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Improving Biopharmaceutical Manufacturing Yield Using Neural Network Classification

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Download VaccineYieldNeuralNet_FaheyCarroll_final.pdf649.14 KB
Author(s)
Fahey, Will 
Carroll, Paula 
Uri
http://hdl.handle.net/10197/8746
Date Issued
January 2016
Date Available
01T16:21:42Z September 2017
Abstract
Traditionally, the Six Sigma framework has underpinned quality improvement and assurance in biopharmaceutical manufacturing process management. This paper proposes a neural network (NN) approach to vaccine yield classification and compares it to an existing multiple linear regression approach. As part of the Six Sigma process, this paper shows how a data mining framework can be used to extract further value and insight from the data gathered during the manufacturing process, and how insights into yield classification can be used in the quality improvement process.
Type of Material
Journal Article
Publisher
BioProcessing Journal
Journal
BioProcessing Journal
Volume
14
Issue
4
Start Page
39
End Page
50
Keywords
  • Biopharmaceutical man...

  • Neural network

  • Classification

  • Business analyitics

DOI
10.12665/J144.Carroll
Language
English
Status of Item
Peer reviewed
ISSN
1538-8786
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
Owning collection
Business Research Collection
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