Performance modeling and simulation of biochemical process sequences with interacting unit operations

• Published in: Biotechnology and bioengineering Vol. 67; no. 3; pp. 300 - 311
• Main Authors: Groep, M. E., Gregory, M. E., Kershenbaum, L. S., Bogle, I. D. L.
• Format: Journal Article
• Language: English
• Published: New York John Wiley & Sons, Inc 05.02.2000; Wiley
• Subjects: Alcohol Dehydrogenase - metabolism; Biochemistry; Biological and medical sciences; Biotechnology; Biotechnology - methods; Biotechnology - standards; Centrifugation - methods; Centrifugation - standards; Chemical Precipitation; Computer simulation; Enzyme engineering; Enzymes; Fermentation; Fermentation - physiology; Fundamental and applied biological sciences. Psychology; Fungal Proteins - metabolism; interaction; Mathematical models; Methods. Procedures. Technologies; modeling; Models, Biological; operations; Optimization; Process engineering; Production of selected enzymes; Saccharomyces cerevisiae; sequence; simulation; Purification; Enzyme; Production; Fermentation; Mathematical model; Operating process; Modeling; Optimization; Operating conditions
• ISSN: 0006-3592; 1097-0290
• DOI: 10.1002/(SICI)1097-0290(20000205)67:3<300::AID-BIT6>3.0.CO;2-P

Many biochemical processes consist of a sequence of operations for which optimal operating conditions (setpoints) have to be determined. If such optimization is performed for each operation separately with respect to objectives defined for each operation individually, overall process performance is likely to be suboptimal. Interactions between unit operations have to be considered, and a unique objective has to be defined for the whole process. This paper shows how a suitable optimization problem can be formulated and solved to obtain the best overall set of operating conditions for a process. A typical enzyme production process has been chosen as an example. In order to arrive at a demonstrative model for the entire sequence of unit operations, it is shown how interaction effects may be accommodated in the models. Optimal operating conditions are then determined subject to a global process objective and are shown to be different from those resulting from optimization of each separate operation. As this strategy may result in an economic benefit, it merits further research into interaction modeling and performance optimization. © 2000 John Wiley & Sons, Inc. Biotechnol Bioeng 67: 300–311, 2000.