On predicting the performance of different silicas on key property enhancements of fine APIs, blends, and tablets
Document Type
Article
Publication Date
1-2-2024
Abstract
Predictive selection of silica size, type (hydrophobic/hydrophilic), and amount is addressed for achieving significant property enhancements of fine active pharmaceutical ingredients (APIs). Four models, Chen's multi-asperity particle-adhesion, total surface energy-based guest-host compatibility, dispersive surface energy-based tablet tensile strength, and stick-bounce-based silica aggregation on coated particles, are invoked. The impact on the bulk properties of four APIs cohesive API powders (∼10 μm) and 40 wt% (wt%) blends of one API, dry-coated at 50% and 100% surface area coverage (SAC) of four nano-silicas (7–20 nm), hydrophobic (R972P), hydrophilic (M5P, A200, A300) is assessed. Significant enhancements in flowability, bulk density, compactability, agglomeration reduction, and dissolution for API or blend are achieved with all silicas. The experimental and model-based outcomes demonstrate that silica performance is impacted by multiple factors, silica size and coating effectiveness being most critical. In conclusion, R972P and A200 at lower 50% SAC present two excellent choices.
Identifier
85177045326 (Scopus)
Publication Title
Powder Technology
External Full Text Location
https://doi.org/10.1016/j.powtec.2023.119104
e-ISSN
1873328X
ISSN
00325910
Volume
432
Grant
IIP-2137209
Fund Ref
National Science Foundation
Recommended Citation
Kim, Sangah S.; Seetahal, Ameera; Kossor, Christopher; and Davé, Rajesh N., "On predicting the performance of different silicas on key property enhancements of fine APIs, blends, and tablets" (2024). Faculty Publications. 691.
https://digitalcommons.njit.edu/fac_pubs/691