Merging Real-Time NIR and Process Parameter Measurements in a Fluidized Bed Granulation Process to Predict Particle Size

Merging Real-Time NIR and Process Parameter Measurements in a Fluidized Bed Granulation Process to Predict Particle Size

<b>Background/Objectives</b>: Controlling the critical quality attributes (CQAs), such as granule moisture level and particle size distribution, that impact product performance is essential for ensuring product quality in medicine manufacture. Oral solid dosage forms, such as tablets, of...

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Bibliographic Details
Main Authors: Ozren Jovic, Marcus O’Mahony, Samuel Solomon, David Egan, Chris O’Callaghan, Caroline McCormack, Ian Jones, Patrick Cronin, Gavin M. Walker, Rabah Mouras
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Pharmaceutics
Subjects:
fluid bed granulation
chemometrics
predictive modeling
machine learning (ML)
critical quality attributes (CQAs)
PLS
Online Access:https://www.mdpi.com/1999-4923/17/6/720
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