Continuous mixing technology: Validation of a DEM model.

Continuous processing Mixing Physical characterization Powder technology Residence time Simulation Solid dosage form

Journal

International journal of pharmaceutics
ISSN: 1873-3476
Titre abrégé: Int J Pharm
Pays: Netherlands
ID NLM: 7804127

Informations de publication

Date de publication:
25 Oct 2021
Historique:
received: 24 06 2021
revised: 18 08 2021
accepted: 29 08 2021
pubmed: 5 9 2021
medline: 13 10 2021
entrez: 4 9 2021
Statut: ppublish

Résumé

Continuous powder mixing is an important technology used in the development and manufacturing of solid oral dosage forms. Since critical quality attributes of the final product greatly depend on the performance of the mixing step, an analysis of such a process using the Discrete Element Method (DEM) is of crucial importance. On one hand, the number of expensive experimental runs can be reduced dramatically. On the other hand, numerical simulations can provide information that is very difficult to obtain experimentally. In order to apply such a simulation technology in product development and to replace experimental runs, an intensive model validation step is required. This paper presents a DEM model of the vertical continuous mixing device termed CMT (continuous mixing technology) and an extensive validation workflow. First, a cohesive contact model was calibrated in two small-scale characterization experiments: a compression test with spring-back and a shear cell test. An improved, quicker calibration procedure utilizing the previously calibrated contact models is presented. The calibration procedure is able to differentiate between the blend properties caused by different API particle sizes in the same formulation. Second, DEM simulations of the CMT were carried out to determine the residence time distribution (RTD) of the material inside the mixer. After that, the predicted RTDs were compared with the results of tracer spike experiments conducted with two blend material properties at two mass throughputs of 15 kg/h and 30 kg/h. Additionally, three hold-up masses (500, 730 and 850 g) and three impeller speeds (400, 440 and 650 rpms) were considered. Finally, both RTD datasets from DEM and tracer experiments were used to predict the damping behavior of incoming feeder fluctuations and the funnel of maximum duration and magnitude of incoming deviations that do not require a control action. The results for both tools in terms of enabling a control strategy (the fluctuation damping and the funnel plot) are in excellent agreement, indicating that DEM simulations are well suited to replace process-scale tracer spike experiments to determine the RTD.

Identifiants

pubmed: 34481005
pii: S0378-5173(21)00871-1
doi: 10.1016/j.ijpharm.2021.121065
pii:
doi:

Substances chimiques

Powders 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

121065

Informations de copyright

Copyright © 2021 Elsevier B.V. All rights reserved.

Auteurs

Peter Toson (P)

Research Center Pharmaceutical Engineering, Inffeldgasse 13, 8010 Graz, Austria.

Pankaj Doshi (P)

Worldwide Research and Development, Pfizer Inc., Groton, CT, USA. Electronic address: Pankaj.Doshi@Pfizer.com.

Marko Matic (M)

Research Center Pharmaceutical Engineering, Inffeldgasse 13, 8010 Graz, Austria.

Eva Siegmann (E)

Research Center Pharmaceutical Engineering, Inffeldgasse 13, 8010 Graz, Austria.

Daniel Blackwood (D)

Worldwide Research and Development, Pfizer Inc., Groton, CT, USA.

Ashwinkumar Jain (A)

Worldwide Research and Development, Pfizer Inc., Groton, CT, USA.

Jenna Brandon (J)

Worldwide Research and Development, Pfizer Inc., Groton, CT, USA.

Kai Lee (K)

Worldwide Research and Development, Pfizer Inc., Sandwich, Kent, United Kingdom.

David Wilsdon (D)

Worldwide Research and Development, Pfizer Inc., Sandwich, Kent, United Kingdom.

James Kimber (J)

Worldwide Research and Development, Pfizer Inc., Sandwich, Kent, United Kingdom.

Hugh Verrier (H)

Worldwide Research and Development, Pfizer Inc., Sandwich, Kent, United Kingdom.

Johannes Khinast (J)

Research Center Pharmaceutical Engineering, Inffeldgasse 13, 8010 Graz, Austria; Institute of Process and Particle Engineering, Graz University of Technology, Inffeldgasse 13, 8010 Graz, Austria.

Dalibor Jajcevic (D)

Research Center Pharmaceutical Engineering, Inffeldgasse 13, 8010 Graz, Austria. Electronic address: Dalibor.Jajcevic@rcpe.at.

Articles similaires

Animals Dietary Fiber Dextran Sulfate Mice Disease Models, Animal
Humans Meta-Analysis as Topic Sample Size Models, Statistical Computer Simulation
Humans Algorithms Software Artificial Intelligence Computer Simulation
Humans Robotic Surgical Procedures Clinical Competence Male Female

Classifications MeSH