Modeling, optimization, and computer control of the cephalosporin C fermentation process

Chu, Wey-Bang Z.; Constantinides, Alkis

doi:10.1002/bit.260320304

Cited by 43 publications

(21 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Glucose and other rapidly utilized carbon sources repress the ring-expansion enzyme desacetoxycephalosporin-C-synthetase and inhibit the first enzyme of the CPC-pathway, the ACV synthetase in the cephalosporin synthesis. The ring expansion enzyme is not inhibited after induction [71]. As for penicillin production, the repression can be avoided by using carbon sources with lower maximum growth rate compared to glucose, such as lactose or oil.…”

Section: Overviewmentioning

confidence: 99%

Proces models for production of β-lactam antibiotics

Bellgardt

1998

Relation Between Morphology and Process Performances

View full text Add to dashboard Cite

Great progress has been made in the modelling of biotechnical processes using filamentous microorganisms. This paper deals with cultivations of Penicillium chrysogenum for the production of Penicillin and of Acrernonium chrysogenum for the production of Cephalosporin C. The properties of the processes and the existing models are reviewed. Models are presented for both processes that consider aspects which are important for industrial cultivation. The process model for Penicillin production is based on a detailed morphological description of growth of hyphal filaments and pellets. The model allows for simulation of the production process including the preculture and considering the inhomogenous pellet population. It opens new possibilities for understanding the complex kinetics of the process and improvement of its control. The structured segregated model for Cephalosporin C production considers soy oil as second carbon source besides sugar. The application of the model for dynamic optimization of feeding strategies by Iterative Dynamic Programming is demonstrated. As an alternative approach, modelling of the Cephalosporin production by an artificial neural network is discussed.

show abstract

Section: Overviewmentioning

confidence: 99%

Proces models for production of β-lactam antibiotics

Bellgardt

1998

Relation Between Morphology and Process Performances

View full text Add to dashboard Cite

show abstract

“…In these reports, the optimization problem is generally formulated on the basis of Pontryagin's maximum principle, taking as a starting point a phenomenological mathematical model of the bioprocess. For simple mathematical models, the problem can be solved analytically, from the Hamiltonian of the system, by applying an iterative scheme on the control variable to determine the optimal control profile [8,[16][17][18][19].…”

Section: Statistical Approaches With Emphasis On Design Of Experimentmentioning

confidence: 99%

“…In antibiotic fermentation, it is well known that the temperature and pH for the maximum rate of antibiotic production are different from those for the maximum rate of cell growth [8]. In this sense, the implementation of temperature and pH profiles plays an important role in significant improvements in antibiotic production bioprocesses [8].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Model-Based Evolutionary Operation Design for Batch and Fed- Batch Antibiotic Production Bioprocesses

Oliveira¹

2018

Statistical Approaches With Emphasis on Design of Experiments Applied to Chemical Processes

View full text Add to dashboard Cite

The control policy determination for batch and fed-batch antibiotic production bioprocesses is an important practical issue due to the high added value of these bioproducts. Since it is highly desirable to optimize the antibiotic production, several methods have been proposed aimed at this objective. Once having a mathematical model for the bioprocess, the optimization problem can be formulated within the framework of Pontryagin's maximum principle and of the optimal control theory to determinate the best control trajectory for certain key manipulated variables, such as temperature, pH, and substrate feed rate. In this chapter, applications of these model-based techniques to optimize and control antibiotics production bioprocesses are reviewed and new aspects are emphasized. The cases analyzed included the optimization of the substrate feed rate in a fed-batch reactor and of the temperature in a batch reactor during penicillin fermentations. The main contributions of this study were: (i) the proposition of a different procedure for calculating the second switching time of substrate feed rate, (ii) the application of simpler numerical methods to solve the two-point boundary-value problem associated with the temperature profile optimization, and (iii) the demonstration that the non-isothermal operation is more productive in antibiotic than the operation under constant temperature.

show abstract

“…[Parulekar85] and [Lim86] calculated the optimal glucose feeding policy in a fed-batch fermentation. [Chu87] computed the optimal temperature and pH profiles for a batch Cephalosporin C fermentation. An iterative run-to-run input profile optimization by using the plant data in addition to an approximate model of the reactor is presented in [Zafiriou90].…”

Section: Motivation For This Workmentioning

confidence: 99%