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Advances in industrial biopharmaceutical batch process monitoring: Machine‐learning methods for small data problems

Biotechnology and bioengineering, 2018-08, Vol.115 (8), p.1915-1924

2018

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Online Batch/Fed-Batch Process Performance Monitoring, Quality Prediction, and Variable-Contribution Analysis for Diagnosis

Industrial & engineering chemistry research, 2003-10, Vol.42 (20), p.4645-4658

2003

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Multivariate statistical monitoring as applied to clean-in-place (CIP) and steam-in-place (SIP) operations in biopharmaceutical manufacturing

Biotechnology progress, 2014-03, Vol.30 (2), p.505-515

2014

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AI in Process Automation

SLAS technology, 2021-02, Vol.26 (1), p.1-2

Undey, Cenk

2021

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Industrial batch process monitoring with limited data

Journal of process control, 2019-05, Vol.77, p.114-133

2019

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Intelligent real-time performance monitoring and quality prediction for batch/fed-batch cultivations

Journal of biotechnology, 2004-02, Vol.108 (1), p.61-77

2004

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A machine‐learning approach to calibrate generic Raman models for real‐time monitoring of cell culture processes

Biotechnology and bioengineering, 2019-10, Vol.116 (10), p.2575-2586

2019

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A modular simulation package for fed-batch fermentation: penicillin production

Computers & chemical engineering, 2002-11, Vol.26 (11), p.1553-1565

2002

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Automatic real‐time calibration, assessment, and maintenance of generic Raman models for online monitoring of cell culture processes

Biotechnology and bioengineering, 2020-02, Vol.117 (2), p.406-416

2020

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PAT Applied in Biopharmaceutical Process Development And Manufacturing: An Enabling Tool for Quality-by-Design

1, 2012

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Cell culture product quality attribute prediction using convolutional neural networks and Raman spectroscopy

Biotechnology and bioengineering, 2024-04, Vol.121 (4), p.1231-1243

2024

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Cytopathic Effect Detection and Clonal Selection using Deep Learning

Pharmaceutical research, 2024-08, Vol.41 (8), p.1659-1669

2024

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Integration of just‐in‐time learning with variational autoencoder for cell culture process monitoring based on Raman spectroscopy

Biotechnology and bioengineering, 2024-07, Vol.121 (7), p.2205-2224

2024

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Machine learning‐based model predictive controller design for cell culture processes

Biotechnology and bioengineering, 2023-08, Vol.120 (8), p.2144-2159

2023

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Spectroscopic models for real‐time monitoring of cell culture processes using spatiotemporal just‐in‐time Gaussian processes

AIChE journal, 2021-05, Vol.67 (5), p.n/a

2021

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A morphologically structured model for penicillin production

Biotechnology and bioengineering, 2002-03, Vol.77 (5), p.538-552

2002

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Real-time multivariate statistical monitoring of biopharmaceutical processes with no prior product-specific history

Computers & chemical engineering, 2024-10, Vol.189, p.108788, Article 108788

2024

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PAT applied in biopharmaceutical process development and manufacturing: an enabling tool for quality-by-design

Undey, Cenk

2012

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High Performance Agent-Based Modeling to Simulate Mammalian Cell Culture Bioreactor

Computer Aided Chemical Engineering, 2018, Vol.44, p.1453-1458

2018

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Batch process monitoring and its application to polymerization systems

Macromolecular symposia., 2004-02, Vol.206 (1), p.121-134

2004

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Machine-learning for biopharmaceutical batch process monitoring with limited data

IFAC-PapersOnLine, 2018, Vol.51 (18), p.126-131

2018

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Condition-based sensor-health monitoring and maintenance in biomanufacturing

IFAC-PapersOnLine, 2020, Vol.53 (2), p.170-175

2020

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Applied advanced process analytics in biopharmaceutical manufacturing: Challenges and prospects in real-time monitoring and control

Journal of process control, 2010-10, Vol.20 (9), p.1009-1018

2010

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Product Attribute Forecast: Adaptive Model Selection Using Real-Time Machine Learning

IFAC-PapersOnLine, 2018, Vol.51 (18), p.121-125

2018

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Advances in industrial biopharmaceutical batch process monitoring: Machine‐learning methods for small data problems

Online Batch/Fed-Batch Process Performance Monitoring, Quality Prediction, and Variable-Contribution Analysis for Diagnosis

Multivariate statistical monitoring as applied to clean-in-place (CIP) and steam-in-place (SIP) operations in biopharmaceutical manufacturing

AI in Process Automation

Industrial batch process monitoring with limited data

Intelligent real-time performance monitoring and quality prediction for batch/fed-batch cultivations

A machine‐learning approach to calibrate generic Raman models for real‐time monitoring of cell culture processes

A modular simulation package for fed-batch fermentation: penicillin production

Automatic real‐time calibration, assessment, and maintenance of generic Raman models for online monitoring of cell culture processes

PAT Applied in Biopharmaceutical Process Development And Manufacturing: An Enabling Tool for Quality-by-Design

Cell culture product quality attribute prediction using convolutional neural networks and Raman spectroscopy

Cytopathic Effect Detection and Clonal Selection using Deep Learning

Integration of just‐in‐time learning with variational autoencoder for cell culture process monitoring based on Raman spectroscopy

Machine learning‐based model predictive controller design for cell culture processes

Spectroscopic models for real‐time monitoring of cell culture processes using spatiotemporal just‐in‐time Gaussian processes

A morphologically structured model for penicillin production

Real-time multivariate statistical monitoring of biopharmaceutical processes with no prior product-specific history

PAT applied in biopharmaceutical process development and manufacturing: an enabling tool for quality-by-design

High Performance Agent-Based Modeling to Simulate Mammalian Cell Culture Bioreactor

Batch process monitoring and its application to polymerization systems

Machine-learning for biopharmaceutical batch process monitoring with limited data

Condition-based sensor-health monitoring and maintenance in biomanufacturing

Applied advanced process analytics in biopharmaceutical manufacturing: Challenges and prospects in real-time monitoring and control

Product Attribute Forecast: Adaptive Model Selection Using Real-Time Machine Learning

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