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Published on: August 9, 2022
Quantification of Amlodipine Maleate Content in Amorphous Solid Dispersions Produced by Fluidized Bed Granulation
Sandi Svetič1,2, Laura Medved1, Klemen Korasa1,2
1KRKA, d. d., 8501 Novo Mesto, Slovenia.
This study introduces Raman and near-infrared (NIR) spectroscopy methods for quantifying active pharmaceutical ingredient (API) content during amorphous solid dispersion (ASD) preparation using fluidized bed granulation (FBG). These process analytical technology (PAT) tools enable real-time monitoring and control for improved quality.
Area of Science:
- Pharmaceutical Technology
- Process Analytical Technology (PAT)
- Spectroscopy
Background:
- Active pharmaceutical ingredient (API) content is a critical quality attribute (CQA) in amorphous solid dispersions (ASDs).
- ASD preparation involves spraying API-polymer solutions onto excipients in a fluid bed granulator.
- Accurate quantification of API content is essential for process control and product quality.
Purpose of the Study:
- To develop and evaluate spectroscopic methods for quantifying API content during fluidized bed granulation (FBG) for ASD preparation.
- To assess the suitability of Raman and near-infrared (NIR) process analysers for real-time monitoring.
- To investigate the application of partial least squares (PLS) modeling for API quantification.
Main Methods:
- Utilized Raman and three near-infrared (NIR) process analysers.
- Developed four partial least squares (PLS) models using data from multiple granulation batches.
- Assessed model performance using metrics like RMSEP, RMSECV, and RPD.
Main Results:
- Off-line and at-line NIR models demonstrated suitability for process control.
- At-line Raman measurements accurately predicted the spraying phase endpoint.
- PLS models showed good predictability for API content.
Conclusions:
- This is the first study to monitor API content during FBG for ASD preparation using PAT tools.
- Raman and NIR spectroscopy combined with PLS modeling offer novel insights for monitoring and controlling ASD manufacturing.
- The developed methods support real-time quality assessment and process optimization.
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