Optimisation of fed-batch culture of hybridoma cells using genetic algorithms

In this paper, a program describing a genetic algorithm is used for optimising fed-batch culture hybridoma cells to obtain the highest yield over certain time period. Optimal feed rate trajectories for a single feed stream containing both glucose and glutamine, and separate feed streams of glucose a...

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Bibliographic Details
Published in:ISA transactions 2001-01, Vol.40 (4), p.381-389
Main Authors: Nguang, Sing Kiong, Chen, LeiZhi, Chen, Xiao Dong
Format: Article
Language:English
Subjects:
Algorithms
Batch cell culture
Computer simulation
Culture Media
Cytological Techniques - instrumentation
Dynamic programming
Genetic algorithm
Genetic algorithms
Genetics - statistics & numerical data
Glucose - metabolism
Glutamine - metabolism
Hybridoma
Hybridomas - physiology
Kinetics
Optimal feed rate
Process control
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Summary:In this paper, a program describing a genetic algorithm is used for optimising fed-batch culture hybridoma cells to obtain the highest yield over certain time period. Optimal feed rate trajectories for a single feed stream containing both glucose and glutamine, and separate feed streams of glucose and glutamine are determined via the genetic algorithm. As compared to the optimal constant feed rate regime, optimal varying feed rate trajectories improve the final monoclonal antibodies concentration by 10% for the single feed rate case and by 39% for the multi feed rate case in this simulation. In comparsion with a dynamic programming, GA calculated feed trajectories yield a much higher level of monoclonal antibodies concentration.
ISSN:0019-0578
1879-2022
DOI:10.1016/S0019-0578(01)00005-2