Scaling up Wurster coating: preserving balance across critical process parameters

Spraying mechanics 

Maladjustment of spraying parameters can cause errors in different ways.

• Over-wetting results from large droplets; often due to high viscosity, high solids content, or low atomisation pressure. A high spray rate can further overload the system by outpacing drying capacity.

• Spray drying occurs when droplets evaporate mid-air – often due to fine droplets caused by high atomisation pressure, low viscosity, or a low nozzle height increasing droplet path distance. These conditions produce droplets with larger surface area per unit volume and longer residence in hot zones.

• Coating uniformity depends on cone geometry. A narrow spray angle improves column penetration but can cause localised overexposure. A wider angle improves distribution but must be matched to the right nozzle height to avoid coating loss or inadequate wetting.

Together, these parameters determine not just how well the coating is applied, but whether it even has a chance to form. Spraying sets the potential, but that alone means little unless it's synchronised with drying and circulation.

Drying capacity 

Drying is what locks the coating in place, turning liquid exposure into a stable film. But if drying is too slow, too aggressive, or mistimed, it triggers three major failure modes.

• Over-wetting: low inlet air temperature slows evaporation, leaving droplets tacky and prone to bridging. A high dew point lowers drying rate, and low air volume (or velocity) can cause inadequate solvent drying.

• Premature drying: when droplets dry in mid-air or before coalescence, they lose adhesion and film integrity. This happens when inlet air and product temperatures are too high, air volume is excessive, or the dew point is too low (creating overly dry air).

• Inconsistent coating: high product temperature can interfere with coating film coalescence and thus brittle coatings. For aqueous polymers, this risk rises sharply if temperature falls below the polymer's minimum film-forming temperature (MFT). A low dew point of inlet air can cause static charge accumulation and agglomeration with non-polar organic coatings, as there is not enough moisture for dissipation of static charge.

In short: drying isn't just about removing solvent. It's about doing so at the right place, at the right time.

Fluidisation and circulation 

Fluidisation and circulation keep the process in motion – literally. They enable particles to spray and dry consistently. But if airflow, fill level, or particle dynamics fall out of balance, the loop breaks.

• Agglomeration can occur due to high fill level that increases bed density, leading to wet collisions and bridging. It’s exacerbated by low inlet air velocity caused by a narrow annular gap that weakens fluidisation.

• Premature drying is less typical here but can occur if airflow is too high. Excessive inlet air volume or velocity can dry coating droplets too fast or even mid-air.

• Inconsistent coating is the most common failure caused by misalignment. Wide particle size or density distributions lead to irregular circulation times. Underfilled beds can allow excess turbulence. Greater partition height enables excess up flow of air into the down-bed region, thereby reducing the pressure differential across the partition and weakening particle draw-in into the spray zone. A shorter partition improves draw-in strength but can shorten exposure.

Pressure drop across the distributor plate serves as a key diagnostic signal: sudden drops may indicate bed collapse, while gradual ones often point to entrainment. Stable circulation relies on carefully scaled airflow, a narrow PSD, and consistent draw-in strength.

Once these dynamic forces are understood, the next step is knowing which parameters to fix – and which to scale.

Parameters to fix during process development 

Before scale-up begins, some key parameters can be locked with minimal revisions required. Once set, the focus can shift to variables that scale-up is actually sensitive to.

1. Air distribution plates

Orifice plates are selected based on the column size and particle size range¹:

2. Atomisation air pressure

While spray rate and nozzle diameter vary with scale, droplet size and atomisation air pressure should be optimised by the end of development trials.

3. Dew point, inlet air temperature and product temperature

These values are typically fixed across batches to preserve drug release, coating integrity, and film coalescence. While minor adjustments may occur at scale due to mass effects, significant changes should be made only with validated justification.

In short: these are not scale-up levers – they’re scaffolding. Get them right early, and the rest becomes manageable.

Scaling up

Equipment selected must be geometrically similar across scales, so that linearity of variables can be established during scale up.

Mathematical relationships³:

• To maintain linear air velocity:
  V = L × A
  V1 / A1 = V2 / A2
  (V = volume of inlet air; L = linear air velocity; A = column cross-sectional area)

• To preserve spray rate relative to drying capacity:
  S1 / S2 = A1 / A2
  (S = spray rate; A = column cross-sectional area)

The recommended partition height is 15-25 mm for 6″ columns, 40-50 mm for 18” ones¹. During coating, it may rise gradually as particle diameter grows.

Even with mathematically correct scaling, increased batch mass can alter heat and moisture dynamics. Expect small iterative adjustments, especially in early pilot batches.

Particle experience: insights from research

While atomisation pressure is often increased with spray rate to maintain droplet size, this adjustment carries risks. Higher droplet momentum increases the likelihood of core attrition and fine generation¹, especially near the nozzle – where larger particles are observed to linger longer⁴.

Simulation-based investigations show that residence time and cycle time distributions are primary determinants of coating uniformity. Larger particles exhibit longer residence and cycle times in the spray zone than small particles – meaning they receive more coating per pass, but traverse the spray zone less frequently⁶. These large particles move closer to the nozzle, disrupting uniformity of droplet deposition and shielding smaller particles from exposure⁷. This inconsistency is exacerbated by recirculation, where particles re-enter the coating zone against the air current, introducing high variability in residence time⁵.

A simulation validated by PEPT data showed that inlet airflow rate and the Wurster column height govern the variance in particle trajectories and time spent in the spray zone⁸.  Thus, these two parameters are the most influential levers to control such variability across scales. Improper scaling of either can widen coating disparities.

Solvent evaporation rate has been shown to be the most sensitive to inlet air temperature, while air flow rate predominantly influences coating yield⁹. Optimising these along with spray rate is shown by a CFD-DEM study to significantly reduce spray drying losses and cut process times.

Conclusion

Wurster coating is scalable – but only when the particle’s experience is preserved across batches. Focus on preserving process dynamics, not just the values. If spraying, drying, and circulation are in sync, your process will scale with confidence.

References:

1. Sonar, Girish. (2015). Wurster technology: Process variables involved and Scale up science. Innovations in Pharmacy and Pharmaceutical Technology.

https://www.researchgate.net/publication/316734542_Wurster_technology_Process_variables_involved_and_Scale_up_science

2. ACG. (2023). Wurster process scale-up - From A to Z. YouTube.
https://www.youtube.com/watch?v=SyP5TC-LXWc

3. Kalra A., Pathak C. & Hollis C. (2018). Technical note scale-up of Wurster process at Catalent Winchester. Catalent. 

https://www.catalent.com/expert-content/oral-technologies/scale-up-of-wurster-process-at-catalent-winchester/

4. Song, Y., Zhou, T., Bai, R., Zhang, M., & Yang, H. (2023). Review of CFD-DEM Modeling of Wet Fluidized Bed Granulation and Coating Processes. Processes, 11(2), 382.
https://www.mdpi.com/2227-9717/11/2/382

5. Jiang, Zhaochen & Bück, Andreas & Tsotsas, Evangelos. (2017). CFD-DEM study of residence time, droplet deposition and collision velocity for a binary particle mixture in a Wurster fluidized bed coater. Drying Technology. https://www.researchgate.net/publication/314749924_CFD-DEM_study_of_residence_time_droplet_deposition_and_collision_velocity_for_a_binary_particle_mixture_in_a_Wurster_fluidized_bed_coater

6. Li, L., Rasmuson, A., Ingram, A., Johansson, M., Remmelgas, J., von Corswant, C. and Folestad, S. (2015), PEPT study of particle cycle and residence time distributions in a Wurster fluid bed. AIChE J., 61: 756-768.
https://aiche.onlinelibrary.wiley.com/doi/full/10.1002/aic.14692

7. Li, Liang & Remmelgas, Johan & Wachem, Berend & Corswant, Christian & Johansson, Mats & Folestad, Staffan & Rasmuson, Anders. (2015). Residence time distributions of different size particles in the spray zone of a Wurster fluid bed studied using DEM-CFD. Powder Technology. 280. https://www.researchgate.net/publication/276165022_Residence_time_distributions_of_different_size_particles_in_the_spray_zone_of_a_Wurster_fluid_bed_studied_using_DEM-CFD

8. Böhling, Peter et al. (2019). Computational Fluid Dynamics-Discrete Element Method Modeling of an Industrial-Scale Wurster Coater. Journal of Pharmaceutical Sciences, Volume 108, Issue 1, 538 – 550.

https://jpharmsci.org/article/S0022-3549(18)30616-6/fulltext

9. S. Madlmeir, T. Forgber, M. Trogrlic, D. Jajcevic, A. Kape, L. Contreras, A. Carmody, P. Liu, C. Davies, A. Sarkar, J.G. Khinast. (2022). Quantifying the coating yield by modeling heat and mass transfer in a Wurster fluidized bed coater. Chemical Engineering Science, Volume 252, 117505.
https://www.sciencedirect.com/science/article/pii/S0009250922000896