Closed-Loop Feedback Control of a Continuous Pharmaceutical Tablet Manufacturing Process via Wet Granulation
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The wet granulation route of tablet manufacturing in a pharmaceutical manufacturing process is very common due to its numerous processing advantages such as enhanced powder flow and decreased segregation. However, this route is still operated in batch mode with little (if any) usage of an automatic control system. Tablet manufacturing via wet granulation, integrated with online/inline real time sensors and coupled with an automatic feedback control system, is highly desired for the transition of the pharmaceutical industry toward quality by design as opposed to quality by testing. In this manuscript, an efficient, plant-wide control strategy for an integrated continuous pharmaceutical tablet manufacturing process via wet granulation has been designed in silico. An effective controller parameter tuning strategy involving an integral of time absolute error method coupled with an optimization strategy has been used. The designed control system has been implemented in a flowsheet model that was simulated in gPROMS (Process System Enterprise) to evaluate its performance. The ability of the control system to reject the unknown disturbances and track the set point has been analyzed. Advanced techniques such as anti-windup and scale-up factor have been used to improve controller performance. Results demonstrate enhanced achievement of critical quality attributes under closed-loop operation, thus illustrating the potential of closed-loop feedback control in improving pharmaceutical tablet manufacturing operations.
KeywordsProcess control Pharmaceutical Granulation Continuous processing Population balance model
Surface area (in square meters)
API composition (–)
Mean particle size (in meters)
PBM density function particles
Height (in meters)
Mass (in kilograms)
Compaction pressure (in megapascals)
Radius (in meters)
Relative standard deviation (–)
Residence time (in seconds)
Powder bulk density (in kilograms per cubic meter)
Material stress (in megapascals)
Rate (in particles per second)
Feeder rotation rate (in revolutions per minute)
Stress-angle empirical parameter
Feed frame disk
This work is supported by the National Science Foundation Engineering Research Center on Structured Organic Particulate Systems, through grant NSF-ECC 0540855. The authors would also like to acknowledge Pieter Schmal (PSE) for useful discussions.
- 1.Singh R, Boukouvala F, Jayjock E, Ramachandran R, Ierapetritou M, Muzzio F. Flexible multipurpose continuous processing of pharmaceutical tablet manufacturing process, GMP news, European Compliance Academic (ECE). 2012b. http://www.gmpcompliance.org/ecanl_503_0_news_3268_7248_n.html. Accessed 1 Jul 2013.
- 2.Salman AD, Reynolds GK, Tan HS, Gabbott I, Hounslow MJ. Handbook of powder technology, Chapter 21: Breakage in granulation, 2007;11:979–1040.Google Scholar
- 17.Ramachandran R, Arjunan J, Chaudhury A, Ierapetritou M. Model-based control loop performance assessment of a continuous direct compaction pharmaceutical processes. J Pharm Innov. 2012;6(3):249–63.Google Scholar
- 19.Singh R, Godfrey A, Gregertsen B, Muller F, Gernaey KV, Gani R, et al. Systematic substrate adoption methodology (SAM) for future flexible, generic pharmaceutical production processes. Comput Chem Eng. 2013;58:344–368.Google Scholar
- 27.Sen M, Dubey A, Singh R, Ramachandran R. Mathematical development and comparison of a hybrid PBM-DEM description of a continuous powder mixing process. J Powder Technol 2012a. doi: 10.1155/2013/843784.
- 33.Seborg DE, Edgar TF, Mellichamp DA. Process dynamics and control. 2nd ed. New York: Wiley; 2004.Google Scholar
- 42.Blevins T, Wojsznis, WK, Nixon M. Advanced control foundation: tools, techniques and applications. Research Triangle Park: International Society of Automation; 2013. ISBN: 978-1-937560-55-3.Google Scholar
- 43.Pawar P, Sullivan M, Heaps D, King E, Wang Y, Dendamrongvit W, Cuitino A, Muzzio FJ. Measurement of the effect of total shear and compaction force on tablet properties using terahertz pulsed spectroscopy: towards the prediction of dissolution rate. AIChE annual meeting, 404d, San Francisco, CA, 3–8 November, 2013.Google Scholar
- 45.Ziegler JG, Nichols B. Optimum settings for automatic controllers. Trans ASME. 1942;64:759–65.Google Scholar
- 46.Ogunnaike BA, Ray WH. Process dynamics, modeling, and control. New York: Oxford University Press; 1994.Google Scholar