Optimization of Diphtheria Toxoid Production Process: Design and Evaluation of Production Yield and Costs using SuperPro Designer

Esmaeilnejad-Ahranjani, Parvaneh; Zahmatkesh, Azadeh

Optimization of Diphtheria Toxoid Production Process: Design and Evaluation of Production Yield and Costs using SuperPro Designer

Document Type : Original Research

Authors

Parvaneh Esmaeilnejad-Ahranjani

Azadeh Zahmatkesh

Department of Anaerobic Bacterial Vaccine Research and Production, Razi Vaccine and Serum Research Institute, Agricultural Research, Education and Extension Organization (AREEO), Karaj

Abstract

The process of diphtheria toxoid production was designed by using SuperPro Designer and the effect of the applied changes in process on the yield and costs of the manufacturing was investigated. First, giving the information of the real process of the toxoid production, a bioreactor with improved operational conditions and a disc stack centrifuge instead of the filter press, which is applied for the bacterial debris separation, were utilized. Such alterations followed the addition of a pump between the bioreactor and centrifuge. The results indicated that improvement of the bioreactor operational conditions can lead to the 25% increase in the toxin production, i.e., the increase of toxoid production from 7,000,000 doses to 8,750,000 doses. The toxin waste through filter press (14%) may be remarkably reduced by using the centrifuge, which in turn resulted in the 44% enhancement in the toxoid production. Such alterations can result in the 16% reduction in the separation operation time, 29% reduction in water consumption and 32% increase in the energy consumption. Overall, the simulation results showed that the costs of the new equipment suggested to be used in the improved process can be recoverable through running two batches.

Keywords

Process design

SuperPro Designer software

Optimization

Bioreactor

Centrifuge

Subjects

Industrial Biotechnology

[1] Choe, S., Bennett, M. J., Fujii, G., Curmi, P. M. G., Kantardjieff, K. A., Collier R. J., and Eisenberg D. (1992) The crystal structure of diphtheria toxin. Nature 357, 216-222.
[2] Jegatheeswaran, S., and Ein-Mozaffari, F. (2020) Investigation of the detrimental effect of the rotational speed on gas holdup in non-Newtonian fluids with Scaba-anchor coaxial mixer: A paradigm shift in gas-liquid mixing. Chem. Eng. J. 383, 123118.
[3] Wang, B., Zhang, K., and Field, R. W. (2018) Slug bubbling in flat sheet MBRs: Hydrodynamic optimization of membrane design variables through computational and experimental studies. J. Membr. Sci. 548, 165-175.
[4] Pino, M. S., Rodríguez-Jasso, R. M., Michelin, M., Flores-Gallegos, A. C., Morales-Rodriguez, R., Teixeira, J. A., and Ruiz, H. A. (2018) Bioreactor design for enzymatic hydrolysis of biomass under the biorefinery concept. Chem. Eng. J. 347, 119-136.
[5] Bach, C., Yang, J., Larsson, H., Stocks, S. M., Gernaey, K. V., Albaek, M. O., and Krühne, U. (2017) Evaluation of mixing and mass transfer in a stirred pilot scale bioreactor utilizing CFD. Chem. Eng. Sci. 171, 19-26.
[6] Moilanen, P., Laakkonen, M., Visuri, O., Alopaeus, V., and Aittamaa, J. (2008) Modelling mass transfer in an aerated 0.2 m3 vessel agitated by Rushton, Phasejet and Combijet impellers. Chem. Eng. J. 142, 95-108.
[7] Bezzo, F., Macchietto, S., and Pantelides, C. C. (2003) General hybrid multizonal/CFD approach for bioreactor modeling. AIChE J. 49, 2133-2148.
[8] Khopkar, A. R., and Tanguy, P. A. (2008) CFD simulation of gas-liquid flows in stirred vessel equipped with dual rushtonturbines: Influence of parallel, merging and diverging flow configurations. Chem. Eng. Sci. 63, 3810-3820.
[9] Ahmed, S. U., Ranganathan, P., Pandey, A., and Sivaraman, S. J. (2010) Computational fluid dynamics modeling of gas dispersion in multi impeller bioreactor. Biosci. Bioeng. 109, 588-597.
[10] Shu, L., Yang, M., Zhao, H., Li, T., Yang, L., and Zou X. (2019) Process optimization in a stirred tank bioreactor based on CFD-Taguchi method: A case study. J. Clean. Prod. 230, 1074-1084.
[11] Mowbray, M., Savage, T., Wu, C., Song, Z., Cho, B. A., Rio-Chanona, E. A. D., and Zhang, D. (2021) Machine learning for biochemical engineering: A review. Biochem. Eng. J. 172, 108054.
[12] Rathore, A. S. (2009) Roadmap for implementation of quality by design (QbD) for biotechnology products. Trends Biotechnol. 27, 546-553.
[13] Chlup, P. H., Bernard, D., and Stewart, G. G. (2008) Disc stack centrifuge operating parameters and their impact on yeast physiology. J. Inst. Brew. 114, 45-61.
[14] Shekhawata, L. K., Sarkara, J., Guptaa, R., Hadpeb, S., and Rathorea, A. S. (2018) Application of CFD in Bioprocessing: Separation of mammalian cells using disc stack centrifuge during production of biotherapeutics. J. Biotechnol. 267, 1-11.
[15] Shah, M. T., Parmar, H. B., Rhyne, L. D., Kalli, C., Utikar, R. P., and Pareek, V. K. (2019) A novel settling tank for produced water treatment: CFD simulations and PIV experiments. J. Pet. Sci. Eng. 182, 106352.
[16] Fernandez, X. R., and Nirschl H. (2013) Simulation of particles and sediment behaviour in centrifugal field by coupling CFD and DEM. Chem. Eng. Sci. 94, 7-19.
[17] Harrison, R. G., Todd, P. W., Rudge, S. R., and Petrides, D. P. (2015) Bioseparations Science and Engineering Oxford University Press, ISBN 978-0-19-539181-7.
[18] Petrides, D., Carmichae, D., Siletti, C., and Koulouris, A. (2014) Biopharmaceutical process optimization with simulation and scheduling tools. Bioengineering 1, 154-187.
[19] Rakicka-Pustułka, M., Mirończuk, A. M., Celińska, E., Białas, W., and Rymowicz, W. (2020) Scale-up of the erythritol production technology–Process simulation and techno-economic analysis. J. Clean. Prod. 257, 120533.
[20] Toumi, A., Jurgens, C., Jungo, C., Maier, B., Papavasileiou, V., and Petrides, D. (2010) Design and optimization of a large scale biopharmaceutical facility using process simulation and scheduling tools. Pharm. Eng. 30, 1-9.
[21] Prazeres, D. M. F., and Ferreira G. N. M. (2004) Design of flowsheets for the recovery and purification of plasmids for gene therapy and DNA vaccination. Chem. Eng. Process. 43, 609-624.
[22] Pleitt, K., Somasundaram, B., Johnson, B., Shave, E., and Lua, L. H. L. (2019) Evaluation of process simulation as a decisional tool for biopharmaceutical contract development and manufacturing organizations. Biochem. Eng. J. 150, 107252.
[23] Esmaeilnejad-Ahranjani, P., and Hajimoradi, M. (2022) Optimization of industrial-scale centrifugal separation of biological products: comparing the performance of tubular and disc stack centrifuges. Biochem. Eng. J. 178, 108281.
[24] Esmaeilnejad-Ahranjani, P., Noofeli, M., Faramarzi, A., (2022) Optimization of an industrial aerobic bioreactor using combined CFD, scale-down, and experimental techniques, Iran. J. Chem. Chem. Eng. https://doi.org/10.30492/ijcce.2022.532530.4799.
[25] Zarei, M., Shahpiri, A., Esmaeilnejad-Ahranjani, P., Arpanaei, A., (2016) Metallothionein-immobilized silica-coated magnetic particles as a novel nanobiohybrid adsorbent for highly efficient removal of cadmium from aqueous solutions. RSC Adv. 6:46785-46793.
[26] Esmaeilnejad-Ahranjani, P., Kazemeini, M., Singh, G., and Arpanaei, A. (2018) Effects of physicochemical characteristics of magnetically recoverable biocatalysts upon fatty acid methyl esters synthesis from oils. Renew. Energy 116, 613-622.
[27] Faramarzi, A., Noofeli, M., Tofighi, A., and Shahcheraghi, F. (2020) Comparison of the diphtheria toxin separation methods on standard vaccine strain using separator and filter presses to improve the quality & quantity of the final product. Jundishapur Sci. Med. J. 18, 459-470.
[28] Limonta, M., Krajnc, N. L., Vidic, U., and Zumalacárregui, L. (2013) Simulation for the recovery of plasmid for a DNA vaccine. Biochem. Eng. J. 80, 14-18.
[29] Pang, Y. X., Yan, Y., Foo, D. C. Y., Sharmin, N., Zhao, H., Lester, E., Wu, T., and Pang, C. H. (2021) The influence of lignocellulose on biomass pyrolysis product distribution and economics via steady state process simulation. J. Anal. Appl. Pyrolysis 158, 104968.
[30] Bajić, B. Ž., Vučurović, D. G., Dodić, S. N., Grahovac, J. A., and Dodić, J. M. (2017) Process model economics of xanthan production from confectionery industry wastewaters. J. Environ. Manage. 203, 999-1004.