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 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.
Nguang
S K
SK
Systems and Control Research Cluster, Department of Electrical and Electronic Engineering, University of Auckland, New Zealand. sk.nguang@auckland.ac.nz
Chen
L
L
Chen
X D
XD
D000465:Algorithms; D003470:Culture Media; D003584:Cytological Techniques / Q000295:instrumentation; D005823:Genetics / Q000706:statistics & numerical data*; D005947:Glucose / Q000378:metabolism; D005973:Glutamine / Q000378:metabolism; D006825:Hybridomas / Q000502:physiology*; D007700:Kinetics
D003470:Culture Media; D005973:Glutamine; D005947:Glucose