Optimizing Loss-in-Weight Feeding of Poorly Flowing Materials

September 2, 2020
James Scicolone, Douglas Hausner, John Palmer, Andrew Birkmire, James Holman, Fernando Muzzio, PhD
Volume 2020 Supplement, Issue 4
Page Number: 24–28

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.

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

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 United States Pharmacopeia (USP) <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 Tables I and II.

Equipment

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.

Method

Feed-factor profile generation. 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 Equation 1:

m(max load)= ρBD·V(after refill)·1.2  [Eq. 1]

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).

Refill study. 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 Table III. 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 Table IV. 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 Table V. The results from Table V 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 Table VI). 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.

Conclusion

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.

References

  1. M.E. Crowley and A.M. MCrean, Eur. J. Parent. Pharm. Sci., 20 (2) 63–69 (2015).
  2. J.G. Osorio et al., “Continuous Powder Mixing,” in Pharmaceutical Blending and Mixing, P.J.Cullen, R.J. Romãnach, N. Abatzoglou, C.D. Rielly, Eds. (John Wiley & Sons, Ltd. Chichester, UK, 2015) pp 59-67.
  3. C.A. Blackshields and A.M. Crean, Pharm. Dev. Techn., 23 (6) 554–560 (2018).
  4. D.H. Wilson and K.W. Bullivant, Loss-in-weight gravimetric feeder. Google Patents: 1986.
  5. W. Engisch and F. Muzzio, J. Pharm. Innov., 11(1) 64–81 (2016).
  6. W.K. Hsiao et al., Drug Discovery Today, 25 (4), 800–806 (2020).
  7. W. Engisch and F. Muzzio, Powder Techol., 228, 395–403 (Sept. 2012).
  8. M. Hopkins, Measurement and Control, 39 (8) 237–40 (2006).
  9. R. Weinekötter and L. Reh, Particle and Particle Systems Charact. 12 (1) 46–53 (1995).
  10. W. Engisch, M. Ierapetritou, and F. Muzzio, “Hopper Refill of Loss-in-weight Feeding Equipment,” Proceedings of the 2010 AIChE Annual Meeting (Salt Lake City, UT, 2010).
  11. A.U.Vanarase, J.G. Osorio, and F.J. Muzzio, Powder Technol. 246, 63–72 (2013).
  12. W.K. Hsiao, Drug Discovery Today, 25 (4) 800–806 (2020).
  13. T. Li et al., Identifying a Loss-in-Weight Feeder Design Space Based on Performance and Material Properties. J. Pharm. Innov., 14 (2) (2019).
  14. M. Sebastian Escotet-Espinoza et al., Powder Technol., 339, 659–676 (2018).
  15. F. Tahir et al., Development of feed factor prediction models for loss-in-weight powder feeders. Powder Technol. 364, 1025-1038 (2020).
  16. S. Moghtadernejad et al., J. Pharm. Innov., 13 (2) 155-187 (2018).
  17. L. Pernenkil and C.L. Cooney, Chem. Eng. Sci., 61, 720-742 (2006).
  18. S.P. Simonaho et al., Eur. J. Pharm. Sci., 90, 38-46 (2016).
  19. USP, USP General Chapter <616> Bulk Density and Tapped Density of Powders (2015).
  20. W.Engisch and F. Muzzio, Pow. Technol., 283, 389–400 (2015).
  21. S. Oka et al., “Design of an Integrated Continuous Manufacturing System” in Continuous Manufacturing of Pharmaceuticals, Advances in Pharmaceutical Technology (Wiley, 2017), pp. 405-446.

About the authors

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.

Article Details

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

Citation

When referring to this article, please cite it as J. Scicolone et al., “Optimizing Loss-in-Weight Feeding of Poorly Flowing Materials,” APIs, Excipients, and Manufacturing Supplement (September 2020).

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