Article (Scientific journals)
Optimizing neotissue growth inside perfusion bioreactors with respect to culture and labor cost: a multi-objective optimization study using evolutionary algorithms.
Mehrian, Mohammad; Geris, Liesbet
2020In Computer Methods in Biomechanics and Biomedical Engineering, 23 (7), p. 285-294
Peer Reviewed verified by ORBi
 

Files


Full Text
CMBBE_2020_MEhrian.pdf
Publisher postprint (1.71 MB)
Download

All documents in ORBi are protected by a user license.

Send to



Details



Keywords :
Algorithms; Bioreactors; Computer Simulation; Perfusion/instrumentation; Time Factors; Tissue Culture Techniques; Tissue Engineering/methods; 3D scaffold; Multi-objective optimization; bone tissue engineering; evolutionary algorithms; labor cost
Abstract :
[en] Tissue engineering is a fast progressing domain where solutions are provided for organ failure or tissue damage. In this domain, computer models can facilitate the design of optimal production process conditions leading to robust and economically viable products. In this study, we use a previously published computationally efficient model, describing the neotissue growth (cells + their extracellular matrix) inside 3D scaffolds in a perfusion bioreactor. In order to find the most cost-effective medium refreshment strategy for the bioreactor culture, a multi-objective optimization strategy was developed aimed at maximizing the neotissue growth while minimizing the total cost of the experiment. Four evolutionary optimization algorithms (NSGAII, MOPSO, MOEA/D and GDEIII) were applied to the problem and the Pareto frontier was computed in all methods. All algorithms led to a similar outcome, albeit with different convergence speeds. The simulation results indicated that, given the actual cost of the labor compared to the medium cost, the most cost-efficient way of refreshing the medium was obtained by minimizing the refreshment frequency and maximizing the refreshment amount.
Disciplines :
Engineering, computing & technology: Multidisciplinary, general & others
Author, co-author :
Mehrian, Mohammad
Geris, Liesbet  ;  Université de Liège - ULiège > Département d'aérospatiale et mécanique > Génie biomécanique
Language :
English
Title :
Optimizing neotissue growth inside perfusion bioreactors with respect to culture and labor cost: a multi-objective optimization study using evolutionary algorithms.
Publication date :
2020
Journal title :
Computer Methods in Biomechanics and Biomedical Engineering
ISSN :
1025-5842
eISSN :
1476-8259
Publisher :
Taylor & Francis, United Kingdom
Volume :
23
Issue :
7
Pages :
285-294
Peer reviewed :
Peer Reviewed verified by ORBi
European Projects :
H2020 - 772418 - INSITE - Development and use of an integrated in silico-in vitro mesofluidics system for tissue engineering
Funders :
ERC - European Research Council
EC - European Commission
Available on ORBi :
since 12 July 2020

Statistics


Number of views
88 (3 by ULiège)
Number of downloads
261 (2 by ULiège)

Scopus citations®
 
8
Scopus citations®
without self-citations
7
OpenCitations
 
6
OpenAlex citations
 
10

Bibliography


Similar publications



Contact ORBi