Back to Search Start Over

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.

Authors :
Basim P
Shah HS
Sedlock R
Parekh BV
Dave RH
Source :
AAPS PharmSciTech [AAPS PharmSciTech] 2024 Oct 10; Vol. 25 (7), pp. 238. Date of Electronic Publication: 2024 Oct 10.
Publication Year :
2024

Abstract

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

Details

Language :
English
ISSN :
1530-9932
Volume :
25
Issue :
7
Database :
MEDLINE
Journal :
AAPS PharmSciTech
Publication Type :
Academic Journal
Accession number :
39390268
Full Text :
https://doi.org/10.1208/s12249-024-02950-3