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Published on: February 3, 2023
Tabletability Flip in Dry Granulated Systems
Zijian Wang1, Chenguang Wang1, Tianxiang Gao1
1Department of Pharmaceutics, College of Pharmacy, University of Minnesota, Minneapolis, MN, 55455, USA.
The tabletability flip phenomenon (TFP) was investigated in dry-granulated formulations. Granule porosity and magnesium stearate levels critically influence TFP by affecting bonding area and strength, impacting tablet quality.
Area of Science:
- Pharmaceutical Sciences
- Materials Science
- Chemical Engineering
Background:
- The tabletability flip phenomenon (TFP) is observed in direct compression, where less deformable active pharmaceutical ingredients (APIs) show improved tabletability with excipients.
- The influence of granulation, specifically dry granulation, on TFP remains largely uncharacterized, necessitating further investigation.
Purpose of the Study:
- To explore the occurrence and underlying mechanisms of TFP in dry-granulated formulations.
- To evaluate the impact of granule porosity and magnesium stearate (MgSt) content on TFP.
Main Methods:
- Acetaminophen (APAP) and ibuprofen (IBU) were used as model APIs for dry granulation.
- Granules were prepared at two porosity levels (9% and 19%) by adjusting compaction pressure.
- Tabletability, bonding area (BA), and bonding strength (BS) were assessed with varying extragranular MgSt concentrations.
Main Results:
- Higher porosity granules (19%) exhibited TFP via fragmentation, similar to non-granulated blends.
- Lower porosity granules (9%) showed TFP governed by the interplay of BA and BS, with APAP maintaining TFP due to higher BS despite lower BA.
- Incorporating ≥1% MgSt reduced BS differences, eliminating TFP by favoring the higher tabletability of softer IBU granules.
Conclusions:
- The bonding area-bonding strength (BA-BS) framework effectively explains TFP in granulated systems.
- Controlling granule porosity and MgSt levels is crucial for optimizing tabletability in dry granulation.
- Understanding these factors is key to predicting and managing TFP in pharmaceutical manufacturing.
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