Continuous wet granulation using a twin-screw extruder has attracted considerable attentions in pharmaceutical industry as it ensures consistent tablet quality at a high production rate. However, challenge still exists in controlling desired granule properties especially when different sized twin-screw granulators are used. This study therefore explored the potential of scalability of two sized twin-screw extruders and the how raw materials affect granules properties in two twin-screw extruders. The first study focuses on aspects of scaling using two twin-screw extruders, 18mm and 27mm. Dimensionless groups including Fr Number, Powder Feed Number and Degree of Fill (<30%) were studied to observe their influences on granule attributes. It was found that these dimensionless groups demonstrated inconsistent effects on granule properties and the effect of Powder Feed Number was highly dependent on Degree of Fill. Different extruder still exerts significant impact on granule properties. A scaling rule was established for median granule size (d50) only, but only moderate degree of fit was found. Although a considerable number of studies have been published on controlled-release and extended-release excipients, little attentions have been given to the influence of microcrystalline cellulose (MCC) grades in twin-screw wet granulation. The second study therefore investigated the processability of five grades MCC from the Avicel® PH family using two twin-screw extruders again, 18mm and 27mm. Granule attributes including particle size, density, moisture, and strength were tested and it was found that MCC inherent density has the most significant impact on granule properties while particle size of MCC has minor positive effect on granule size. This study also concluded that better granule flowability and uniformity can be achieved by using low moisture, larger particle size and high density MCC as excipients. / Thesis / Master of Applied Science (MASc)
| Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/27950 |
| Date | January 2022 |
| Creators | Shi, Zequn |
| Contributors | Thompson, Michael, Chemical Engineering |
| Source Sets | McMaster University |
| Language | English |
| Detected Language | English |
| Type | Thesis |
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