experimental data and utilizes interval arithmetic for uncertainty propagation. A constrained optimization approach was also proposed to overcome the drawback of interval arithmetic in the data-based approach. Results depict probability intervals around the upstream disturbance tracking profile and the funnel plot, facilitating better decision-making for quality control under uncertainty.

Residence time distribution (RTD) modeling can aid the understanding and characterization of macro-mixing in continuous powder processing unit operations by relating observed behavior to quantitative model parameters. This article is the second part of the work done to characterize the effect of material properties on the measurement of RTDs in continuous powder processing operations. The goal of this paper is to examine the behavior of the RTD given different sets of tracer material properties. Tracer addition methods are discussed within the framework of their mathematical representation. The two most widely used RTD models in powder systems in the literature, the axial dispersion and the tank-in-series model, are presented and used to describe the experimental data. The RTD model parameters (e.g., Peclet number, number of tanks in series, and residence times) were regressed from the experimental data and compared using one-way ANOVA to determine the effects of materials properties on RTD. A model independent approach using a Multivariate Analysis of Variance (MANOVA) was also applied to compare the results with the model dependent method. Lastly, examples of how the RTD models can aid process design and understanding were described using both continuous and discrete convolution. The RTD models and their regressed coefficients were used to predict the mixing outputs of a semi-random input and the impact of disturbances on the process.

Residence time distribution (RTD) models are essential to understand process dynamics and support process monitoring and control in continuous manufacturing systems. RTD models can also be used to monitor material traceability and to isolate intermediate materials or finished products when specifications are not met. However, while pharmaceutical companies are currently making extensive use of RTD approaches, standard methods for conducting, interpreting, and using RTD results in continuous pharmaceutical manufacturing have not yet been established by regulatory authorities. This paper seeks to facilitate generating such standards. We discuss in detail the assumptions and conditions that are relevant to the proper selection of tracers for RTD experiments, and demonstrate that tracer selection can have substantial impact on RTD results. We selected seven materials with a wide range of properties as tracers and a single material as our base “blend”. The experimental results led to two major conclusions: (1) materials with different mechanical properties have dissimilar mean residence times (MRT) inside the systems and (2) blend ingredients with different mechanical properties travel at different speed inside of continuous blending systems. Results further indicated there were two critical mean residence times (MRTs): that of the tracer and that of the bulk. Matching of material properties between tracers is key in order to obtain similar MRTs using a given tracer. Differences between selected tracer and bulk material properties were found to lead to differences between the bulk space time and the tracer MRT. A set of recommendations on how to select tracer materials that would help characterize accurately the RTD of a continuous flow system are presented.

The rotary kiln is an essential device in chemical and metallurgical industries, with applications in a wide range of solids manufacturing processes. In particular, in the preparation of industrial chemical catalysts, the kiln has become a popular reactor for continuous calcination of catalysts ranging from millimeter-sized extrudates to micron-sized powders. As granular and powder flow behaviors are difficult to characterize, the design and scale-up of rotary calcination processes are often performed empirically. The goal of this research is to improve the fundamental understanding of powder flow in rotary kilns to aid in optimization of the continuous calcination process. For successful calcination to occur, the residence time of the particles must exceed the time required for heating and subsequent treatment. For uniform treatment of the feed, the particles must also exhibit low axial dispersion. In this work, the mean residence time and axial dispersion coefficient for a cohesive fluid catalytic cracking powder were determined in a pilot plant kiln by measuring the residence time distribution. This study utilized a pulse test developed by Danckwerts. Results were fit to the Taylor solution of the axial dispersion model and compared to the Sullivan prediction for mean residence time. It was found that the mean residence time decreases as the feed rate, kiln incline, and rotation rate increase. It was also found that the axial dispersion coefficient increases with speed of rotation and angle of incline. However, the axial dispersion coefficient decreases as the feed rate is increased.

Material properties are known to have a significant impact on pharmaceutical manufacturing performance, particularly for solid product processes. Evaluating the performance of a specific material, for example an active pharmaceutical ingredient or excipient, is critical during development stages in order to determine the impact of material properties on the process. However, materials may be scarce during the early stages of process development due to high cost, unavailability, import restrictions, etc. Furthermore, research on particular active pharmaceutical ingredients may be difficult given unknown exposure limits, which may delay process development and technology transfer. The purpose of this work was to establish a methodology for finding materials with similar behavior during processing using material property measurements so that a surrogate may be found and may replace the scarce material during process development. This work presents several commercially available material property tests and emphasizes the benefits of compiling material property measurements into libraries. Twenty pharmaceutically relevant materials and seven different powder characterization tests were considered as a case study. A total of 32 measurements were collected for each of the 20 materials, leading to a dataset of 640 measurements. The material property library was utilized to find similarities between materials using two multivariate methods: principal component analysis (PCA) and hierarchical clustering. The similarities between materials were evaluated with the performance of materials on powder feeding, refilling, and continuous blending equipment. Material clusters showed similar behavior in the characterized equipment. Moreover, results from the PCA and clustering analysis were further used to evaluate the level of collinearity and similarity between characterization measurements that can be further investigated to reduce the number of measurements that need to be collected. Material property measurement clusters were established based on the collinearity of the metrics.

Impregnation of active pharmaceutical ingredients (APIs) onto porous excipients has numerous benefits for solid dosage formulations. Previous work has successfully demonstrated the manufacturing of pharmaceuticals using fluidized bed (FB) impregnation of APIs onto porous carriers and discussed its advantages (such as easy to implement, improvement of blend uniformity and dissolution kinetics, and stabilization of amorphous APIs). This study aims to develop methods for analysis of the spatial distribution of the impregnated API inside the porous excipient. An understanding of the spatial distribution of the API can be important if one wants to achieve high drug loadings. In addition, the spatial distribution of the API can impact its dissolution rate. The impregnation profile is analyzed using energy dispersive X-ray spectroscopy (EDS). Two formulations are investigated using Fenofibrate and Acetaminophen (model APIs), impregnated onto Neusilin (porous excipient). Several methods are presented for particle embedding and cutting in order to produce cross-sections for analysis. Embedding with carbon-based resins/adhesives produces cross-sections with high quality but the resins contaminate the sample with carbon and reduce the detection of trace elements. Manually cutting particles immobilized on carbon tape or inorganic-based adhesives produces cross-sections with a higher degree of roughness but improves the detection of trace elements and reduces/eliminates carbon contamination in the sample, allowing for API detection by its carbon footprint. EDS analytical results showed that for both Fenofibrate and Acetaminophen formulations examined in this work, the API profile is highly uniform (detected by both carbon and characteristic trace elements).

As the pharmaceutical industry modernizes its manufacturing practices and incorporates more efficient processing approaches, it is important to reevaluate which process design elements affect product quality and the means to study these systems. The purpose of this work is to provide insight on a methodology to correlate the effect of raw material properties to equipment and process performance using both data-driven and semi-empirical models. In this work, lubricated blends of pharmaceutically-relevant materials were made using varying levels of magnesium stearate, ranging from 0.25 to 1.5%. Materials characterization (e.g., compressibility, permeability, density, particle size) was performed for all materials and blends. The blends were compressed using a two by three experimental design, varying tablet fill cam depth and tablet thickness, respectively. Tablet properties (e.g., weight, tensile strength, and thickness) were collected for all tablets. Using the collected tablet property results, models coefficients for the semi-empirical Kuentz and Leuenberger equation, which relates the tablet tensile strength to changes in porosity, were regressed. Empirical models were then developed to correlate the values of the Kuentz and Leuenberger equation coefficients to the blend material properties. The empirical models were then used in conjunction with the Kuentz and Leuenberger equation to evaluate the compression design and operational space, accounting for material properties. This proof of concept work aimed at developing correlations between raw material properties and unit operation models can aid process development, especially in design space characterization and robustness analysis.

Residence time distribution (RTD) models were developed to track raw material lots and investigate batch transitions in a continuous manufacturing system. Two raw materials with similar physical properties (granular metformin and lactose) were identified via Principal Component Analysis (PCA) from a library of bulk material properties and used to simulate the switching of lots during production. In-line near-infrared (NIR) spectra were collected with the powder flowing through a chute in a continuous manufacturing system to monitor metformin and lactose concentration in step-change experiments with Partial Least Squares (PLS) models. RTD provided an understanding of raw material propagation through the continuous manufacturing system. Transition times between raw material changes were identified using the results of two multivariate approaches PLS and PCA. The methodology was implemented to discriminate the transition zone in a raw material change, contributing to design control strategies for acceptance and diverting mechanisms.

Raman chemical mapping is an inherently slow analysis tool. Accurate and robust multivariate analysis algorithms, which require least amount of time and effort in method development are desirable. Calibration-free regression and resolution approaches such as classical least squares (CLS) and multivariate curve resolution using alternating least squares (MCR-ALS), respectively, help in reducing the resources required for method development. However, conventional CLS does not consider appropriate constraints, which may result in negative and/or greater than 100 % Raman concentration scores, while MCR-ALS may not always be as accurate as regression-based algorithms. Linear iterative optimization technology (IOT) is another calibration-free algorithm, which with appropriate constraints has previously shown promise in online and offline pharmaceutical mixture composition determination. This paper aims to evaluate the performance of the linear IOT algorithm for Raman chemical mapping of the active pharmaceutical ingredient (API), diluent, and lubricant in pharmaceutical tablets. Two pre-processing strategies were applied to the raw Raman mapping spectra. The results were compared with CLS (current reference method) and MCR-ALS. Special emphasis was given to mapping at low Raman exposure times to enable feasible total acquisition times (5 h). The quality of IOT/CLS/MCR-ALS estimated Raman concentration predictions were assessed by calculating a correlation factor between the spectrum corresponding to the maximum predicted concentration (or resolved spectra) of a component for IOT/CLS (or MCR-ALS) and the pure powder component spectrum. The Raman chemical maps were visualized, and the average Raman concentrations scores were compared. The results demonstrated the utility of IOT in Raman chemical mapping of pharmaceutical tablets. The diluent (lactose) and API (semi-fine APAP) used in this study were reliably estimated by IOT at relatively short Raman exposure times. On the other hand, as expected, the lubricant (magnesium stearate) could not be detected in any of the cases investigated here, irrespective of the algorithm used. Overall, for the API and diluent used in this formulation as well as the chemical mapping conditions, linear IOT seemed to better estimate the pure spectrum intensities and the average Raman scores (closer to CLS) in comparison to MCR-ALS. Moreover, application of appropriate constraints in linear IOT avoided the presence of negative and/or greater than 100 % Raman concentration scores, as observed in CLS-based Raman chemical maps.

This study investigates the use of twin-screw binder-free melt granulation (BFMG) in the development of high-dose solid dose formulations for low melting point thermally stable drugs. Both ibuprofen and guaifenesin are examined. By granulating pure API powder, it is shown that BFMG can successfully be used to produce granules that contain 100% API. A design of experiments (DoE) response surface methodology was used to establish the design space for the end-product. The effects of the most relevant process variables (barrel operating temperature, powder feed rate, screw speed and screw configuration) on granule properties (outlet temperature, size distribution, morphology, flowability, compressibility, porosity) and tablet attributes (tensile strength and in-vitro dissolution) were thoroughly studied. Barrel temperature (alone or in interactions with the other variables) represented the most significant variable for both drugs since it governs the formation of granules by partial melting and subsequent agglomeration of the fed powder. Interestingly, the shear action originated by screw speed and screw configuration resulted in various significant responses depending on the drug substance, indicating that it can also be affected by the nature of the processed molecule. Flow properties were improved (i.e., lower Hausner ratio) for both drugs after formation of granules. Tabletability was also tested by preparing 600 mg tablets for all samples. Surprisingly, the resulting granules were highly compactible, requiring only 1% lubricant to form strong tablets containing 96% API and 3% disintegrant. The results also showed that tablets become harder as the granule size increased, especially for guaifenesin. As expected, in-vitro dissolution results indicated that tablets and capsules showed slightly slower dissolution rates than the granules.

Purpose Lubrication is critical in pharmaceutical manufacturing of solid dosage forms. The purpose of this paper is to systematically compare and correlate the lubrication effect of two devices, a controlled shear system and a Resonant Acoustic Mixer, on the flow properties of pharmaceutical blends. Method A model formulation was selected. Full factorial designs were conducted to examine the effect of the total strain (or total energy) and the shear rate (or power) on the powder blend flow properties. Analysis of variance (ANOVA) and effect size test using omega-squared statistics were performed. Results Lubrication significantly improved the blend flowability. Mixing without magnesium stearate, or insufficient strain, resulted in more cohesive blends. The statistical analysis suggests that the shear rate had a minimal effect on the blend flow properties. The experimental results also suggest that although the two devices had comparable lubrication effects on the overall blend flowability, the changes of the interparticle forces in the lubricated blends were not identical. Conclusion This study demonstrated a scientific approach to compare different lubrication processes in an objective and reproducible manner. The findings are useful for process design, development, and transfer between different equipment types and process scales.

In this study, the origins of granule content non-uniformity in the high-shear wet granulation of a model two-component pharmaceutical blend were investigated. Using acetaminophen as the active pharmaceutical ingredient (API) and microcrystalline cellulose as the excipient, the distribution of the API across the granule size classes was measured for a range of conditions that differed in the duration of the initial dry mixing stage, the overall composition of the blend and the wet massing time. The coarse granule fractions were found to be systematically sub-potent, while the fines were enriched in the API. The extent of content non-uniformity was found to be dependent on two factors - powder segregation during dry mixing and redistribution of the API between the granule size fractions during the wet massing phase. The latter was demonstrated in an experiment where the excipient was pre-granulated, the API was added later and wet massed. The content non-uniformity in this case was comparable to that obtained when both components were present in the granulator from the beginning. With increasing wet massing time, the extent of content non-uniformity decreased, indicating that longer wet massing times might be a solution for systems with a natural tendency for component segregation.

Binary powder mixtures with variable segregation tendencies were “mixed” in a tumbling batch blender and in a continuous convective tubular blender. The degree of homogeneity of the final blend obtained from the continuous blender was found to be much higher than that from the batch V-blender, for mixtures and blender process parameters examined in this study. A direct relationship was observed between the segregation index of mixtures and a new material property metric defined as the ratio of the median particle size and bulk density of the ingredients that constitute the mixture. Moreover, for freely flowing materials, the extent of non-homogeneity at the end of a batch blending process was found to be proportional to the segregation index of the mixture and thus consequently in relation to the material property metric. Results demonstrate the superior capability of continuous blenders compared to batch blenders in their ability to homogenize segregating mixtures.

Purpose Accurate and consistent delivery of materials by well-designed feeders ensures overall process stability. Importantly, feeding performance is strongly dependent on material flow properties. The purpose of this study is to develop a methodology that identifies predictive correlation between material flow properties and feeder performance. Method The proposed methodology includes techniques to characterize material flow properties, methods to quantify feeding performance of a loss-in-weight feeder, and predictive multivariate analysis. Two approaches to correlate feeding performance and material flow properties were examined in the study: principal component analysis, followed by similarity scoring (PCA-SS), and partial least squares regression (PLSR). Results Experimental results showed that selection of the optimal feeder screw to achieve optimum feeding performance is heavily dependent on material flow properties. Both approaches to predict feeding performance based on material properties were validated. In addition, a strong correlation between the initial feed factor of each material and its flow properties were observed. Conclusion The work presented here has demonstrated an efficient approach to correlate material properties with gravimetric feeder performance. This approach is especially powerful in the early phase of process and product development, when the amount of a material is limited.

While continuous rotary calcination is a widely used thermal treatment in large-scale catalyst manufacturing, the process's heat and mass transfer mechanisms remain a challenge to characterize and to predict. Thus, the goal of this research is to improve fundamental understanding of rotary calcination to aid in the creation of a scientific methodology for process design and scale-up. For successful calcination to occur, the residence time of the particles must exceed the time required for heating and calcination at a set temperature. The optimal residence time therefore depends on both of these competing time scales, each of which is function of feed material properties, kiln geometry and kiln operating conditions. For uniform treatment of the feed, the particles must also exhibit low axial dispersion. In this work, the residence time distribution and axial dispersion coefficient for a dry cohesive fluid cracking catalyst powder were measured in a pilot plant kiln using a tracer study developed by Danckwerts. Results were successfully matched to the Taylor fit of the axial dispersion model and the Sullivan prediction for mean residence time. It was found that an increase in feed rate, kiln incline and rotary speed decreased mean residence time and overall axial dispersion. Such results have been established previously for free-flowing material like millimeter-sized extrudates, but have not been previously reported for the cohesive powders such as the one used in our work. As in free-flowing material, the axial dispersion coefficient was found to vary with kiln conditions. The values of the axial dispersion coefficients were lower for the powder than for free-flowing material, showing a dependency of axial dispersion on material properties as well as bulk flow behavior.

A full factorial design of experiments was used to study the effect of blend shear strain on the compaction process, relative density and strength of pharmaceutical tablets. The powder blends were subjected to different shear strain levels (integral of shear rate with respect to time) using an ad hoc Couette shear cell. Tablets were compressed at different compaction forces using an instrumented compactor simulator, and compaction curves showing the force-displacement profiles during compaction were obtained. Although the die-fill blend porosity (initial porosity) and the minimum in-die tablet porosity (at maximum compaction) decreased significantly with shear strain, the final tablet porosity was surprisingly independent of shear strain. The increase in the in-die maximum compaction with shear strain was, in fact, compensated during post-compaction relaxation of the tables, which also increased significantly with shear strain. Therefore, tablet porosity alone was not sufficient to predict tablet tensile strength. A decrease in the ‘work of compaction’ as a function of shear strain, and an increase in the recovered elastic work was observed, which suggested weaker particle-particle bonding as the shear strain increased. For each shear strain level, the Ryskewitch Duckworth equation was a good fit to the tensile strength as a function of tablet porosity, and the obtained asymptotic tensile strength at zero porosity exhibited a 60% reduction as a function of shear strain. This was consistent with a reduced bonding efficiency as the shear strain increased.

Modeling conductive heat transfer from rotary drum walls to a particle bed via discrete element method simulations, three time scales were determined: 1) the characteristic heating time of the bed, τ; 2) the particle thermal time constant, τp; and 3) the contact time between a particle and the wall, τc. Results fall onto a monotonic curve of τ/τc vs. ϕ (τp/τc), with three heating regimes. At low ϕ, conduction dominates, and the system heats quickly as a solid body. At high ϕ, granular convection dominates, and the bed heats slowly at a nearly uniform temperature. At intermediate ϕ, the system heats as a cool core with warmer outer layers. The results of this work have important implications for improving the design and operation of rotary drums (e.g., energy-intensive calcination processes). By calculating τp and τc from material and operating parameters, the characteristic heating time, τ, can be predicted a priori.

This study presents the first investigations on the micro-mixing properties of pharmaceutical powder blends from a resonant acoustic mixer using near-infrared chemical imaging. All experiments were done in a laboratory resonant acoustic mixer (RAM). The powder blends were studied using near-infrared chemical imaging (NIR-CI). Qualitative (i.e. chemical images) and quantitative (e.g. mean diameter of aggregates) results were obtained using this analytical method. The quantitative results were correlated to the acceleration (mixing intensity) and total mixing time. Overall, the resonant acoustic mixing performance increased with increasing acceleration and mixing time. Therefore, larger aggregates of the active pharmaceutical ingredient (API) were found at lower accelerations (mixing intensity) and shorter mixing times. Mixing in the RAM efficiently reduced the overall aggregate size of the cohesive API (semi-fine APAP, ~ 45 μm) used in a common blend of filler (microcrystalline cellulose, ~ 110 μm) and lubricant (magnesium stearate, ~ 10 μm).

Purpose The purpose of this study is to develop a model for predicting the flow properties of a four-component powder mixture. Method To build the model, 22 samples were prepared using an extreme vertices mixture design. The flow properties were characterized using rotational shear cell methodology. Two additional blends were tested for external validation to illustrate model applicability. Results Cohesion was shown to be in a linear relation with unconfined yield strength and a power relation with flow factor. The special cubic model was used to build a mathematical model. Normality test of residuals showed that the regression model was more robust to predict cohesion than to use flow factor. Conclusion This QbD approach is shown to be useful for predicting flow performance and finding design space during formulation development.

Purpose The shear cell test has been widely used to characterize flow properties of powders and granular materials. The purpose of this study is to address the gap between the extensive usage of the test and the limited methods available to analyze the data, and to introduce methodologies for comparing results for different initial consolidation stresses, materials, and testing devices. Method A library of shear cell data was established. Forty-one powders were included, and each material was tested under four different initial consolidation stresses. For each initial consolidation stress, 3 sampling replicates were performed. Results A dimensionless cohesion, C*, was defined as the cohesion divided by the initial consolidation stress. By identifying a correlation between the flow function coefficient (ffc) and C*, the effects of the initial consolidation stress and the testing device were separated. In addition, by identifying a mathematical correlation between the unconfined yield strength and the cohesion, the yield loci from different initial consolidation stresses could be collapsed into a single material characteristic line, enabling one to characterize each material by a single number (the characteristic slope). This approach can be used to economically compare different materials, or different testing devices. Conclusion The proposed method augments shear cell data analysis and significantly reduces the complexity of the shear cell data.

The objective of this work was to study the granulation behavior of three different types of zirconium hydroxide, each varying in particle size and density. Different concentrations of yttrium (III) nitrate hexahydrate (Y(NO 3 ) 3 ·6H 2 O) solutions were used as a doping agent and also acted as binder. Experiments were performed using a high shear wet granulation process by adjusting two parameters, 1. liquid to solid mass ratio and 2. impeller speed, to obtain four parameter settings (referred as bounds in the paper) for a two factorial design of experiment for each powder. To understand the granule growth behavior, a regime map analysis using the growth regime map first proposed by Iveson and Litster (1998) , was carried out on the bounds. The granule growth behavior observed experimentally was compared with the regime map results. Different growth behavior was observed for different powders. Furthermore, an attempt was made to obtain a steady growth for those parameter settings that initially resulted in an induction growth. A surfactant, SDS (Sodium dodecyl sulfate), was used to improve the wetting properties of the powder and its addition to the binder solution resulted in a steady growth that is more controllable for granulation manufacturing operations compared to induction growth.

Rotating drums are encountered in numerous industrial applications, including blenders, rotary calciners, impregnators, coaters, granulators, and cement mixers. In all of these devices, the rotation of the drum is used to engender mixing of the granular material in the radial direction. Axial mixing, because of its significantly lower rate, can also have an impact on the process performance, especially when control of residence time is important. Typically, the particle dynamics in rotating drums are quantified as a function of process conditions, such as rotation speed, fill level, and cylinder size. Particle properties are also important, but previous studies have largely been limited to the effects of particle size. In this work, the quantification of the axial particle dynamics has been expanded to include the effect of bulk flow properties by studying a number of cohesive powders. Fick's second law was found to describe the axial dispersion behavior of cohesive particles. Therefore, changes in behavior can be characterized using the axial dispersion coefficient. The effect of material flow properties was found to be statistically significant; the flowability of the material (as measured using bulk flow properties) correlated significantly to the axial dispersion coefficient. Partial least squares was used to determine that 95% of the variation observed in the axial dispersion coefficient measurement can be explained using particle size, compressibility, and shear cell measurements.

This paper compares the micro-mixing dynamics of three active pharmaceutical ingredients (APIs) varying in particle size, bulk density and cohesion. Chlorpheniramine maleate, acetaminophen and caffeine, in a common blend of excipients, were used in this study. Micro-mixing was studied in a 1-L bin-blender using in-line near infrared chemical imaging (NIR-CI) to monitor the aggregate size distribution of the APIs and excipients. A science-based calibration chemometric method was used to calculate the concentration maps of ingredients in the blends. Chlorpheniramine maleate, smallest in particle size with lowest bulk density, resulted in the highest relative standard deviation (RSD) for all concentrations. The RSDs obtained for acetaminophen and caffeine were similar and dependent on their concentrations. Chlorpheniramine remained in large aggregates throughout the blending process. Overall, other ingredients (e.g. Avicel) required longer blending times to become well dispersed in the presence of chlorpheniramine maleate, as evidenced by the aggregate size measurements. This in-line NIR-CI technique was able to approximate the number of API aggregates and their size during a common blending process. Although further development of this technique is necessary, metrics measured using this technique could potentially be used as a critical quality attributes during pharmaceutical processing.

Looking for a way to measure residence time distributions of an 80 micron fluidized cracking catalyst (FCC) powder, a simple measurement technique was discovered that quantifies tracer color concentration. Using a color spectrophotometer that measures percent reflectance as a function of wavelength, a calibration curve can be constructed for standard mixtures of dyed and un-dyed powder. This calibration curve can then be used to determine the color concentration of an unknown sample by measuring its reflectance. The effects of operating parameters such as dye strength, aperture size, surface roughness, sample volume and depth, and continuous flow were all evaluated. This spectrophotometric technique was found to be a quick and simple way to measure colored mixture concentrations. In addition to being ideal for residence time distribution applications, it has the potential to easily quantify mixing in any unit operation, batch or continuous.

Continuous powder processing requires accurate and consistent feed streams of the raw materials which makes loss-in-weight feeders invaluable. Periodic hopper refill of the feeders, which is needed for continuous operation, can lead to inconsistent and poor feeding performance. This paper presents both a method for measuring the feeding performance during hopper refill as well as several methods for quantifying the resultant deviations from feedrate setpoint caused by refill. The main results show that hopper fill level is the most significant factor that can be used in mitigating the deviations effects during refill. The use of discharge screens also showed a small improvement in feeding accuracy. Another potentially useful method of reducing deviations during refill is to use refilling systems that have a lower more controlled rate of refill that gently replenishes the feed hopper rather than the high rate refill of some refilling systems.

Developed to aid in the design of hoppers and silos, the shear cell is now frequently used to rank the flowability of powders relative to one another. While standards, such as ASTM D6773 and D6128, exist for shear cell tests, there are still differences between commercially available shear cell testers, such as cell geometry and size. In this work, we used two materials, a free-flowing alumina and a cohesive alumina, to compare measurements from three commercially available rotational shear cells. Results were collected and compared for cohesion, unconfined yield stress, major principal stress, pre-shear stress, flow function coefficient, bulk density, effective angle of internal friction, and the angle of internal friction. ANOVA methods were used to determine the statistical significance and relative size of each of these effects. This work has found that while, as expected, the material type has the largest effect on the shear cell results, the consolidation at which the material was tested and the tester type are also statistically significant effects. These results indicate that care should be taken when comparing the results between different shear cells.

An experimental study was performed to characterize two continuous mills for their ability to mill alumina–magnesia extrudates. The effect of mill parameters, namely, the screen aperture size, and impeller speed on the particle size distribution of the milled product was quantified for a conical screen mill and a hammer mill. In general, the conical screen mill was found to be more sensitive to changes in impeller speed compared to the hammer mill. The effect of impeller speed in case of the hammer mill was non-monotonic while the increasing speeds led to reduction in particle size in case of the cone mill, for the same screen aperture size. The effect of aperture screen size was observed to play a dominant role in dictating particle size distribution of the product material for both mills. In case of the cone mill, grated type screens exhibited higher milling capacity than round screens with equivalent apertures. Lastly, a study comparing the statistical particle size distribution parameters was performed for process design purposes. It was deduced that, if the desired particle size is greater, the comil provides a narrower particle size distributions than the hammer mill; whereas if the desired particle size is smaller, both mills exhibit similar poly-dispersity. The study provided insight into fundamental breakage mechanisms for both mill classes. Breakage in the hammer mill occurs primarily due to the impact of the hammers and large particles may often leak through the mill without sufficient breakage. Breakage in the comil is more gradual as the impeller sweeps a wide area generally ensuring sufficient breakage of particles before they exit the milling chamber.

An experimental investigation was carried out to study the mixing performance of a laboratory-scale ResonantAcoustic® Mixer (LabRAM). The first part of the study summarizes the results of a fractional factorial design of experiments used to determine the main effects of process parameters (fill level, acceleration, and blending time) on blend homogeneity. Studies were carried out for several blends having various values of particle size, cohesion and concentration of the active pharmaceutical ingredient. The second part of the study describes the LabRAM mixing performance as a function of process parameters (fill level and acceleration) and total blending time. The blend homogeneity was quantified by estimating the relative standard deviation (RSD) for low concentration of active pharmaceutical ingredient (acetaminophen, 3% w/w) and lubricant (magnesium stearate, 1% w/w) blend. Overall, the LabRAM reached the minimum blend homogeneity in as low as 30 s depending on process parameters. The temperature of the final blend increased with fill level, time and acceleration. Resonant acoustic mixing can significantly reduce blending time, making it a good candidate for improving the efficiency of powder mixing processes.

The objective of the current work was to investigate the effect of liquid to solid ratio (L/S), impeller speed and the wet massing time on the critical quality attributes of granules in a high shear wet granulation process for a two component (API and excipient) system. The parameters were evaluated for their effect on granule properties using a design of experiment based approach. Granules were characterized for their particle size distribution, content uniformity, morphology and porosity. The liquid to solid (L/S) ratio was found to have a dominant effect on the median particle size and exhibited a clear trend. The system was found to be extremely well mixed for all conditions thus implying robust composition uniformity within and between batches, independent of process parameters. The release kinetics of granules within the batch were found to be identical, independent of particle size. The granules were found to be fairly spherical as observed through a scanning electron microscope with no distinct agglomeration. The images indicate granulation by layering and consolidation. All three process parameters were found to have an effect on granule porosity, with the wet massing time having the most pronounced effect. A judicious selection of the afore mentioned process parameters will enable a balance between granule growth and porosity to be achieved without compromising on the mixing efficiency of the process thereby allowing one to build quality into the final product.

Tablet compression has great significance in the pharmaceutical industry since most of the drugs are in the tablet dosage form. The tablet press feed frame is used to fill powder into the empty dies. Die filling is one of the key steps to control final properties of tablets. Using the Discrete Element Method (DEM), a standard feed frame taken from a Manesty Betapress was simulated which represents the tableting process without the compression stage. DEM was used to understand the micro-macro dynamics of the particles inside the feed frame. Segregation behavior of a single material with a particle size distribution was investigated using this method. The DEM simulation components included 2 paddle wheel speeds (24 and 72 rpm) and 2 die disk speeds (29 and 57 rpm). Results obtained have highlighted the effect of feed frames on the powder properties. The DEM results show size segregation inside the feed frame and during the die filling stage. Velocity profiles and particle vectors show that the percolation phenomenon is the most significant segregation mechanism. Paddle wheel speed was demonstrated to be the most important factor to control particle size segregation inside the feed frame.

A novel manufacturing strategy based on continuous processing integrated with online/inline monitoring tools coupled with an advanced control system is highly desired for efficient Quality by Design (QbD)-based pharmaceutical manufacturing. A control system ensures the predefined end product quality, satisfies the high regulatory constraints, facilitates real time release of the product, and optimizes the resources. In this work, a systematic framework for the onsite design and implementation of the control system in continuous tablet manufacturing process has been developed. The framework includes a generic methodology and supporting tools through which the control system can be designed at the manufacturing site and can be implemented for closed-loop operation. The control framework has different novel features such as the option to run the plant in closed-loop (MPC/PID), open-loop and simulation mode. NIR sensor, an online prediction tool, a PAT data management tool, and a control platform have been used to close the control loop.

The present study introduces a new in situ near-infrared chemical imaging technique (imMixTM) designed to characterize micro-mixing in pharmaceutical powder blends. The technique uses in-line, non-contact monitoring of the blending process, eliminating the bias introduced by commonly used powder sampling techniques. A Science-Based Calibration (SBC) chemometric method, which uses pure component spectral data to create a calibration model, was used to create concentration maps of the blends studied here. The advantage of SBC over the alternative Partial Least Squares (PLS) or Principal Component Analysis (PCA) calibration methods is that it does not require a large number of samples to create a calibration. The imMix system proved to be useful in monitoring the spatial distribution and aggregate sizes of acetaminophen, used as the model drug, and of excipients in the blends. Using a 1-l bin-blender, measurements were able to detect changes in the constituents and other experimental parameters as a function of blending time. Such measurements can be used to determine the mixing time and shear requirements of blends during product and process development.

This paper focuses on two aspects of continuous powder mixing, namely characterizing the effects of material properties on the bulk powder flow behavior, and developing continuous blending strategies suitable for cohesive materials. The relative effects of process parameters and material properties on the bulk powder flow behavior were analyzed by performing a PLS analysis of the output parameters, including mean residence time, and axial dispersion coefficient as a function of input parameters (impeller speed, flow rate, bulk density and cohesion). The mean residence time was primarily affected by the bulk density and impeller speed, whereas the axial dispersion coefficient was affected by impeller speed and cohesion. Based on previously developed knowledge of mixing performance as a function of process parameters [1] , a design rule to select the optimal number of impeller passes based on the bulk density was proposed. Impeller speed and cohesion showed a significant interacting effect on the output variable, the axial dispersion coefficient. Increase in cohesion leads to increase in the axial dispersion coefficient at higher impeller speeds, whereas a negligible effect of cohesion on the axial dispersion coefficient was observed at lower impeller speeds. In the second part of the paper, a continuous blending methodology for blending cohesive materials was demonstrated. Considering the feeding limitations of cohesive materials, and limitations in the application of shear in the bladed continuous mixer, a combination of high shear and low shear mixing with high-shear mixing as a first step exhibited an optimal mixing strategy.

Reduced-order modeling (ROM) techniques are playing a very significant role in the recent literature bridging the gap between computationally expensive simulators and their application in optimization and control of distributed parameter systems. In modeling of solid-based processes, Discrete Element Method (DEM) is a very popular high-fidelity modeling approach which enables the tracking of discrete entities as they are processed inside complex geometries interacting with each other and with process boundaries. However, the computational cost of DEM models limits their applicability to simulation of specific and limited number of cases. In this work, we develop the DE–ROM (Discrete Element–Reducer-order model) approach which reduces the computational cost—while maintaining model accuracy—of expensive DEM models. The proposed methodology is based on Principal Component Analysis (PCA), combined with surrogate-model mapping and data imputation for the cases where there is missing information. The results of the application of the developed method to the powder mixing process, demonstrate that the DE–ROM model produces accurate profiles of distributed particle properties in real time. Finally, the developed model is used for the identification of the optimal design and operating conditions of the mixing process.

Characterization of powder consolidation and flow is important to a large number of industries that process solids. A variety of powder testers exist today, however most are application specific and results they provide are mainly qualitative. Comparison studies have been attempted previously; their main focus was whether various methods correlate, while the reasons for disagreement in the results have seldom been investigated. Among the different methods used to characterize powder flow behavior, density-based methods are some of the simplest and most popular. They are also some of the least sensitive and least reproducible. A method comparison study was performed to characterize the variability in bulk density as measured by various powder flow characterization methods. It was found that the density of the powders tested in most unconsolidated methods had a near-perfect linear correlation with one another, suggesting that there exists a critical “dilated” density value that is independent of the measurement method and can be considered a material property. The densities of the powders in consolidated states correlated poorly, especially for the methods where consolidation mechanisms were not tightly controlled (i.e. tapping). In addition, the effect of the consolidation state of the powder bed during testing on cohesion measurements was studied. The cohesion measured by shear cells at differing consolidation states and by an avalanching method, during which the powder bed is dilated, were compared. It was found that the differences in cohesion results from the shear cells tested can be attributed to differences in the powder consolidation state. Cohesion results acquired from a dilated powder bed correlate more linearly with the shear cell cohesion results at low consolidation stresses than at high consolidation stresses; further supporting the impact of the powder bed packing state on the measurement of cohesion.

Continuous powder mixing has attracted a lot of interest within the pharmaceutical industry. Much work has been done recently that targets the characterization of continuous powder mixing. In this paper, a quantitative scaling up strategy is introduced that allows the transition from lab to industrial scale. The proposed methodology is based on the variance spectrum analysis, and the residence time distribution, which are key indexes in capturing scale-up of the batch-like mixing, and scale-up of the axial mixing and motion, respectively. Our simulation results are used as preliminary guidance for scaling up different powder mixing cases.

Pharmaceutical powder processing is notoriously subject to unpredictable jamming, sticking and charging disturbances. To unveil the material science underlying these effects, we use atomic force microscopy (AFM) on a common pharmaceutical, acetaminophen (APAP). Specifically, we study surface adhesion and morphology as a function of relative humidity (RH) for monoclinic acetaminophen, using both plain AFM tips and tips functionalized to be hydrophobic or hydrophilic. Results indicate that the (0 0 1) crystal face exhibits significantly higher adhesion (surface potential) than the other crystal faces. For all the faces clear peaks in adhesion occur at 50–60% RH when they are examined using hydrophilic tips. The surface morphology of some facets showed a strong dependence on RH while others showed little or no significant change. In particular, the morphology of the (1 −1 0) faces developed large terraces at high humidity, possibly due to deliquescence followed by recrystallization. These results confirm the hypothesis that different crystal facets exhibit distinct surface potentials and morphology that change with environmental exposure. The work suggests that future studies of powder behaviors would benefit from a more detailed modeling of crystal surface contact mechanics.

Feed frame is a device used in rotary tablet presses to drive the powders into compression dies. It applies shear forces to the powders as they are stirred around the feed frame chambers. This study focused on understanding the particle attrition, powder properties and the flow property changes of the material processed. The results demonstrated that the impact of the feed frame and die disk on the particle size distribution (PSD) outlet depended on the initial mean particle size, the die size and the powder outlet position. It also impacted the flow properties. The scale-up effect using a feed frame for a high production tablet press shows a significant increment in powder attrition.

While continuous powder mixing has been an area of active research in recent years, effects of operating conditions on the mixing performance has not been well understood yet. Based on our previously developed periodic section modeling ( Gao et al., 2012 ), this paper examines the effects of operating conditions on two significant parameters of the continuous blending processes: axial velocity and local mixing rate of the mixture. Four mixing cases differing in particle size, density and cohesiveness are simulated. Results show that when the local mixing rate improves at low fill levels and high blade speed, particles also move faster in the axial direction and reside for a shorter time inside the mixer. This trade-off between ascending local mixing rate and descending residence time indicates a non-optimal overall blending performance even when the best operating condition is applied. Based on these results, strategies that can further improve the blending performance are performed, which are proposed by increasing the blade speed while keeping a constant axial velocity. These strategies guarantee that the variance decay rate along the mixing axis is proportional to the blade speed in continuous blending processes. Dramatic improvements are observed when these strategies are applied, which shows the merit of this work on design and optimization of continuous power blending processes.

This review traces current applications of the residence time theory in various solid unit operations. Besides reviewing recent experimental and simulation studies in the literature, some common modeling and tracer detection techniques applied in continuous flow systems are also considered. We attempt to clarify and emphasize the influence of the residence time profile on the unit performance, which is the key in system design and performance improvement of practical unit operations. The development of predictive modeling is also an important goal in the long-term development of the residence time theory.

This paper presents a method for evaluating the steady state performance of loss-in-weight powder feeding equipment and then demonstrates the use of the method in evaluating the performance of a K-Tron KT35 loss-in-weight feeder for three pharmaceutical grade powders. The method describes in detail the experimental setup, the procedure used in collecting feedstream data, and the filtering and subsequent analysis that is needed to determine differences in the steady state feeding performance. The data stream is shown to be a complex data set that can be simplified, after applying a suggested filtering and analysis algorithm, to two quantities (average feedrate and relative standard deviation) that can be used for comparison of different feeding treatments (powder, feeder tooling, and setpoint). Through analysis of variance (ANOVA), the significance of various tooling on optimizing feeder performance can be evaluated.

A computational study using the discrete element method was performed to study the effect of pan speed, fill level and the design of the spray pattern on the coating variability of tablets coated in a rotating pan. The method simulates the movement of tablets in the pan and calculates the residence time of each tablet inside the spray zone, which is directly related to the amount of coating received by the tablet. The computational method was experimentally validated using a Laser Induced Breakdown Spectroscopy based analytical method. The simulations showed that the axial mixing was the most critical parameter affecting the coating variability. Although axial mixing was found to be better at higher pan speed, it did not affect the coating variability significantly. Lower variability was obtained when a 100% fill level was used as compared to 67% fill. Four spray patterns were used, two idealized (full surface spray and a symmetric band spray) and two realistic (5-ellipse and 5-circular spray guns). The full and band spray showed similar results while the ellipse and circular patterns were similar to each other (and much worse than the other two patterns) at all speeds and fill levels.

A method comparison study was undertaken to characterize the effects of the formulation composition on the flow and shear properties of pharmaceutically relevant powders. Fourteen blends with various concentrations of an active ingredient, magnesium stearate as a lubricant and silica as a glidant were prepared. These blends were characterized with two very different techniques: the gravitational displacement rheometer (GDR), and a rotational shear cell. The values of GDR flow index were compared to the values of principal stresses and cohesion obtained with the shear cell. These measurements are different in that the GDR operates in the gravity-driven flow regime while the shear cell utilizes an imposed normal force, which leads to a much more pronounced powder consolidation. In spite of these differences, the study demonstrated a significant correlation between the two methods, although some discrepancies were observed due to differences in the consolidation state for each technique. This observation was confirmed by measuring compressibility of these formulations with the FT4 Powder Rheometer; the presence of a cohesive component influenced the values of the shear cell principal stresses (and therefore, the shear cell flow factor) in a non-linear manner, contributing to the discrepancies in the correlation between the flow factor and the GDR flow index. Conversely, the correlation between the shear cell cohesion parameter and the GDR flow index was significantly better, as both indices test the materials at similar degree of consolidation. The study examined the limits and the ranges of applicability of each technique, offered recommendations on applications, where the use of each method was more reliable, as well as provided reasons for the methods' failure.

An experimental investigation was carried out to study the mixing performance and flow behavior in a continuous powder mixer for a typical pharmaceutical mixture. Blender performance, characterized by the relative standard deviation (RSD) of composition of blend samples taken at the blender discharge and by the variance reduction ratio (VRR) of the blender, was measured as a function of impeller rotation rate, flow rate and blade configuration. The flow behavior in the continuous mixer was characterized using the residence time distribution (RTD) and powder hold-up measurements. To quantify the strain applied to the powder in the blender, the number of blade passes experienced by the powder in the blender was calculated using the residence time measurements. The relationship between different experimental parameters and mean residence time and mean centered variance was examined. The mixing performance was largely dominated by the material properties of the mixture, which had a larger effect than the ingredient flow rate variability contributed by the feeders. Holdup was strongly dependent on impeller rotation rate; as impeller rotation rate increased, holdup (and therefore, residence time) decreased sharply. As a result, intermediate rotation rates showed the best mixing performance. Blade configuration affected performance as well; blade patterns where some of the blades push the powder backwards improved the mixing performance.