Application of chaos analysis to pressure fluctuation data from a fluidized bed dryer containing pharmaceutical granule

Chaplin, Gareth; Pugsley, Todd; Winters, Conrad

doi:10.1016/j.powtec.2004.05.001

Cited by 50 publications

(32 citation statements)

References 16 publications

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“…Insensitivity in the S-statistic to changes in particle size distribution was noted by Chaplin et al 10 where reduced sensitivity to changes in particle size distribution in the S-statistic at superficial gas velocities >2.8 m/s was observed in the same GPGC1 unit operated as a dryer. In Figure 3, it can also be noted that the S-statistic is initially >3 followed by an immediate drop to a consistent state within 2 min of the start of the experiment.…”

Section: Resultsmentioning

confidence: 75%

“…10,11 This technique was calibrated for the optimum test parameters as described previously, 10,11 and the optimum parameters were found to be identical to those found for the drying of pharmaceutical granule in this fluidized bed unit. The pressure time series collected during the granulation process was broken into evaluation data sets lasting 1 min.…”

Section: Discussionmentioning

confidence: 88%

“…Previously, an evaluation time series of 2 min was used for each S-statistic value. 10,11 The shorter evaluation time series of 1 min was selected to track the rapid changes observed in this process. It has been determined that the use of time segments of 1 min did not affect the performance of the test.…”

Section: Discussionmentioning

confidence: 99%

“…8 The chaos analysis technique, denoted as the S-statistic, represents a statistical comparison between 2 bed states described by chaotic attractors reconstructed from separate time series of pressure fluctuations. 9 The S-statistic has been applied to pressure fluctuations collected in the drying of pharmaceuticals by Chaplin et al 10,11 In the current study, we apply the S-statistic test to pressure fluctuations collected in a fluidized bed granulator used for the production of pharmaceuticals.…”

Section: Introductionmentioning

confidence: 99%

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Monitoring the fluidized bed granulation process based onS-statistic analysis of a pressure time series

2005

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Pressure fluctuation measurements collected during the fluidized bed granulation of pharmaceutical granule have been analyzed using the attractor comparison technique denoted as the S-statistic. Divergence of the bed state from the reference during granulation is followed by a return to a condition statistically similar to the original state of the dry fluidized ingredients on drying. This suggests insensitivity of the S-statistic technique to the changes in particle size distribution occurring during the granulation process. Consequently, the monitoring of pressure fluctuations alone may provide an easily implemented technique for the tracking of granule moisture and process end-point determination.

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Section: Resultsmentioning

confidence: 75%

Section: Discussionmentioning

confidence: 88%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Monitoring the fluidized bed granulation process based onS-statistic analysis of a pressure time series

2005

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“…Different from conventional batch fluid bed drying processes where the drying endpoint is mainly determined by temperature-based monitoring methods [16][17][18][19][20], a fixed drying time for each cell of the segmented dryer unit was applied in order to retain the continuity of the system. LOD values obtained after drying of granules produced by the actual batch process were 1.77%, 1.93% and 1.91% for batch 1, 2 and 3, respectively (Table 1).…”

Section: Evaluation Of Granule Propertiesmentioning

confidence: 99%

Stability and repeatability of a continuous twin screw granulation and drying system

Vercruysse

Delaet

Assche

et al. 2013

European Journal of Pharmaceutics and Biopharmaceutics

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The aim of this study was to investigate the process transfer of a commercially available product from the current batch fluid bed granulation and drying production method to an innovative continuously operating 'from powder to tablet' production line using twin screw granulation as an intermediate granulation step. By monitoring process outcomes (torque, water temperature at the granulator jacket inlet, differential pressure over the dryer filters, temperature mill screen) and granule and tablet quality in function of process time, the stability and repeatability during long production runs were determined.Three consecutive 5h 'from powder to tablet' production runs were performed using the ConsiGma TM -25 system (GEA Pharma Systems, Collette TM , Wommelgem, Belgium). A premix of two active ingredients, powdered cellulose, maize starch, pregelatinized starch and sodium starch glycolate was granulated with distilled water. After drying and milling (1000µm, 800rpm), granules were in-line blended with magnesium stearate and directly compressed using a Modul TM P tablet press (tablet weight: 430 mg, main compression force: 12 kN).Granule (loss on drying, particle size distribution, friability, flow) and tablet (weight uniformity, hardness, thickness, friability, content uniformity, disintegration time and dissolution) quality was evaluated in function of process time.For each of the logged process outcomes, a stabilization period was needed to reach steady-state conditions. Slightly deviating particle size distribution and friability results for milled granules were observed during start-up due to initial layering of the mill screen.However, no deviating tablet quality was detected in function of process time.For multiple hours, granule and tablet quality was constant in function of process time. Furthermore, process data trends were highly repeatable. Consequently, the ConsiGma TM -25 system can be considered as a stable and repeatable system for the continuous production of tablets via wet granulation.

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Physical characteristics of fluidized beds via pressure fluctuation analysis

Hartman

Trnka

2008

AIChE Journal

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in Wiley InterScience (www.interscience.wiley.com).During various applications of gas fluidized units, the state/quality of the fluidized bed of solids can change due to changes in operation conditions or variations in the gas or solid feed. An analysis method is developed and applied which employs spectra of the fast Fourier transform of measured pressure fluctuations within the fluidized bed. The procedure is based upon the spectral analysis of successive time series of pressure fluctuations reflecting the actual hydrodynamic state (regime) of the bed. Practical application of the method is illustrated for fluidization at ambient temperature and pressure of spherical particles (glass beads) as well as irregularly shaped particles (limestone, sulfated limestone, and dried sewage sludge), in an 8-cm-ID fluidized bed. Using air, experiments were conducted with different fractions of the materials spanning a very wide range of 0.28-4.5 mm. The evolution was explored of bed behavior from the onset of fluidization to the pneumatic transport (elutriation) of solids from the bed. The method recognizes alterations of the hydrodynamic state of the bed caused by minor changes in the bed mass and/or in the granularity of the bed material.

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Application of chaos analysis to pressure fluctuation data from a fluidized bed dryer containing pharmaceutical granule

Cited by 50 publications

References 16 publications

Monitoring the fluidized bed granulation process based onS-statistic analysis of a pressure time series

Monitoring the fluidized bed granulation process based onS-statistic analysis of a pressure time series

Stability and repeatability of a continuous twin screw granulation and drying system

Physical characteristics of fluidized beds via pressure fluctuation analysis

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