Material-Sparing Approach to Predict Tablet Capping Under Processing Compression Conditions Based on Mechanical and Molecular Properties Derived from Compaction Simulation and Crystal Structural Analysis.


Journal

AAPS PharmSciTech
ISSN: 1530-9932
Titre abrégé: AAPS PharmSciTech
Pays: United States
ID NLM: 100960111

Informations de publication

Date de publication:
10 Oct 2024
Historique:
received: 15 07 2024
accepted: 15 09 2024
medline: 11 10 2024
pubmed: 11 10 2024
entrez: 10 10 2024
Statut: epublish

Résumé

Present study evaluates the usability of compaction simulation-based mechanical models as a material-sparing approach to predict tablet capping under processing compression conditions using Acetaminophen (APAP) and Ibuprofen (IBU). Measured mechanical properties were evaluated using principal component analysis (PCA) and principal component regression (PCR) models. PCR models were then utilized to predict the capping score (CS) from compression pressure (CP). APAP formulations displayed a quadratic correlation between CS and CP, with CS rank order following CP of 200MPa < 300MPa < 100MPa, indicating threshold compression pressure (TCP) limit between 200 and 300 MPa, resulting in higher CS at 300 than 200 MPa regardless of increased CP. IBU formulations displayed a linear correlation between CS and CP, with CS rank order following CP of 100MPa < 200MPa < 300MPa, indicating TCP limit between 100 and 200 MPa, resulting in higher CS at 200 and 300 than 100 MPa regardless of increased CP. Molecular models were developed as validation methods to predict capping from CP. Measured XRPD patterns of compressed tablets were linked with calculated Eatt and d-spacing of slip planes and analyzed using variable component least square methods to predict TCP triggering cleavage in slip planes and leading to capping. In APAP and IBU, TCP values were predicted at 245 and 175 MPa, meaning capped tablets above these TCP limits regardless of increased CP. A similar trend was observed in CS predictions from mechanical assessment, confirming that compaction simulation-based mechanical models can predict capping risk under desired compression conditions rapidly and accurately.

Identifiants

pubmed: 39390268
doi: 10.1208/s12249-024-02950-3
pii: 10.1208/s12249-024-02950-3
doi:

Substances chimiques

Tablets 0
Ibuprofen WK2XYI10QM
Acetaminophen 362O9ITL9D
Excipients 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

238

Informations de copyright

© 2024. The Author(s), under exclusive licence to American Association of Pharmaceutical Scientists.

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Auteurs

Pratap Basim (P)

Arnold & Marie Schwartz College of Pharmacy and Health Sciences, Division of Pharmaceutical Sciences, Long Island University, 75 DeKalb Avenue, Brooklyn, New York, 11201, USA.
Natoli Institute for Industrial Pharmacy Research and Development, Long Island University, Brooklyn, New Jersey, USA.
Thermo Fisher Scientific, Cincinnati, Ohio, 45237, USA.

Harsh S Shah (HS)

Arnold & Marie Schwartz College of Pharmacy and Health Sciences, Division of Pharmaceutical Sciences, Long Island University, 75 DeKalb Avenue, Brooklyn, New York, 11201, USA.
J-Star Research Inc, Cranbury, New Jersey, 08823, USA.

Robert Sedlock (R)

Natoli Institute for Industrial Pharmacy Research and Development, Long Island University, Brooklyn, New Jersey, USA.
Natoli Scientific, Telford, Pennsylvania, 18969, USA.

Bhavin V Parekh (BV)

Arnold & Marie Schwartz College of Pharmacy and Health Sciences, Division of Pharmaceutical Sciences, Long Island University, 75 DeKalb Avenue, Brooklyn, New York, 11201, USA.
Natoli Institute for Industrial Pharmacy Research and Development, Long Island University, Brooklyn, New Jersey, USA.

Rutesh H Dave (RH)

Arnold & Marie Schwartz College of Pharmacy and Health Sciences, Division of Pharmaceutical Sciences, Long Island University, 75 DeKalb Avenue, Brooklyn, New York, 11201, USA. Rutesh.Dave@liu.edu.
Natoli Institute for Industrial Pharmacy Research and Development, Long Island University, Brooklyn, New Jersey, USA. Rutesh.Dave@liu.edu.

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