Quantification of Amlodipine Maleate Content in Amorphous Solid Dispersions Produced by Fluidized Bed Granulation Using Process Analytical Technology Tools

Background: Active pharmaceutical ingredient (API) content is a critical quality attribute (CQA) of amorphous solid dispersions (ASDs) prepared by spraying a solution of APIs and polymers onto the excipients in fluid bed granulator. This study presents four methods for quantifying API content during...

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Bibliographic Details
Published in:Pharmaceutics 2024-12, Vol.16 (12), p.1538
Main Authors: Svetič, Sandi, Medved, Laura, Korasa, Klemen, Vrečer, Franc
Format: Article
Language:English
Subjects:
amorphous solid dispersion
Bioavailability
Cellulose
fluidized bed granulation
Lactose
Manufacturing
Mean square errors
multivariate analysis
near-infrared spectroscopy
Nonsteroidal anti-inflammatory drugs
Pharmaceuticals
process analytical technology
Raman spectroscopy
Support vector machines
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Summary:Background: Active pharmaceutical ingredient (API) content is a critical quality attribute (CQA) of amorphous solid dispersions (ASDs) prepared by spraying a solution of APIs and polymers onto the excipients in fluid bed granulator. This study presents four methods for quantifying API content during ASD preparation. Methods: Raman and three near-infrared (NIR) process analysers were utilized to develop methods for API quantification. Four partial least squares (PLS) models were developed using measurements from three granulation batches, with an additional batch used to evaluate model predictability. Models performance was assessed using metrics such as root mean square error of prediction (RMSEP), root mean square error of cross-validation (RMSECV), residual prediction deviation (RPD), and others. Results: Off-line and at-line NIR models were identified as suitable for process control applications. Additionally, at-line Raman measurements effectively predicted the endpoint of the spraying phase. Conclusions: To the best of authors’ knowledge, this is the first study focused on monitoring API content during fluidized bed granulation (FBG) used for ASD preparation. The findings provide novel insights into the application of Raman and NIR process analysers with PLS modelling for monitoring and controlling ASD preparation processes.
ISSN:1999-4923
DOI:10.3390/pharmaceutics16121538