Literature DB >> 24806479

Hybrid modeling for quality by design and PAT-benefits and challenges of applications in biopharmaceutical industry.

Moritz von Stosch1, Steven Davy, Kjell Francois, Vytautas Galvanauskas, Jan-Martijn Hamelink, Andreas Luebbert, Martin Mayer, Rui Oliveira, Ronan O'Kennedy, Paul Rice, Jarka Glassey.   

Abstract

This report highlights the drivers, challenges, and enablers of the hybrid modeling applications in biopharmaceutical industry. It is a summary of an expert panel discussion of European academics and industrialists with relevant scientific and engineering backgrounds. Hybrid modeling is viewed in its broader sense, namely as the integration of different knowledge sources in form of parametric and nonparametric models into a hybrid semi-parametric model, for instance the integration of fundamental and data-driven models. A brief description of the current state-of-the-art and industrial uptake of the methodology is provided. The report concludes with a number of recommendations to facilitate further developments and a wider industrial application of this modeling approach. These recommendations are limited to further exploiting the benefits of this methodology within process analytical technology (PAT) applications in biopharmaceutical industry.
Copyright © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Entities:  

Keywords:  Biopharmaceuticals; Bioprocess development; Hybrid modeling; Process analytical technology; Quality by design

Mesh:

Year:  2014        PMID: 24806479     DOI: 10.1002/biot.201300385

Source DB:  PubMed          Journal:  Biotechnol J        ISSN: 1860-6768            Impact factor:   4.677


  6 in total

1.  Hybrid modeling as a QbD/PAT tool in process development: an industrial E. coli case study.

Authors:  Moritz von Stosch; Jan-Martijn Hamelink; Rui Oliveira
Journal:  Bioprocess Biosyst Eng       Date:  2016-02-15       Impact factor: 3.210

Review 2.  Harnessing the potential of machine learning for advancing "Quality by Design" in biomanufacturing.

Authors:  Ian Walsh; Matthew Myint; Terry Nguyen-Khuong; Ying Swan Ho; Say Kong Ng; Meiyappan Lakshmanan
Journal:  MAbs       Date:  2022 Jan-Dec       Impact factor: 5.857

3.  Generic and specific recurrent neural network models: Applications for large and small scale biopharmaceutical upstream processes.

Authors:  Jens Smiatek; Christoph Clemens; Liliana Montano Herrera; Sabine Arnold; Bettina Knapp; Beate Presser; Alexander Jung; Thomas Wucherpfennig; Erich Bluhmki
Journal:  Biotechnol Rep (Amst)       Date:  2021-05-28

4.  Investigation of the interactions of critical scale-up parameters (pH, pO2 and pCO2) on CHO batch performance and critical quality attributes.

Authors:  Matthias Brunner; Jens Fricke; Paul Kroll; Christoph Herwig
Journal:  Bioprocess Biosyst Eng       Date:  2016-10-17       Impact factor: 3.210

5.  Towards smart biomanufacturing: a perspective on recent developments in industrial measurement and monitoring technologies for bio-based production processes.

Authors:  Carina L Gargalo; Isuru Udugama; Katrin Pontius; Pau C Lopez; Rasmus F Nielsen; Aliyeh Hasanzadeh; Seyed Soheil Mansouri; Christoph Bayer; Helena Junicke; Krist V Gernaey
Journal:  J Ind Microbiol Biotechnol       Date:  2020-09-07       Impact factor: 3.346

6.  Transforming data to information: A parallel hybrid model for real-time state estimation in lignocellulosic ethanol fermentation.

Authors:  Pau Cabaneros Lopez; Isuru A Udugama; Sune T Thomsen; Christian Roslander; Helena Junicke; Miguel M Iglesias; Krist V Gernaey
Journal:  Biotechnol Bioeng       Date:  2020-10-15       Impact factor: 4.530

  6 in total

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