Evaluation of Prediction Models for the Capping and Breaking Force of Tablets Using Machine Learning Tools in Wet Granulation Commercial-Scale Pharmaceutical Manufacturing

Evaluation of Prediction Models for the Capping and Breaking Force of Tablets Using Machine Learning Tools in Wet Granulation Commercial-Scale Pharmaceutical Manufacturing

<b>Background/Objectives</b>: This study aimed to establish a predictive model for critical quality attributes (CQAs) related to tablet integrity, including tablet breaking force (TBF), friability, and capping occurrence, using machine learning-based models and nondestructive experimenta...

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Bibliographic Details
Main Authors: Sun Ho Kim, Su Hyeon Han, Dong-Wan Seo, Myung Joo Kang
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Pharmaceuticals
Subjects:
machine learning
capping prediction
tablet breaking force
permutation feature importance analysis
Online Access:https://www.mdpi.com/1424-8247/18/1/23
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https://www.mdpi.com/1424-8247/18/1/23

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