PenSim: A Web Based Program for Dynamic Simulation of Fed-Batch Penicillin Production 

Production of secondary metabolites has been the subject of many studies because of its academic and industrial importance. Filamentous microorganisms (Figure 1) are used commercially for the production of secondary metabolites such as antibiotics. The formation of the target product, the antibiotic, is usually not associated with cell growth. For this reason, it is common practice to grow the microorganisms in a batch culture followed by a fed-batch operation to promote the synthesis of the antibiotic (Birol et al., 1999; Birol et al., 2000b; Atkinson and Mavituna, 1991). There is a voluminous literature on penicillin production with varying degrees of complexities ( Heijnen et al., 1979; Bajpai and Reuss, 1980; Nestaas and Wang, 1983; Menezes et al. 1994). The book by Nielsen is an excellent source for the interested reader in all aspects of penicillin production (Nielsen 1997). 

In this simulator, we have extended the mechanistic model of Bajpai and Reuss (Bajpai and Reuss, 1980). Details of the model development can be found in Birol et al. (2000). Briefly speaking, the mechanistic model has been substantially augmented by the inclusion of aeration rate, agitation power, feed flow rates of substrate and oxygen, carbon dioxide concentration, feed coolant and bioreactor temperatures, generated heat and the medium pH. The schematic representation of the process can be seen in Figure 2. In a typical penicillin production process, the bioreactor is switched to the fed-batch mode of operation ca. after 40 hours of batch growth phase when the cells enter their stationary phase. Figure 3 shows time profiles of glucose, penicillin, biomass and oxygen for a typical run.

Figure 1. Growth of Filamentous Microorganisms.
Figure 2. A Flowsheet of the Process.
Figure 3. Time Profiles of Glucose, Penicillin, Biomass Concentrations and Dissolved Oxygen.
Atkinson B. and Mavituna F. Biochemical Engineering and Biotechnology Handbook, Stockton Press, New York, 1991.

Bailey J.E. and Ollis D.F. Biochemical Engineering Fundamentals, McGraw Hill, Singapoure, 1986.

Bajpai R.K. and Reuss M. "A Mechanistic Model for Penicillin Production" J. Chem. Technol. And Biotechnol. 30, 332-344, 1980.

Birol I., Undey C., Birol G. and Cinar A."A User-friendly, Bioprocess Simulator for Teaching Process Dynamics and Control" AICHE 00 Annual Meeting, to be presented, Los Angeles, CA., November 12-17, 2000.

Birol G., Undey C. and Cinar A. "A Modular Simulation Package for Penicillin Production" Submitted to Computers and Chemical Engineering, 2000b.

Birol G., Undey C., Williams B., Parulekar S.J. and Cinar A."A Comparative Study on the Modeling of Penicillin Fermentation" AICHE 99 Annual Meeting, Dallas, TX, 1999.

Heijnen J.J., Roels J.A. and Stouthamer A.H. "Application of Balancing Methods in Modeling the Penicillin Fermentation", Biotechnol. Bioeng., 21, 2175-2201, 1979.

Menezes J.C., Alves S.S., Lemos J.M. and Azevedo S.F. "Mathematical Modeling of Industrial Pilot-Plant Penicillin G Fed-Batch Fermentation" J. Chem Technol. Biotechnol., 61, 123-138, 1994.

Montague G.A., Morris A.J., Wright A.R. M/ Aynsley and Ward A. "Growth Monitoring and Control Through Computer-aided On-line Mass Balancing in Fed-batch Penicillin Fermentation" Can. J. Chem. Eng., 64,567-580, 1986.

Nestaas E. and Wang D.I.C. "Computer Control of the Penicillin Fermentation Using the Filtration Probe in Conjunction with a Structured Process Model" Biotechnol. Bioeng., 25, 781-796, 1983.

Nielsen J., Physiological Engineering Aspects of Penicillium Chrysogenum, World Scientific, Singapore, 1997.

Pirt S.J. and Righoletto R.C. "Effect of Growth Rate on the Synthesis of Penicillin by Penicillium chrysogenum in Batch and Chemostat Cultures" Applied Microbiol. 15, 1284-1290, 1967.

Undey C., Williams B.A., Birol G., Parulekar S.J. and Cinar A. "Multivariate Statistical Monitoring of Penicillin Fermentation" AICHE 99 Annual Meeting, Dallas, TX, 1999.