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Model development and prediction of particle size distribution, density and friability of a comilling operation in a continuous pharmaceutical manufacturing process

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Abstract
The comilling process plays an important role in solid oral dosage manufacturing. In this process, the granulated products are comminuted to the required size distribution through collisions created from a rotating impeller. In addition to predicting particle size distribution, there is a need to predict other critical quality attributes (CQAs) such as bulk density and tapped density, as these impact tablet compaction behavior. A comprehensive modeling approach to predict the CQAs is needed to aid continuous process modeling in order to simulate interaction with the tablet press operation. In the current work, a full factorial experiment design is implemented to understand the influence of granule strength, impeller speed and residual moisture content on the CQAs. A population balance modeling approach is applied to predict milled particle size distribution and a partial least squares modeling approach is used to predict bulk and tapped density of the milled granule product. Good agreement between predicted and experimental CQAs is achieved. An R-2 value of 0.9787 and 0.7633 is obtained when fitting the mean particle diameters of the milled product and the time required to mill the granulated material respectively.
Keywords
BIOMATH, Breakage, Conical screen mill, Population balance model, Partial least squares model, CONICAL SCREEN MILL, BREAKAGE, COAGULATION, SIMULATION, REDUCTION

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Citation

Please use this url to cite or link to this publication:

Chicago
Metta, Nirupaplava, Maxim Verstraeten, Michael Ghijs, Ashish Kumar, Elisabeth Schafer, Ravendra Singh, Thomas De Beer, et al. 2018. “Model Development and Prediction of Particle Size Distribution, Density and Friability of a Comilling Operation in a Continuous Pharmaceutical Manufacturing Process.” International Journal of Pharmaceutics 549 (1-2): 271–282.
APA
Metta, N., Verstraeten, M., Ghijs, M., Kumar, A., Schafer, E., Singh, R., De Beer, T., et al. (2018). Model development and prediction of particle size distribution, density and friability of a comilling operation in a continuous pharmaceutical manufacturing process. INTERNATIONAL JOURNAL OF PHARMACEUTICS, 549(1-2), 271–282.
Vancouver
1.
Metta N, Verstraeten M, Ghijs M, Kumar A, Schafer E, Singh R, et al. Model development and prediction of particle size distribution, density and friability of a comilling operation in a continuous pharmaceutical manufacturing process. INTERNATIONAL JOURNAL OF PHARMACEUTICS. 2018;549(1-2):271–82.
MLA
Metta, Nirupaplava, Maxim Verstraeten, Michael Ghijs, et al. “Model Development and Prediction of Particle Size Distribution, Density and Friability of a Comilling Operation in a Continuous Pharmaceutical Manufacturing Process.” INTERNATIONAL JOURNAL OF PHARMACEUTICS 549.1-2 (2018): 271–282. Print.
@article{8581904,
  abstract     = {The comilling process plays an important role in solid oral dosage manufacturing. In this process, the granulated products are comminuted to the required size distribution through collisions created from a rotating impeller. In addition to predicting particle size distribution, there is a need to predict other critical quality attributes (CQAs) such as bulk density and tapped density, as these impact tablet compaction behavior. A comprehensive modeling approach to predict the CQAs is needed to aid continuous process modeling in order to simulate interaction with the tablet press operation. In the current work, a full factorial experiment design is implemented to understand the influence of granule strength, impeller speed and residual moisture content on the CQAs. A population balance modeling approach is applied to predict milled particle size distribution and a partial least squares modeling approach is used to predict bulk and tapped density of the milled granule product. Good agreement between predicted and experimental CQAs is achieved. An R-2 value of 0.9787 and 0.7633 is obtained when fitting the mean particle diameters of the milled product and the time required to mill the granulated material respectively.},
  author       = {Metta, Nirupaplava and Verstraeten, Maxim and Ghijs, Michael and Kumar, Ashish and Schafer, Elisabeth and Singh, Ravendra and De Beer, Thomas and Nopens, Ingmar and Cappuyns, Philippe and Van Assche, Ivo and Ierapetritou, Marianthi and Ramachandran, Rohit},
  issn         = {0378-5173},
  journal      = {INTERNATIONAL JOURNAL OF PHARMACEUTICS},
  language     = {eng},
  number       = {1-2},
  pages        = {271--282},
  title        = {Model development and prediction of particle size distribution, density and friability of a comilling operation in a continuous pharmaceutical manufacturing process},
  url          = {http://dx.doi.org/10.1016/j.ijpharm.2018.07.056},
  volume       = {549},
  year         = {2018},
}

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