Iterative Design of Dynamic Experiments in Modeling for Optimization of Innovative Bioprocesses

被引:1
作者
Cristaldi, Mariano
Grau, Ricardo
Martinez, Ernesto
机构
来源
CHEMICAL PRODUCT AND PROCESS MODELING | 2009年 / 4卷 / 02期
关键词
modeling; optimization; biotechnology; experimental design; dynamic experiments;
D O I
10.2202/1934-2659.1298
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
Finding optimal operating conditions fast with a scarce budget of experimental runs is a key problem to speed up the development and scaling up of innovative bioprocesses. In this paper, a novel iterative methodology for the model-based design of dynamic experiments in modeling for optimization is developed and successfully applied to the optimization of a fed-batch bioreactor related to the production of r-interleukin-11 (rIL-11) whose DNA sequence has been cloned in an Escherichia coli strain. At each iteration, the proposed methodology resorts to a library of tendency models to increasingly bias bioreactor operating conditions towards an optimum. By selecting the 'most informative' tendency model in the sequel, the next dynamic experiment is defined by re-optimizing the input policy and calculating optimal sampling times. Model selection is based on minimizing an error measure which distinguishes between parametric and structural uncertainty to selectively bias data gathering towards improved operating conditions. The parametric uncertainty of tendency models is iteratively reduced using Global Sensitivity Analysis (GSA) to pinpoint which parameters are keys for estimating the objective function. Results obtained after just a few iterations are very promising.
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页数:27
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共 37 条
[1]   Avoiding acetate accumulation in Escherichia coli cultures using feedback control of glucose feeding [J].
Åkesson, M ;
Hagander, P ;
Axelsson, JP .
BIOTECHNOLOGY AND BIOENGINEERING, 2001, 73 (03) :223-230
[2]  
[Anonymous], PHARM BIOTECHNOLOGY
[3]   Designing robust optimal dynamic experiments [J].
Asprey, SP ;
Macchietto, S .
JOURNAL OF PROCESS CONTROL, 2002, 12 (04) :545-556
[4]   Statistical tools for optimal dynamic model building [J].
Asprey, SP ;
Macchietto, S .
COMPUTERS & CHEMICAL ENGINEERING, 2000, 24 (2-7) :1261-1267
[5]   Mathematical modeling and analysis in biochemical engineering: Past accomplishments and future opportunities [J].
Bailey, JE .
BIOTECHNOLOGY PROGRESS, 1998, 14 (01) :8-20
[6]   Dynamic optimization of chemical and biochemical processes using restricted second-order information [J].
Balsa-Canto, E ;
Banga, JR ;
Alonso, AA ;
Vassiliadis, VS .
COMPUTERS & CHEMICAL ENGINEERING, 2001, 25 (4-6) :539-546
[7]   Stochastic dynamic optimization of batch and semicontinuous bioprocesses [J].
Banga, JR ;
Alonso, AA ;
Singh, RP .
BIOTECHNOLOGY PROGRESS, 1997, 13 (03) :326-335
[8]   ONLINE ESTIMATION OF MICROBIAL SPECIFIC GROWTH-RATES [J].
BASTIN, G ;
DOCHAIN, D .
AUTOMATICA, 1986, 22 (06) :705-709
[9]   Nonlinear and Adaptive Control in Biotechnology: A Tutorial [J].
Bastin, G. ;
Van Impe, J. F. .
EUROPEAN JOURNAL OF CONTROL, 1995, 1 (01) :37-53
[10]   Optimal operation of batch reactors - a personal view [J].
Bonvin, D .
JOURNAL OF PROCESS CONTROL, 1998, 8 (5-6) :355-368