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Crystal ball – 2011

View Article: PubMed Central

ABSTRACT

In this feature, leading researchers in the field of microbial biotechnology speculate on the technical and conceptual developments that will drive innovative research and open new vistas over the next few years.

No MeSH data available.


Model development framework for bioprocess systems engineering.
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f2: Model development framework for bioprocess systems engineering.

Mentions: The ever‐increasing development and improvement of sustainable bioprocesses towards efficient production of pharmaceuticals and chemicals inadvertedly requires the implementation of a rational and feasible approach. Process systems engineering offers a variety of modelling, simulation and process evaluation tools, which are widely used in the chemicals and fuels sectors where even small process improvements may bring substantial economic profits (Jimenez‐Gonzalez and Woodley, 2010). Therefore, the need for a Bioprocess Systems Engineering research framework may prove beneficial. We have formalized such a systematic approach for modelling biological systems (Kontoravdi et al., 2005; 2007; 2010; Kiparissides et al., 2009; Koutinas et al., 2010), shown in Fig. 2. In our opinion, a mathematical representation of a studied biological system should aim to describe the system using adequate yet not excessive information regarding the relevant biological mechanisms. Overly complex mathematical formulations that lead to over‐parameterized models should be avoided. Rigorous model analysis is required to screen for significant and/or redundant parameters and design optimally informative experiments in order to refine the parameter values and minimize the uncertainty in the model output even potentially leading to model reduction. The aim should be a ‘high‐fidelity’ model that is successful over a wide range of operating conditions that can be used for model based optimization and control. Maybe then we can successfully bridge ‘scales’ between ‘molecules, cells & processes’ that will render modelling practically useful to biology.


Crystal ball – 2011
Model development framework for bioprocess systems engineering.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3818853&req=5

f2: Model development framework for bioprocess systems engineering.
Mentions: The ever‐increasing development and improvement of sustainable bioprocesses towards efficient production of pharmaceuticals and chemicals inadvertedly requires the implementation of a rational and feasible approach. Process systems engineering offers a variety of modelling, simulation and process evaluation tools, which are widely used in the chemicals and fuels sectors where even small process improvements may bring substantial economic profits (Jimenez‐Gonzalez and Woodley, 2010). Therefore, the need for a Bioprocess Systems Engineering research framework may prove beneficial. We have formalized such a systematic approach for modelling biological systems (Kontoravdi et al., 2005; 2007; 2010; Kiparissides et al., 2009; Koutinas et al., 2010), shown in Fig. 2. In our opinion, a mathematical representation of a studied biological system should aim to describe the system using adequate yet not excessive information regarding the relevant biological mechanisms. Overly complex mathematical formulations that lead to over‐parameterized models should be avoided. Rigorous model analysis is required to screen for significant and/or redundant parameters and design optimally informative experiments in order to refine the parameter values and minimize the uncertainty in the model output even potentially leading to model reduction. The aim should be a ‘high‐fidelity’ model that is successful over a wide range of operating conditions that can be used for model based optimization and control. Maybe then we can successfully bridge ‘scales’ between ‘molecules, cells & processes’ that will render modelling practically useful to biology.

View Article: PubMed Central

ABSTRACT

In this feature, leading researchers in the field of microbial biotechnology speculate on the technical and conceptual developments that will drive innovative research and open new vistas over the next few years.

No MeSH data available.