Back to Search Start Over

Distributed and Lumped Parameter Models for the Characterization of High Throughput Bioreactors

Authors :
Manuela Teresa Raimondi
Gioacchino Conoscenti
Giovanna D'Urso
Laura Iannetti
Rocky S. Tuan
Elena Cutrì
Riccardo Gottardi
Paolo Zunino
Iannetti, L
D’Urso, G
Conoscenti, G
Cutrì, E
Tuan, RS
Raimondi, MT
Gottardi, R
Zunino, P
Source :
PLOS ONE, PLoS ONE, PLoS ONE, Vol 11, Iss 9, p e0162774 (2016)

Abstract

Next generation bioreactors are being developed to generate multiple human cell-based tissue analogs within the same fluidic system, to better recapitulate the complexity and interconnection of human physiology. The effective development of these devices requires a solid understanding of their interconnected fluidics, to predict the transport of nutrients and waste through the constructs and improve the design accordingly. In this work, we focus on a specific model of bioreactor, with multiple input/outputs, aimed at gen- erating osteochondral constructs, i.e., a biphasic construct in which one side is cartilagi- nous in nature, while the other is osseous. We next develop a general computational approach to model the microfluidics of a multi-chamber, interconnected system that may be applied to human-on-chip devices. This objective requires overcoming several chal- lenges at the level of computational modeling. The main one consists of addressing the multi-physics nature of the problem that combines free flow in channels with hindered flow in porous media. Fluid dynamics is also coupled with advection-diffusion-reaction equa- tions that model the transport of biomolecules throughout the system and their interaction with living tissues and C constructs. Ultimately, we aim at providing a predictive approach useful for the general organ-on-chip community. To this end, we have developed a lumped parameter approach that allows us to analyze the behavior of multi-unit bioreactor systems with modest computational effort, provided that the behavior of a single unit can be fully characterized.

Details

Language :
English
ISSN :
19326203
Volume :
11
Issue :
9
Database :
OpenAIRE
Journal :
PLOS ONE
Accession number :
edsair.doi.dedup.....522dc5f9879427df4ce379382496a3d1
Full Text :
https://doi.org/10.1371/journal.pone.0162774