Special Issue "Application of Systems Engineering Principles to Bioprocessing "

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Biological Systems".

Deadline for manuscript submissions: 15 February 2020.

Special Issue Editors

Dr. Cleo Kontoravdi
E-Mail Website
Guest Editor
Department of Chemical Engineering, Imperial College London, South Kensington Campus, London SW7 2AZ
Interests: bioprocessing, recombinant protein production, protein glycosylation, modelling and optimization of cell culture systems
Dr. Alexandros Kiparissides
E-Mail Website
Guest Editor
Department of Biochemical Engineering, University College London, Bernard Katz building, London, WC1E 6BT
Interests: systems biology; recombinant protein production; modelling and optimization of cell culture systems; sensitivity analysis; parameter estimation; design of experiments; cell culture media and feeding strategies

Special Issue Information

Dear Colleagues,

The Quality by Design initiative has supported the application of model-based tools in the biopharmaceutical industry with the aim of improving process understanding and moving towards the implementation of optimisation and control principles using process analytical technologies. In the past decade we have seen significant progress in the development of data-driven, knowledge-driven and hybrid models of both upstream and downstream processing, which have enhanced the exploration of the design space as well as quantifying relationships between process parameters and critical quality attributes for specific unit operations. At the same time, we have seen the emergence of Synthetic Biology, which has expanded our toolset for genetic modification of hosts with an increased degree of specificity, accuracy and control. This opens up new possibilities for model-based design of pathways and functionalities that can enhance bioprocess performance.

This special issue on “Application of Systems Engineering Principles to Bioprocessing” aims to curate novel advances in the development and application of computational modeling and model-based applications to address longstanding challenges in Bioprocessing. Topics include, but are not limited to:

  • Modelling (mechanistic and data-driven) and optimisation of upstream and downstream unit operations;
  • Implementation of online control strategies;
  • Model-driven process design;
  • Whole process simulation and analysis, including flowsheeting of novel manufacturing processes for new modalities or modular production;
  • Model-based approaches to enhance the understanding and performance of cellular behaviour under industrial bioprocessing conditions, such as design of genetic and metabolic engineering strategies, and/or enable the analysis of large datasets, such as systems biology, machine learning and artificial intelligence appraoches.

Dr. Cleo Kontoravdi
Dr. Alexandros Kiparissides
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Processes is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1400 CHF (Swiss Francs). Please note that for papers submitted after 30 June 2020 an APC of 1500 CHF applies. Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • bioprocess design
  • process simulation
  • metabolic modelling
  • fermentation modelling
  • model-based optimization
  • online control
  • first-principles modelling
  • data-driven modelling

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Research

Open AccessArticle
Adaptive Control of Biomass Specific Growth Rate in Fed-Batch Biotechnological Processes. A Comparative Study
Processes 2019, 7(11), 810; https://doi.org/10.3390/pr7110810 - 04 Nov 2019
Abstract
This article presents a comparative study on the development and application of two distinct adaptive control algorithms for biomass specific growth rate control in fed-batch biotechnological processes. A typical fed-batch process using Escherichia coli for recombinant protein production was selected for this research. [...] Read more.
This article presents a comparative study on the development and application of two distinct adaptive control algorithms for biomass specific growth rate control in fed-batch biotechnological processes. A typical fed-batch process using Escherichia coli for recombinant protein production was selected for this research. Numerical simulation results show that both developed controllers, an adaptive PI controller based on the gain scheduling technique and a model-free adaptive controller based on the artificial neural network, delivered a comparable control performance and are suitable for application when using the substrate limitation approach and substrate feeding rate manipulation. The controller performance was tested within the realistic ranges of the feedback signal sampling intervals and measurement noise intensities. Considering the efforts for controller design and tuning, including development of the adaptation/learning algorithms, the model-free adaptive control algorithm proves to be more attractive for industrial applications, especially when only limited knowledge of the process and its mathematical model is available. The investigated model-free adaptive controller also tended to deliver better control quality under low specific growth rate conditions that prevail during the recombinant protein production phase. In the investigated simulation runs, the average tracking error did not exceed 0.01 (1/h). The temporary overshoots caused by the maximal disturbances stayed within the range of 0.025–0.11 (1/h). Application of the algorithm can be further extended to specific growth rate control in other bacterial and mammalian cell cultivations that run under substrate limitation conditions. Full article
(This article belongs to the Special Issue Application of Systems Engineering Principles to Bioprocessing )
Show Figures

Figure 1

Back to TopTop