Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Report . 2020
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Report . 2020
License: CC BY
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Report . 2020
License: CC BY
Data sources: Datacite
versions View all 2 versions
addClaim

Modeling the Integration of Flow, Cell and Microcarrier Biomechanics in a Stirred Tank Bioreactor - Proof-of-Concept Report

Authors: Aguilar, Boris; Chen, Jiajia; Potter, Greg; Kahan, Simon; Clark, Chris; Cantarero Rivera, Fernando; Camphuijsen, Jaro;

Modeling the Integration of Flow, Cell and Microcarrier Biomechanics in a Stirred Tank Bioreactor - Proof-of-Concept Report

Abstract

Increasing worldwide demand for meat is driving the growth of environmentally detrimental factory farming. Cultivated meat is a potentially more sustainable alternative to factory farming that could mitigate water contamination, land use, and disease spread. As a nascent technology, however, a number of challenges must be overcome before cultivated meat is available worldwide. Arguably the most fundamental challenge is the efficient production of biomass at scale. At present, two significant issues stand in the way of scaling up production. First is the cost of media fed into the bioreactor to support cell growth. Media costs will decline as serum-free media technologies - already in use by some cultivated meat producers - eliminate the need for expensive fetal bovine serum. Further cost reductions are expected as media formulations transition from small quantities and custom combinations used in R&D to the higher volumes and more predictable demand typical of ingredients used in mass production. How much media cost reduction will be achieved through economy of scale though is a subject of debate. The second impediment to scaling production is the efficacy of the bioreactor equipment itself at high production volumes. Cells require a nutritious, oxygen rich, homogeneous environment. At the same time cells consume some molecules such as cytokines and chemokines in the environment and excrete others. In live animals, vasculature delivers and collects molecules to sustain every cell’s environment. In bioreactors, mixing the fluid acts as a coarse surrogate for vasculature. As bioreactor volume and cell density increases, maintaining a well-mixed environment tends to require faster fluid flow. A faster fluid flow can induce strong shear forces that cause cells to cease proliferating or to die. Maintaining a favorable molecular environment for cells without subjecting them to excessive shear stress will require innovation in, and optimization of, bioreactor designs and processes. Both innovation and optimization require extensive experimentation. However, building physical prototypes and running experiments are slow and expensive. Virtual prototyping and experimentation through computer simulation promises to accelerate and lower the cost of progress. However, virtual experiments replicating actual bioreactor and biological behaviors are not immediate: we need first to develop predictive models of the bioreactor environment. Tha main challenge in developing a predictive model of cells growing in a bioreactor is the complexity of the bioreactor environment and cell behavior. Media flow dynamics, forces and mixing of media components needs to be incorporated into the model. Simultaneously, cells growing on microcarriers, consuming nutrients, excreting waste, proliferating and dying introduces an additional layer of complexity. Thus, modeling the resulting system requires an altogether new multiscale methodology accounting for phenomena happening at diverse spatial and temporal scales.

This proof-of-concept project was funded by Merck KGaA, Darmstadt, Germany

Related Organizations
Keywords

physical stress, Cultivated Meat, Clean Meat, Multiscale modeling, muscle cells, Computational Fluid Dynamics, Stir tank bioreactor, microcarrier, Agent Based modeling

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
    OpenAIRE UsageCounts
    Usage byUsageCounts
    visibility views 12
    download downloads 14
  • 12
    views
    14
    downloads
    Powered byOpenAIRE UsageCounts
Powered by OpenAIRE graph
Found an issue? Give us feedback
visibility
download
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
OpenAIRE UsageCountsDownloads provided by UsageCounts
0
Average
Average
Average
12
14
Green