Abstract
AbstractFed-batch processes are prevalent in biotechnological industries, but design of experiments often results in sub-optimal conditions due to incomplete solution space characterization. We employ a single-level dynamic control (DC) algorithm for dynamic flux balance analysis (dFBA), enhancing efficiency by reducing Karush-Kuhn-Tucker (KKT) condition constraints and adapting the algorithm for predicting optimal process length. In a growth-decoupled plasmid DNA production case study, we predict the optimal feeding profile and switching time between growth and production phase. Comparing our algorithm to its predecessor shows a speed-up of at least a factor of four. When the process length is part of the objective function the speed-up becomes considerably larger.
Publisher
Cold Spring Harbor Laboratory
Reference18 articles.
1. Bauer, J. and Klamt, S. (2024). Optmsp: A toolbox for designing optimal multi-stage (bio) processes. Journal of Biotechnology.
2. MPEC problem formulations and solution strategies with chemical engineering applications
3. Nonlinear programming reformulation of dynamic flux balance analysis models;Computers & Chemical Engineering,2023
4. A dynamic method based on the specific substrate uptake rate to set up a feeding strategy for pichia pastoris;Microbial Cell Factories,2011
5. Engineered e. coli w enables efficient 2, 3-butanediol production from glucose and sugar beet molasses using defined minimal medium as economic basis;Microbial Cell Factories,2018
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献