Predicting Pharmaceutical Particle Size Distributions Using Kernel Mean Embedding

Predicting Pharmaceutical Particle Size Distributions Using Kernel Mean Embedding

In the pharmaceutical industry, the transition to continuous manufacturing of solid dosage forms is adopted by more and more companies. For these continuous processes, high-quality process models are needed. In pharmaceutical wet granulation, a unit operation in the ConsiGma<inline-formula> &l...

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Bibliographic Details
Main Authors: Daan Van Hauwermeiren, Michiel Stock, Thomas De Beer, Ingmar Nopens
Format: Article
Language:English
Published: MDPI AG 2020-03-01
Series:Pharmaceutics
Subjects:
granulation
wet granulation
continuous manufacturing
process modeling
particle size distributions
kernel methods
kernel mean embedding
predictive modeling
data-driven
machine learning
Online Access:https://www.mdpi.com/1999-4923/12/3/271

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