Investigation of the Electrokinetic Potential of Granules and Optimization of the Pelletization Method Using the Quality by Design Approach Article Swipe
YOU?
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· 2024
· Open Access
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· DOI: https://doi.org/10.3390/pharmaceutics16070848
The preparation of pellets using a high-shear granulator in a rapid single-step is considered a good economic alternative to the extrusion spheronization process. As process parameters and material attributes greatly affect pellet qualities, successful process optimization plays a vital role in producing pellet dosage forms with the required critical quality attributes. This study was aimed at the development and optimization of the pelletization technique with the Pro-CepT granulator. According to the quality by design (QbD) and screening design results, chopper speed, the volume of the granulating liquid, binder amount, and impeller speed were selected as the highest risk variables for a two-level full factorial design and central composite design, which were applied to the formula of microcrystalline cellulose, mannitol, and with a binding aqueous polyvinylpyrrolidone solution. The design space was estimated based on physical response results, including the total yield of the required size, hardness, and aspect ratio. The optimized point was tested with two different types of active ingredients. Amlodipine and hydrochlorothiazide were selected as model drugs and were loaded into an optimized formulation. The kinetics of the release of the active agent was examined and found that the results show a correlation with the electrokinetic potential because amlodipine besylate can be adsorbed on the surface of the MCC, while hydrochlorothiazide less so; therefore, in this case, the release of the active agent increases. The research results revealed no significant differences between plain and model drug pellets, except for hydrochlorothiazide yield percent, in addition to acceptable content uniformity and dissolution enhancement.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/pharmaceutics16070848
- https://www.mdpi.com/1999-4923/16/7/848/pdf?version=1719051535
- OA Status
- gold
- Cited By
- 1
- References
- 39
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4399969911
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4399969911Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/pharmaceutics16070848Digital Object Identifier
- Title
-
Investigation of the Electrokinetic Potential of Granules and Optimization of the Pelletization Method Using the Quality by Design ApproachWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-06-22Full publication date if available
- Authors
-
Azza A. Mahmoud, Alharith A. A. Hassan, Dorina Gabriella Dobó, Krisztina Ludasi, László Janovák, Géza Regdon, Ildikó Csóka, Katalin KristóList of authors in order
- Landing page
-
https://doi.org/10.3390/pharmaceutics16070848Publisher landing page
- PDF URL
-
https://www.mdpi.com/1999-4923/16/7/848/pdf?version=1719051535Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.mdpi.com/1999-4923/16/7/848/pdf?version=1719051535Direct OA link when available
- Concepts
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Response surface methodology, Pellets, Materials science, Central composite design, Fractional factorial design, Pelletizing, Microcrystalline cellulose, Factorial experiment, Process engineering, Quality by Design, Chromatography, Critical quality attributes, Design of experiments, Box–Behnken design, Hydrochlorothiazide, Composite material, Particle size, Chemical engineering, Chemistry, Mathematics, Cellulose, Engineering, Statistics, Radiology, Blood pressure, MedicineTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
-
2024: 1Per-year citation counts (last 5 years)
- References (count)
-
39Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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