C-SOPS, Department of Chemical and Biochemical Engineering at Rutgers, The State University of New Jersey

Douglas Hausner

Loss-in-weight (LIW) or gravimetric feeding is the most commonly used continuous feeding method for pharmaceutical powders (1–4). With the commercial adoption of continuous manufacturing of solid oral pharmaceutical dosage forms in recent years, there has been increasing focus on LIW feeding for these applications, looking at both equipment design and utilization within the process. Feeding is one of the most important unit operations within a continuous manufacturing process, and while this can be said regardless of the type of process (e.g., wet granulation, roller compaction, direct compression), it is most critical for continuous direct compression processes. In a direct compression process, the material attributes of the formulation ingredients being fed can have a major effect on the downstream process and attributes of the final product. Materials that are challenging to feed may lead to higher variability of the final product, or in extreme cases, the need to pause operations and attend to the feeder. Therefore, it is important that LIW feeder performance is optimized during process development, particularly for poorly flowing materials.

Previous work has demonstrated that the operational range of LIW feeders depends on the feeder size, tooling, and the attributes of the material being fed. Cohesive materials that tend to agglomerate or entrap air within the powder bed will have a narrower range of operation as compared to well-flowing materials. Additionally, irregularity in bed properties can result in unstable flow rates, and erratic mass flow behavior can be transferred down to successive unit operations downstream of the feeders (5–12) and to the final product. Recent work has been performed to correlate LIW feeder performance to material properties (13–16). Li 

 identified a correlation between the feedfactor for Coperion K-Tron KT-20 LIW feeders to conditioned bulk density obtained from the Freeman FT4 Powder Rheometer (13), and Escotet-Espinoza 

 found a similar correlation between conditioned bulk density and the feedfactor for a GEA Compact LIW Feeder (14). Escotet-Espinoza 

 also found that using principal component analysis (PCA), a correlation can be established between bulk material properties (e.g., free-flowing particles versus soft compressed agglomerates) and how the material discharges from the feeder (14). Tahir 

 also found correlation between bulk material properties and feeder performance using partial-least square regression and PCA similarity grouping of materials (15). The recent focus of research has further highlighted the need to understand and optimize LIW feeder performance for the further development of pharmaceutical continuous manufacturing processes of solid dose products (16).

Even though LIW feeder systems may seem simple in principle, the behavior of feed materials can be complex (3). Given their importance in a continuous pharmaceutical solid dose manufacturing process, LIW feeders need to be tested and validated during process development to understand the performance capabilities of a given material–feeder combination. The ability to feed powder consistently and continuously is a critical requirement of a continuous manufacturing process (17,18). This requirement becomes especially relevant when feeding APIs, which cannot always be selected based on their suitability for the process such as an excipient potentially can.

In this study, a previously defined method for characterizing and classifying materials was used to identify a range of materials, from poorly flowing through well flowing, for experimentation (18). Within this classification system, group 1 materials are poorly flowing with a tendency to stick to surfaces, group 2 materials have better granular flow and a lesser tendency to stick to surfaces, and group 3 materials are considered to be well flowing. These materials were then characterized so that their material properties could be used to determine the initial set-up of a LIW feeder. The feeder set-up was then optimized for each material, including the screw, screen, and configuration for refill.

Materials from the three groups were chosen for this investigation. Microcrystalline cellulose (MCC) (Avicel 102, DuPont) was a group 1 material. Another MCC (Avicel 101, DuPont), croscarmellose sodium (AcDiSol, DuPont), and Prosolv 50 (JRS Pharma) represented materials from group 2. Powder grade acetaminophen (Mallinckrodt), magnesium stearate (Mallinckrodt), and Lactose 450m (DFE Pharma) represented materials from group 3. The particle sizes (d10, d50, and d90) for all seven materials were obtained from a laser diffraction particle sizer (LS 13-320, Beckman-Coulter) with a tornado dry powder module. Aerated and tapped density were recorded from a tapped density test performed according to 

 <616> standard procedure (19) using an automated tap density measurement instrument (Autotap, Quantachrome). The Hausner ratio was calculated from the ratio of tapped density to aerated density. A rheometer (FT4, Freeman) was used to characterize the powder packing and flow properties. Compressibility, permeability, flow energy, and shear cell tests were performed according to the Freeman FT4 protocol. The conditioned bulk density (cBD), compressibility percent at 15 kPa normal stress (CP% at 15 kPa), and density at 15 kPa were obtained from the FT4 compressibility test. Permeability at 15 kPa was obtained from the FT4 permeability test. Basic flow energy (BFE) was obtained from the FT4 stability and variable flow rate test. Cohesion, unconfined yield strength (UYS), major principal stress (MPS), angle of internal friction (AIF), and flow function coefficient (FFc) were obtained from the FT4 3-kPa shear cell test. The material characterization values appear in 

The Compact Feeder (GEA) is a twin-screw, LIW feeder with an integrated refill system that is designed specifically for use in pharmaceutical applications. The small footprint design allows for a high number of units to be placed around the inlet of subsequent unit operations without the need for sloped hoppers or multiple feeding stages. The feeder is made up of two main sections: a swappable top section, which can be removed and replaced, consisting of the powder pump and hopper and a bottom section containing the load cell and servo motor used to drive the agitator and screws.

The feeder uses a 2.6-L flat-bottomed hopper with a four-blade agitator used to fill the screws. The agitator can either be flat or fitted with vertical bridge-breaker elements to prevent cohesive materials from bridging in the hopper. Typically, the feeder is expected to deliver mass flow rates accurately in the range of hundreds of grams per hour to tens of kilograms per hour. Delivery for different ranges is achieved by using change parts, such as different servomotor gearboxes (63:1, 235:1, and 455:1) and screw designs (10-mm and 20-mm concave).

The compact feeder uses an integrated refill system used to accurately and repeatably refill the feeder hopper with material. The refill system consists of a ball valve and hopper (either configured with a vacuum system or gravity feed). The ball valve volume can be changed by using inserts with final volumes of 1.6, 1.2, 0.8, and 0.4-L achievable. The refill volume is typically chosen based on the feedfactor profile for a given material. The feedfactor is the maximum amount of powder which can fit within the screw flight per unit time.

 The feeder was mechanically configured in its optimum set-up for each material and then filled to its maximum load with an expected volume of powder of 2 L after refill. The maximum load is a function of the expected refill volume and the bulk density as shown in 

In this work, the feeder was primed by running the screws until the mass flow rate of material leaving the screws was at a steady state. Steady state was confirmed by performing three static feed factors tests at a screw speed close to the screw speed required for the mass flow rate set-point and checking that the measured feed factor was reproducible . The feeder was then refilled back to its maximum load and then started under gravimetric control. After the screws ran empty, the feeder was stopped. The whole procedure was repeated in triplicate. The data were recorded directly from the programmable logic controller using software (TwinCat Scopeview, Beckhoff Automation).

 The refill system was configured in its optimum set-up for each material. The system was then filled to the specified maximum fill level. In order to test the reproducibility of the refill system, 10 refills were conducted, and the mass of each refill was recorded using an external balance. When the level fell below the specified minimum fill volume, the system was refilled manually back to the maximum fill volume. The mean and variability for the 10 refills were calculated for each material.

Different material classes with optimized feeders

Prior to use, LIW feeders need to be tested and validated to understand the performance capabilities of a given material–feeder combination. A feeder is first calibrated to obtain an initial feed factor, and then it is run, without interferences, for a given period of time. The feeder data are then analyzed to quantify the accuracy of mass flow rate dispensed by the feeder.

In this experiment, the standard hopper and standard impeller were used for the materials except magnesium stearate and acetaminophen. The baffled hopper was used with the asymmetric impeller for the magnesium stearate to break up the powder flow within the hopper. For the group 1 materials, magnesium stearate, lactose 450m, and powder-grade acetaminophen, a screen was used at the exit of the feeder screws. The screen creates a slight backpressure to improve uniformity of powder filling the screws and reduce any carving effects from the materials leaving the screws. A 2-mm mesh screen was used for magnesium stearate, whereas a 8-mm mesh screen was used for the lactose 450m and the powder-grade acetaminophen. Additionally, the gearbox, which dictates the maximum screw speed from a gear reduction of the motor speed, was varied based on the desired target set point. Higher gear reduction ratio is required for lower set points. Each set point was chosen based on an assumed weight percentage for each of the materials that was likely to occur in a given formulation with a total operational throughput of 50 kg/hr. For instance, the set point for powder-grade acetaminophen was calculated to be 5 kg/hr, assuming it would be 10 w/w% in a representative formulation. Therefore, a 63:1 ratio gearbox number was used for Avicel 101, Avicel 102, power-grade acetaminophen, and Prosolv 50; a 235:1 ratio gearbox number was used for lactose 450m; and a 455:1 ratio gearbox was used for AcDiSol and magnesium stearate. Concave screws with a 20-mm pitch were used for Avicel 101, Avicel 102, AcDiSol, Prosolv 50, Lactose 450, and powder-grade acetaminophen. Since the target throughput for magnesium stearate was very low, 10-mm pitch concave screws were used. The 10-mm pitch screws have a lower volumetric throughput than the 20-mm screws, resulting in better control of throughput at low set points. The conditions used for the feeder performance tests are shown in 

. All experiments were performed in a controlled environment with an average relative humidity of 33% and temperature of 19.7 °C.

For each material, the feedfactor calibration was performed three times, prior to each of the three runs, and the average and relative standard deviation (RSD) were calculated from the nine values. The calibration was performed to obtain the maximum throughput for the specific feeder, screw, and powder. The feeder was then filled and run until it was empty. The GEA control software can also calculate and record the feedfactor in bins, separated by every 10% of hopper fill. All feedfactor data appear in 

. For all materials, the feedfactor decreases as the hopper fill diminishes; the decrease is more pronounced for different types of materials, due to the flowability and the head pressure of the powder sitting above the screws. Prosolv 50 and AcDiSol maintained a consistent feedfactor throughout the run, with a feedfactor above 90% of the initial feedfactor. Avicel 102 and Avicel 101 maintained a feedfactor above 90% of the initial feedfactor, down to 10% fill; however, noticeable change occurred in the final 10% hopper fill. The group 1 materials showed more significant changes in feedfactor than both groups 2 and 3. Lactose 450m and powder-grade acetaminophen maintained 90% of the initial feedfactor until 40% hopper fill. Below 40%, both feedfactors decreased significantly, with Lactose 450m ending with a feedfactor that was 63% of the initial feedfactor, and powder-grade acetaminophen ending with a feedfactor that was 44% of the initial feedfactor. Magnesium stearate showed the most significant decrease in feedfactor, dropping below 90% initial feedfactor at 50% hopper fill and ending with a feedfactor that was 58% of the initial feedfactor. The changes in feedfactor assist the user with determining when a refill should occur, as the refill should be performed prior to significant changes in feedfactor.

From the one-second interval feeder data of the complete dispensing of each of the powders, the average, standard deviation and RSD were then calculated for the mass flow and screw speed. The theoretical weight percent, set point, average mass flow rate, mass flow rate RSD, average screw speed, and the screw speed RSD are presented in 

 show that the feeder accurately dispenses the mass flow on target with high consistency. The feeder mass flow RSD values for all materials were less than 4%, whether the material was from group 1, 2, or 3. The most change observed was for the feeder screw speed when dispensing magnesium stearate. This value shows that there is a change in bulk density of the magnesium stearate because the screws had to change speed more frequently than for the other materials. However, even with the changing in screw speed, the feeder was able to accurately meet the target of 0.1 g/s with a mass flow RSD below 2%.

The refill system was set up for an optimal discharge for each material. Based on past experimental experience with acetaminophen, the straight hopper was used for powder-grade acetaminophen because it results in less bridging. For the remaining six materials, the Volkman hopper type was used. Each hopper type had a vibration unit attached, which was controlled by an air supply with 2 Bar of pressure and run from 3 to 5 seconds after each refill.

To characterize the consistency of powder refill, each material was dispensed 10 times, and the mass recorded for each instance was used to calculate an average mass and RSD (see 

). For the majority of the materials tested, the RSD was below 1%. Magnesium stearate and powder-grade acetaminophen had the highest RSD values of 2.7 and 5.5%, respectively, which was to be expected due to the more cohesive nature of these materials. However, in our experience, these values of mass flow rate RSD are small to moderate and easily handled by typical continuous blenders.

For successful and robust process development of sold-dose products by continuous pharmaceutical manufacturing, LIW feeders need to be tested and validated to understand the performance capabilities of a given material–feeder combination. The authors have demonstrated a robust process for testing individual materials in LIW feeders to obtain the ideal configuration and operational parameters that will provide the minimal RSD and refill perturbation at the exit of the feeder. A range of materials were selected, including challenging compounds that are not well flowing. Under the optimized conditions, nearly all of the materials were fed with acceptable RSD values. 

Because the unit operations downstream of the LIW feeders within the process will influence the RSD of the final product, it remains important to consider the LIW feeder operational RSD as well as the refill perturbation of each ingredient in combination with these downstream unit operations. Continuous blending will typically follow feeding within one or two unit operations and can serve to further mitigate feed-rate variations and disturbances (20,21). This mitigation is particularly important for poorly flowing group 1 materials within this study, such as powder-grade acetaminophen and magnesium stearate.

Overall, the proper set-up and optimization of a given feeder–material combination will ensure that the most robust continuous pharmaceutical sold-dose manufacturing process is developed. The proper time and effort should be put into examining feeder performance as early as possible during process development. While it may be difficult to do this examination for APIs based on available quantity and associated cost, it should be feasible to test excipients early on and include feedability as one of the criteria for their selection for a continuous process.

J.G. Osorio et al., “Continuous Powder Mixing,” in 

, P.J.Cullen, R.J. Romãnach, N. Abatzoglou, C.D. Rielly, Eds. (John Wiley & Sons, Ltd. Chichester, UK, 2015) pp 59-67.

D.H. Wilson and K.W. Bullivant, Loss-in-weight gravimetric feeder. Google Patents: 1986.

W. Engisch, M. Ierapetritou, and F. Muzzio, “Hopper Refill of Loss-in-weight Feeding Equipment,” 

Proceedings of the 2010 AIChE Annual Meeting

A.U.Vanarase, J.G. Osorio, and F.J. Muzzio, 

T. Li et al., Identifying a Loss-in-Weight Feeder Design Space Based on Performance and Material Properties. 

F. Tahir et al., Development of feed factor prediction models for loss-in-weight powder feeders. 

 General Chapter <616> Bulk Density and Tapped Density of Powders (2015).

S. Oka et al., “Design of an Integrated Continuous Manufacturing System” in 

Continuous Manufacturing of Pharmaceuticals, Advances in Pharmaceutical Technology

James Scicolone is research professor, and Douglas B. Hausner is associate director at C-SOPS, both at Rutgers, the State University of New Jersey; John Palmer is process modeling specialist at GEA; Andrew Birkmire is process development manager at GEA; James Holman is Technology Management director, Pharma Solids, at GEA. Fernando J. Muzzio* is director at C-SOPS and a Distinguished Professor at the Department of Chemical and Biochemical Engineering, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA, Tel.: +1-848-445-3357; fax: +1-848-445-6758, muzzio@soe.rutgers.edu.

*To whom all correspondence should be addressed.

 Supplement: APIs, Excipients, and Manufacturing
September 2020
Pages: 24–28

When referring to this article, please cite it as J. Scicolone et al., “Optimizing Loss-in-Weight Feeding of Poorly Flowing Materials,” 

Articles

Prior to use in a continuous manufacturing system for oral solid dosage forms, loss-in-weight feeders need to be tested and validated to understand the performance capabilities of a given material–feeder combination. In this article, the proper strategy for set-up and optimization of a loss-in-weight feeder is demonstrated for a range of materials. The optimized set-up of the feeders was demonstrated to provide suitable performance for even the most challenging, poorly flowing materials.

Optimizing Loss-in-Weight Feeding of Poorly Flowing Materials

Granular mixing can be generally classified either as macro-mixing or micro-mixing, based on the scale of mixing. Macro-mixing is defined as the macro-scale transport of particles or particle assemblies from one spatial coordinate to the other. Macro-mixing is responsible for most of the reduction in variance in unmixed powder streams. Micro-mixing is defined as mixing at the scale of a single particle. Micro-mixing is always associated with a change in the properties of individual particles (1).

	The role of micro-mixing becomes particularly important when it involves shear-sensitive ingredients, such as magnesium stearate or other lubricants, which are added to the formulation to reduce sticking in the tablet press. Magnesium stearate also improves the packing efficiency of coated materials (i.e., increased bulk density) and improves flow properties (2).

	Lubricants, however, can also cause problems in the formulation. Magnesium stearate, generally present as thin nanoparticles, is known to coat larger, shear insensitive excipients and active ingredients (3). This coating reduces the bonding ability of particles, and consequently causes a loss in the tabletability of the material (2). Magnesium stearate is also hydrophobic in nature, so coating active ingredient particles with magnesium stearate increases their hydrophobicity, resulting in a lower dissolution rate for the active ingredient (4, 5). 

	The coating extent of the shear-sensitive material and, consequently, its associated effects, are directly proportional to the total amount of strain experienced by the blend. The greater the strain, the more pronounced the extent of coating and, consequently, the more pronounced the associated effects (2–5).

	Close attention is thus paid to the extent of lubricant mixing in traditional batch manufacturing to ensure that the lubricant is not subjected to excessive strain levels during the blending operation. Typically, shear-sensitive ingredients are added in a second stage, after the mixing of other ingredients, to minimize the strain they experience. The bulk ingredients are blended for a few hundred revolutions in the blender before the lubricant is added to the system, and the lubricant is generally mixed for a few tens of revolutions.

	The design and operation of a continuous paddle blender differ significantly from that of a batch tumble blender. Moreover, the material is in the continuous blender for a much shorter time. In a continuous blending process, the material spends typically between a few seconds to a few minutes in the blender and experiences anywhere between 50 to a few hundred impeller revolutions (6).

	The number of impeller passes or revolutions is defined as follows:

	Number of impeller passes = τ (min) * impeller speed (rpm)

	where τ is the mean residence time of the material in the blender.

	How do strain levels differ in the continuous blender compared to the batch blender? The answer to this question will determine whether or not shear-sensitive ingredients must be added at a second stage.

	Comparison of strain energy in batch and continuous processes

	Razavi et al. (7) performed a study to quantify the amount of strain that the material experiences in a full-scale continuous process, and compared that to the strain resulting from a laboratory-scale batch blending operation. The researchers quantified the difference in the speed of sound in compressed tablets due to density differences between materials subjected to the variable degrees of strain. The authors found that the total amount of strain experienced by the material in a full-scale continuous process was less than that in a laboratory-scale batch operation.

	In this experiment, the continuous process was operated at a total mass flow-rate of 20 kg/hr. The continuous blender was run at 200 rpm, while the feed-frame was operated at 25 rpm. The material thus experienced strain in both the continuous blender and the feed-frame (7). The same material was blended in a laboratory-scale V-blender, with magnesium stearate, for 50 revolutions and compressed in a tablet press emulator. The tablet press emulator does not use a feed-frame to feed powder in compression dies. The powder processed by the batch operation is thus only subjected to strain during the batch blending operation. Despite the presence of the additional shear provided by the feed-frame in the continuous process, it was found that, overall, the material experienced less strain in the continuous process than it did in the batch blending operation (7).

	These results suggest that the amount of strain experienced by the material while it traverses a full-scale continuous blender is negligible compared to that experienced by the material in a laboratory-scale batch device. There are two reasons for this effect:

	Material in the continuous process spends a shorter amount of time in the equipment than it does in the batch process, and thus the total time of exposure to the shearing environment is much lower.

	The total mass of material in the continuous process, at any time, is significantly lower than it is in the batch process. A lower net mass results in lower consolidation and frictional stresses, leading to a lower overall degree of strain.

	Thus, the typical strain level in industrial-scale horizontal convective blenders is much lower than it is in benchtop batch devices, and most certainly lower than it is in full-scale batch blenders.

	Results also suggest that there needn’t be as much concern about potential over-lubrication in continuous blending operations, because they are gentler, so two-staged ingredient addition may not be necessary.

	It is also interesting to note that, in a continuous blender, the ratio of free volume in the system (i.e., volume not swept by the rotating blades) to the total blender volume is much smaller than it is in a batch blender (where the entire volume of the blender is considered free).

	The authors hypothesize that, in continuous blenders, a small amount of material is more uniformly subjected to the convective action of the blades, resulting in a more uniform nature of strain energy compared to what is found in batch systems.

	To quantify the effect of strain rate on blend properties, experiments were performed in which 300 g of material were subjected to 50, 100, 500, and 1000 revolutions with 1% magnesium stearate (w/w), in a modified continuous blender, albeit at different strain rates. The lubricity of the blend was quantified by measuring its contact angle with water, as described by Denesuk et al. (8).

	The blend consisted of 65% anhydrous Compap L acetaminophen and 34% Avicel PH-101, by weight. It was added to a Gericke GCM-250 continuous blender whose blades were adjusted such that they do not promote any axial motion of the material. The exit of the blender was sealed so that no material could leave the blender tube. Strain rates of 50, 150, and 250 rpm were investigated.

 shows the effect of the strain rate addition on the lubricity or hydrophobicity of the final blend. Blend lubricity is quantified as the cosine of the blend contact angle with water; a smaller cosine value indicates greater hydrophobicity. It can be observed that the blend hydrophobicity is not dependent on the rate at which strain is applied to the material, but only dependent on the total strain it experiences.

	The total amount of strain experienced by the in-process material in a batch tumbling blender is greater than that in a continuous paddle blender, under typical operating conditions. The higher strain experienced in batch processing necessitates the addition of shear-sensitive materials, such as magnesium stearate, at a later stage in the blending operation, resulting in two stages of ingredient addition. Two-stage addition may not be necessary in gentler continuous operations. The material experiences a more uniform degree of shear in a continuous blender compared to a batch blender.

	Lastly, the rate of strain addition (i.e., rotation speed) does not have an impact on the lubricity of the final blend. Lubricity depends only on the total amount of strain the blend experiences in either batch or continuous processing.

	Sarang Oka, Sara Moghtadernejad, Zhanjie Liu, Douglas Hausner and Fernando Muzzio* are all from the Department of Chemical & Biochemical Engineering at Rutgers, The State University of New Jersey, fjmuzzio@yahoo.com.

	*To whom all correspondence should be addressed.

	When referring to this article, please cite it as S. Oka, et al., "Lubrication in Continuous Tubular Powder Blenders," 

Shear-sensitive ingredients in a tableting formulation experience different conditions in a batch tumble blender than they would in a continuous paddle blender.