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A Simulation Analysis of an Influenza Vaccine Production Plant in Areas of High Humanitarian Flow. A Preliminary Study for the Region of Norte de Santander (Colombia)

Jefferson E. Contreras-Ropero
Silvia L. Ruiz-Roa
Janet B. García-Martínez
Néstor A. Urbina-Suarez
Germán L. López-Barrera
Andrés F. Barajas-Solano
1 and
Antonio Zuorro
Department of Environmental Sciences, Universidad Francisco de Paula Santander, Av. Gran Colombia, No. 12E-96, Cucuta 540003, Colombia
Department of Clinical Care and Rehabilitation, Universidad Francisco de Paula Santander, Av. Gran Colombia No. 12E-96, Cucuta 540003, Colombia
Department of Chemical Engineering, Materials and Environment, Sapienza University, Via Eudossiana 18, 00184 Roma, Italy
Author to whom correspondence should be addressed.
Appl. Sci. 2022, 12(1), 183;
Submission received: 27 October 2021 / Revised: 11 December 2021 / Accepted: 21 December 2021 / Published: 24 December 2021
(This article belongs to the Section Food Science and Technology)


The production of vaccines of biological origin presents a tremendous challenge for researchers. In this context, animal cell cultures are an excellent alternative for the isolation and production of biologicals against several viruses, since they have an affinity with viruses and a great capacity for their replicability. Different variables have been studied to know the system’s ideal parameters, allowing it to obtain profitable and competitive products. Consequently, this work focuses its efforts on evaluating an alternative for producing an anti-influenza biological from MDCK cells using SuperPro Designer v8.0 software. The process uses the DMEN culture medium supplemented with nutrients as raw material for cell development; the MDCK cells were obtained from a potential scale-up with a final working volume of 500 L, four days of residence time, inoculum volume of 10%, and continuous working mode with up to a total of 7400 h/Yr of work. The scheme has the necessary equipment for the vaccine’s production, infection, and manufacture with yields of up to 416,698 units/h. In addition, it was estimated to be economically viable to produce recombinant vaccines with competitive prices of up to 0.31 USD/unit.

1. Introduction

Influenza is an acute viral infection that can cause symptoms ranging from mild to severe, including bronchitis, pneumonia, and death, especially in patients with risk factors [1]. Unlike in the United States, where there is one influenza season, in Colombia, it occurs in two peaks (March–June, and September–November) [2]. In 2019, prior to the COVID-19 emergency, approximately 6.7 million people suffered symptomatic influenza infection, with over twenty thousand hospitalizations in intensive care units; most of these cases were reported in the region of Norte de Santander [2]. The region of Norte de Santander is located on the northeast side of Colombia and shares a wide border with Venezuela. Due to the economic instability experienced in the last 10 years by the neighboring country, a substantial share of their citizens have migrated to Colombia and other Latin American countries using the control border located in the cities of Cucuta and Villa del Rosario [3].
In 2012, the Colombian Ministry of Health (Minsalud) launched the Ten-Year Public Health Plan (PDSP) 2012–2021 as a tool to strengthen access to health in an equitable and egalitarian way throughout the national territory [4]. According to the ministry, the age-specific mortality rate for transmissible diseases in Norte de Santander is higher than the national median (46.8 and 34.50, respectively) [5]. For the region of Norte de Santander, respiratory infections accounted for 40% of care in all subgroups of the general population, also showing a trend towards an increase in cases [6]. The best way to control influenza outbreaks is through vaccination [7]; however, barriers to global implementation of vaccine production such as limited manufacturing, vaccine cost, and suboptimal efficacy [8] hampers the efforts to avoid unnecessary death. Despite the importance of vaccine production, no companies in Colombia are focused on producing influenza vaccines to the best of the author’s knowledge.
SuperPro Designer® is a process simulator explicitly developed for the modeling, evaluation, and optimization of bioprocess unit operations [9], which can be used from conceptual design, process operation, and optimization [10], as well as process economics and waste stream characterization [11]. The present work carried out a preliminary study of an influenza vaccine production plant, using SuperPro Designer® v8.0 as an initial alternative for vaccine production in Colombia.

2. Materials and Methods

2.1. Process Description

The process of vaccine production using recombinant viruses and animal cell cultures consists of three critical steps that correspond to two industrial faces of the process (Upstream and Downstream). In the first step (Cell Propagation), MDCK cells (CCL-34TM) are produced in DMEM culture medium (mainly composed of amino acids, sodium pyruvate, vitamin B12, biotin, and ascorbic acid) [12]; this media is used with a wide variety of suspension cells and adherent mammalian cells including keratinocytes, primary rat astrocytes, and human melanoma cells [13].
Once the desired cell concentration is obtained, the cells are transferred to fermenters with higher working volumes (pre-inoculum). Once the optimal cell density is reached, the cells are transferred and incubated with the virus A/HK/403946/09 (H1N1) [14] (also known as virus infection and propagation) under specific culture conditions (37 ± 1 °C, pH of 7.4) [15]. The final stage (downstream) consists of the liberation, elicitation, purification, inactivation, formulation, and packaging of the vaccine (Figure 1).

2.2. Plant Simulation

The influenza vaccine production plant was simulated using SuperPro Designer® software v8.0. (Intelligen, Inc., Scotch Plains, NJ, USA). This software allows us to compare different pre-treatment processes, production, consumption, and yields, making the process technically and economically feasible over time.

3. Results

Recombinant retroviruses and the massive culture of animal cell lines are fundamental techniques for large-scale biotechnological inputs to produce viral vaccines [16]. These vaccines are recombinant molecules obtained by expressing or replacing exogenous gene fragments in the host cell genome, which can be dispensed in the other cell sequences [17]. However, the production of retroviruses presents some difficulties, such as the need for a deep knowledge of the culture at different scales and the recovery technologies of these products; therein lies the importance of using simulation software to obtain production and cost estimates at an industrial level.
The use of simulators to model industrial processes is becoming more and more popular every day because it provides the opportunity to improve and reduce the time needed to generate different processes that integrate great applicability in different industrial branches [18]. These techniques are mainly based on the use and schematization of the process using mathematical tools and software, where all those independent and dependent variables (mass and energy balance) of the various biological and mechanical systems that make up the process are detailed to predict the natural behavior of the plant [19]. It also considers different aspects, including economic aspects such as construction, labor, equipment, waste, and total costs for the manufacturing and maintenance of the system. The operational, economic parameters of the system were classified in different sections: in the first one, we will find the total direct process costs (TIC), which include equipment, construction, maintenance, and labor (Total investment cost) (Equation (1)).
According to Table 1, the main items that influence the total direct cost of the plant (TPDC) are equipment purchase, construction, and adaptation with percentages of up to 41, 11, and 10%, respectively, of the total TPDC. In contrast, the items related to the construction of the infrastructure is the element that has the most significant impact on the indirect costs of silver (TAC) (Table 2).
Table 3 shows that the costs associated with the security of the project cover up to 10% of the total needed for the implementation of the system (CFD). Finally, Table 4 and Table 5 show the operational costs of the equipment and raw materials of the system in question. The culture medium is a critical parameter within the production process, occupying up to 35% of raw materials.

3.1. Upstream

The upper part of Figure 2 shows the upstream scheme of the vaccine production system. The cells are strongly dependent on different factors such as nutrient concentration, gas injection, agitation, and other variables; therefore, the preparation and maintenance of the culture medium and culture system to be used are of great importance. In the present process, the DMEM culture medium is sterilized by dry steam (P2/ST-101) and supplemented by Fetal Bovine Serum (S-114). The scale-up process is increased up to a final working volume of 500 L (R4-/500) with a 10% (v/v) inoculum of MDCK cells (CCL-34TM) until reaching a cell density of 1.0 × 105 cells/mL, which allows decreasing the oncogenic capacity of the final product [20]. Likewise, the growth conditions were maintained at pH 7.4, 37 °C and 100% dissolved oxygen for the first 24 h, and then a reduction of up to 50% in oxygen saturation in the reactor [17]. The infection phase was performed considering the MOI multiplicity of infection factor of 2 [21], decreasing up to 13% of the cells not infected by the virus. Each reactor had a residence time of 4 days. Infection and virus adaptation was performed in stoichiometric fermentation with an infection rate of 87% of the produced cells. It is essential to highlight that the virus selected for the present analysis has a high capacity for infection, reproduction, and adaptation in different types of cells such as respiratory, muscular, and kidney tissues, among others [14]. About 20 log10 genome copies/mL were obtained in the final fermentation process [22].

3.2. Downstream

The lower part of Figure 2 shows the downstream scheme of the vaccine production system. The process of obtaining the raw material begins with a bead mill (Bead Melling P-6/BM101) which accelerates cell lysis allowing the release of the viruses inside the cells; purification begins with precipitation using isopropanol at 50 °C at a ratio of 1:2, which is based on the differential solubility of the genetic material of the virion and is based on the decrease in the dielectric constant of the aqueous solvent, causing a decrease in the solubility of the DNA that allows the material to be separated and subsequently subjected to centrifugation (P-9/CF-101) to eliminate cellular debris.
Inactivation plays a vital role in this phase since it is only necessary to leave the genetic material inactive and the surface proteins unchanged so that it can be recognized by the immune system without affecting it, generating specialized antibodies for the destruction of its envelope. This allows the virion particles to be chemically inactivated with binary ethylamine (BEI) [23] and subsequently purified by salting out. These residual salts that allow the concentration of the vaccine are removed by microfiltration (P-8/MF-101) after washing to facilitate the permeation of the components and eliminate suspended solids, bacteria, proteins, or some dyes that may have been immersed in the inactivated virus [24]. Finally, the entire purified volume is mixed with adjuvants, Penicillin, Streptomycin, Amphotericin B, and salts as an antibiotic, antifungal, and preservative of the compound. Each vial is packed to a volume of 1 mL, containing 20 μg of inactivated influenza virus for a total yield of 3,083,569,629 units/yr.
Several authors have shown that the implementation of antigens using cell lines originating from different organs has facilitated the breakthrough in vaccine production since it allows the generation of biologics in a more accelerated way, with characteristics and public health standards that can compete with other vaccines [14,25]. However, according to several authors, animal cellular tissues have a high immunogenicity and safety capacity for producing attenuated viruses [26,27,28,29].

4. Discussion

The cases of influenza in the region of Norte de Santander are of great importance for the epidemiological monitoring of respiratory diseases since its proximity to Venezuelan cities makes it an epidemiological focus that should be monitored. According to the Regional Institute of Health of Norte de Santander, the demand for health care services for communicable conditions ranked second in 2009–2018, with a slight upward trend at all times of the life course and in both genders. Likewise, within the subgroup of communicable conditions, respiratory infections accounted for 40% of care in all general population subgroups, showing an increasing trend in the frequency of these conditions [6]. The Expanded Program of Immunization implemented by the Colombian Ministry of health guarantees free access to influenza vaccines for infants only after completing the first year of life [30]. In the case of the adult population, free annual access to this biologic only benefits the population over 60 years of age, evidencing a failure in the coverage of access to this biologic in the general population, which is even more worrisome for the population of Norte de Santander, knowing the morbidity and mortality indicators previously mentioned [6]. The availability of interventions to meet this public health need, including annual access to influenza vaccine within the expanded program of immunizations, could prevent two-thirds of deaths from respiratory infections in children under five years of age, as well as reduce the demand for health care due to respiratory infections in all population groups in the Region of Norte de Santander [30].
Based on the modeling of the manufacturing process (Figure 2) and the information about the costs of setting up the system (Table 1, Table 2, Table 3, Table 4 and Table 5), it is possible to determine that the annual revenue is estimated at USD 1079 million with an opportunity cost of sale of an additional 10% of the production value. Additionally, based on the sale of USD 0.35 per unit, the payback period of the investment is 11.2 months, followed by annual liabilities of USD 103 million. The calculation of the gross cost of the product was obtained by dividing the number of doses obtained by the total cost of production, resulting in a cost of 0.31 USD/unit, the most relevant component being the operational cost of manufacturing. In work carried out by Aliya Mohamad Ros et al. [31], they evaluated the production of influenza vaccines using the Vero cell line. Their results identified that changes in cell line production kinetics affect the system’s total cost. Likewise, and according to Farid [32], and Nestola et al. [33], the variables involved in the purification phase are the costliest (50%), followed by the production and maintenance phase (Table 4 and Table 5). The processing, recovery, and purification of the different products associated with viral vaccines are critical processes for the stability of the process. Different techniques such as microfiltration have been considered for this stage; this technique can reduce costs by up to 70% compared to chromatography [24]. On the other hand, another possible way to reduce the size of the investment in fermentation equipment is the use of perfusion reactors; however, the difference lies in the initial investment costs since the production costs per unit are partially similar [34,35,36].
According to the results obtained in Table 4 and Table 5, the manufacturing costs were about 30 times higher than the costs of plant establishment, mainly since the energy requirements for the physiological needs of the cell culture are high [37]. Likewise, in establishing the vaccine production system, the different costs related to vaccine supply and distribution were not considered, since the literature on the optimization of vaccine production in developing countries is quite scarce. However, according to Lee et al. [38], the costs of vaccine supply chains in developing countries are as much as 5 to 28 times lower than the total cost of production [39,40,41]. Likewise, the model presented here does not evaluate new emerging vaccine production technologies such as SARS-CoV2, since different kinetic parameters may change the model’s performance. However, it presents a lean approach to the industrial production system for vaccines of viral origin, estimating the different construction and production costs.

5. Conclusions

The production cost of the vaccine was estimated at 0.31 USD/unit, which is lower than the sales value of the producing pharmaceutical companies; however, this should be verified in a complete and detailed way for each operation, since the midstream sector, which includes transportation, storage, and commercialization of the product, was not considered. The implementation of SuperPro Designer® as a tool allowed considering the impact of the technical and economic analysis based on experimental studies, allowing the development of improvements in different production processes in comparison with alternative unitary operations, and the interaction of them with the other variables on a large scale. This also exposes that the raw material and size of cell production are a key part of the process.

Author Contributions

Conceptualization, J.E.C.-R., J.B.G.-M. and A.F.B.-S.; methodology, J.E.C.-R. and S.L.R.-R.; software, J.E.C.-R. and N.A.U.-S.; validation, A.Z. and G.L.L.-B.; formal analysis, J.E.C.-R. and, A.Z.; investigation, J.B.G.-M. and, S.L.R.-R.; resources, A.F.B.-S. and G.L.L.-B.; data curation, A.Z.; writing—original draft preparation, J.E.C.-R. and, J.B.G.-M.; writing—review and editing, A.F.B.-S. and A.Z.; visualization, N.A.U.-S.; supervision, A.Z.; project administration, A.F.B.-S. and N.A.U.-S.; funding acquisition, A.F.B.-S., N.A.U.-S. and, G.L.L.-B. All authors have read and agreed to the published version of the manuscript.


This paper was supported by Universidad Industrial de Santander and the Colombian Ministry of Science Technology and Innovation MINCIENCIAS with the project “Strengthening of the scientific-technological capabilities of the molecular biology Laboratory-UFPS as a tool for the biology laboratory as a tool for the diagnosis of biological agents of high risk to human health” BPIN 2020000100123.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.


We would like to express our sincere gratitude to Universidad Francisco de Paula Santander (Colombia) and Sapienza University of Rome (Italy) for providing the equipment for this review and the Colombian Ministry of Science Technology and Innovation MINCIENCIAS for the support to national Ph.D. Doctorates through the Francisco José de Caldas scholarship program.

Conflicts of Interest

The authors declare no conflict of interest.


  1. Reed, C.; Chaves, S.S.; Kirley, P.D.; Emerson, R.; Aragon, D.; Hancock, E.B.; Butler, L.; Baumbach, J.; Hollick, G.; Bennett, N.M.; et al. Estimating Influenza Disease Burden from Population-Based Surveillance Data in the United States. PLoS ONE 2015, 10, e0118369. [Google Scholar] [CrossRef] [PubMed]
  2. Instituto Nacional de Salud. Acute Respiratory Infection Event Report, Colombia, 2019. Available online:ÓN%20RESPIRATORIA%20AGUDA_2019.pdf (accessed on 11 September 2021).
  3. International Organization for Migration. DTM Survey—Vocation of Venezuelan Population to Stay in Colombia, Colombia, 2020. Available online: (accessed on 10 December 2021).
  4. Ministerio de Salud y Protección Social de Colombia. Ten-Year Public Health Plan 2012–2021 of Colombia. 2012. Available online: (accessed on 11 September 2021).
  5. Ministerio de Salud y Protección Social de Colombia. ABC of the Ten-Year Public Health Plan. Available online: (accessed on 11 September 2021).
  6. Instituto Departamental de Salud de Norte de Santander. Health Situation Analysis with the Social Determinants Model Norte de Santander Department 2019, Colombia. 2019. Available online: (accessed on 10 December 2021).
  7. Athimulam, A.; Kumaresan, S.; Foo, D.; Sarmidi, M.; Aziz, R. Modelling and Optimization of Eurycoma longifolia Water Extract Production. Food Bioprod. Process. 2006, 84, 139–149. [Google Scholar] [CrossRef] [Green Version]
  8. Sparrow, E.; Wood, J.G.; Chadwick, C.; Newall, A.T.; Torvaldsen, S.; Moen, A.; Torelli, G. Global production capacity of seasonal and pandemic influenza vaccines in 2019. Vaccine 2021, 39, 512–520. [Google Scholar] [CrossRef] [PubMed]
  9. Jiang, B.; Patel, M.; Glass, R.I. Polio endgame: Lessons for the global rotavirus vaccination program. Vaccine 2019, 37, 3040–3049. [Google Scholar] [CrossRef]
  10. Canizales, L.; Rojas, F.; Pizarro, C.A.; Caicedo-Ortega, N.H.; Villegas-Torres, M.F. SuperPro Designer®, User-Oriented Software Used for Analyzing the Techno-Economic Feasibility of Electrical Energy Generation from Sugarcane Vinasse in Colombia. Processes 2020, 8, 1180. [Google Scholar] [CrossRef]
  11. Ernst, S.; Garro, O.A.; Winkler, S.; Venkataraman, G.; Langer, R.; Cooney, C.L.; Sasisekharan, R. Process simulation for recombinant protein production: Cost estimation and sensitivity analysis for heparinase I expressed in Escherichia coli. Biotechnol. Bioeng. 1997, 53, 575–582. [Google Scholar] [CrossRef]
  12. Huang, D.; Xia-Hou, K.; Liu, X.-P.; Zhao, L.; Fan, L.; Ye, Z.; Tan, W.-S.; Luo, J.; Chen, Z. Rational design of medium supplementation strategy for improved influenza viruses production based on analyzing nutritional requirements of MDCK Cells. Vaccine 2014, 32, 7091–7097. [Google Scholar] [CrossRef]
  13. Genzel, Y. Designing cell lines for viral vaccine production: Where do we stand? Biotechnol. J. 2015, 10, 728–740. [Google Scholar] [CrossRef]
  14. Li, I.; Chan, K.; To, K.; Wong, S.; Ho, P.L.; Lau, S.K.P.; Woo, P.C.Y.; Tsoi, H.; Chan, J.F.-W.; Cheng, V.; et al. Differential susceptibility of different cell lines to swine-origin influenza A H1N1, seasonal human influenza A H1N1, and avian influenza A H5N1 viruses. J. Clin. Virol. 2009, 46, 325–330. [Google Scholar] [CrossRef]
  15. Fontana, D.; Marsili, F.; Garay, E.; Battagliotti, J.; Etcheverrigaray, M.; Kratje, R.; Prieto, C. A simplified roller bottle platform for the production of a new generation VLPs rabies vaccine for veterinary applications. Comp. Immunol. Microbiol. Infect. Dis. 2019, 65, 70–75. [Google Scholar] [CrossRef]
  16. Dewannieux, M.; Ribet, D.; Heidmann, T. Risks linked to endogenous retroviruses for vaccine production: A general overview. Biologicals 2010, 38, 366–370. [Google Scholar] [CrossRef]
  17. George, M.; Farooq, M.; Dang, T.; Cortes, B.; Liu, J.; Maranga, L. Production of cell culture (MDCK) derived live attenuated influenza vaccine (LAIV) in a fully disposable platform process. Biotechnol. Bioeng. 2010, 106, 906–917. [Google Scholar] [CrossRef]
  18. Limonta, M.; Krajnc, N.L.; Vidič, U.; Zumalacárregui, L. Simulation for the recovery of plasmid for a DNA vaccine. Biochem. Eng. J. 2013, 80, 14–18. [Google Scholar] [CrossRef]
  19. Petrides, D.; Carmichael, D.; Siletti, C.; Koulouris, A. Biopharmaceutical Process Optimization with Simulation and Scheduling Tools. Bioengineering 2014, 1, 154. [Google Scholar] [CrossRef]
  20. Liu, J.; Mani, S.; Schwartz, R.; Richman, L.; Tabor, D.E. Cloning and assessment of tumorigenicity and oncogenicity of a Madin–Darby canine kidney (MDCK) cell line for influenza vaccine production. Vaccine 2010, 28, 1285–1293. [Google Scholar] [CrossRef]
  21. Guerriero, V. Power Law Distribution: Method of Multi-Scale Inferential Statistics. J. Mod. Math. Front. JMMF 2012, 1, 21–28. [Google Scholar]
  22. Youil, R.; Su, Q.; Toner, T.; Szymkowiak, C.; Kwan, W.-S.; Rubin, B.; Petrukhin, L.; Kiseleva, I.; Shaw, A.; DiStefano, D. Comparative study of influenza virus replication in Vero and MDCK cell lines. J. Virol. Methods 2004, 120, 23–31. [Google Scholar] [CrossRef]
  23. Valero, Y.; Olveira, J.; López-Vázquez, C.; Dopazo, C.; Bandín, I. BEI Inactivated Vaccine Induces Innate and Adaptive Responses and Elicits Partial Protection upon Reassortant Betanodavirus Infection in Senegalese Sole. Vaccines 2021, 9, 458. [Google Scholar] [CrossRef]
  24. Moyle, P.M. Progress in Vaccine Development. Curr. Protoc. Microbiol. 2015, 36, 18.1.1–18.1.26. [Google Scholar] [CrossRef]
  25. Frey, S.; Vesikari, T.; Szymczakiewicz-Multanowska, A.; Lattanzi, M.; Izu, A.; Groth, N.; Holmes, S. Clinical Efficacy of Cell Culture–Derived and Egg-Derived Inactivated Subunit Influenza Vaccines in Healthy Adults. Clin. Infect. Dis. 2010, 51, 997–1004. [Google Scholar] [CrossRef]
  26. Bart, S.; Cannon, K.; Herrington, D.; Mills, R.; Forleo-Neto, E.; Lindert, K.; Mateen, A.A. Immunogenicity and safety of a cell culture-based quadrivalent influenza vaccine in adults: A Phase III, double-blind, multicenter, randomized, non-inferiority study. Hum. Vaccines Immunother. 2016, 12, 2278–2288. [Google Scholar] [CrossRef] [Green Version]
  27. Hartvickson, R.; Cruz, M.; Ervin, J.; Brandon, D.; Forleo-Neto, E.; Dagnew, A.F.; Chandra, R.; Lindert, K.; Mateen, A.A. Non-inferiority of mammalian cell-derived quadrivalent subunit influenza virus vaccines compared to trivalent subunit influenza virus vaccines in healthy children: A phase III randomized, multicenter, double-blind clinical trial. Int. J. Infect. Dis. 2015, 41, 65–72. [Google Scholar] [CrossRef] [Green Version]
  28. Ambrozaitis, A.; Groth, N.; Bugarini, R.; Sparacio, V.; Podda, A.; Lattanzi, M. A novel mammalian cell-culture technique for consistent production of a well-tolerated and immunogenic trivalent subunit influenza vaccine. Vaccine 2009, 27, 6022–6029. [Google Scholar] [CrossRef]
  29. Szymczakiewicz-Multanowska, A.; Groth, N.; Bugarini, R.; Lattanzi, M.; Casula, D.; Hilbert, A.; Tsai, T.; Podda, A. Safety and Immunogenicity of a Novel Influenza Subunit Vaccine Produced in Mammalian Cell Culture. J. Infect. Dis. 2009, 200, 841–848. [Google Scholar] [CrossRef] [Green Version]
  30. Ministerio de Salud y Protección Social de Colombia. Guidelines for the Management and Administration of the Expanded Program on Immunization—API—2020, Colombia, 2020. Available online: (accessed on 10 December 2021).
  31. Aliya Mohamad Ros, F.N.; Rahman, N.A.; Ali, J.M.; Anuar, N.; Abdullah, S.R.B.S.; Yusoff, A.F.B.J. Comparative Study between Avian Cell and Mammalian Cell in Production of Influenza Vaccine Shariah Compliance. IOP Conf. Series Mater. Sci. Eng. 2020, 778, 12029. [Google Scholar] [CrossRef]
  32. Farid, S.S. Process economics of industrial monoclonal antibody manufacture. J. Chromatogr. B 2007, 848, 8–18. [Google Scholar] [CrossRef]
  33. Nestola, P.; Peixoto, C.; Silva, R.R.J.S.; Alves, P.M.; Mota, J.P.B.; Carrondo, M.J.T. Improved virus purification processes for vaccines and gene therapy. Biotechnol. Bioeng. 2015, 112, 843–857. [Google Scholar] [CrossRef]
  34. Yang, W.C.; Lu, J.; Kwiatkowski, C.; Yuan, H.; Kshirsagar, R.; Ryll, T.; Huang, Y.-M. Perfusion Seed Cultures Improve Bio-pharmaceutical Fed-Batch Production Capacity and Product Quality. Biotechnol. Prog. 2014, 30, 616–625. [Google Scholar] [CrossRef]
  35. Tapia, F.; Vázquez-Ramírez, D.; Genzel, Y.; Reichl, U. Bioreactors for high cell density and continuous multi-stage cultivations: Options for process intensification in cell culture-based viral vaccine production. Appl. Microbiol. Biotechnol. 2016, 100, 2121–2132. [Google Scholar] [CrossRef] [Green Version]
  36. Xu, J.; Xu, X.; Huang, C.; Angelo, J.; Oliveira, C.L.; Xu, M.; Xu, X.; Temel, D.; Ding, J.; Ghose, S.; et al. Biomanufacturing evolution from conventional to intensified processes for productivity improvement: A case study. MAbs 2020, 12, 1770669. [Google Scholar] [CrossRef]
  37. Rubio, A.P.; Eiros, J.M. Cell culture-derived flu vaccine: Present and future. Hum. Vaccines Immunother. 2018, 14, 1874–1882. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  38. Lee, B.Y.; Connor, D.L.; Wateska, A.R.; Norman, B.A.; Rajgopal, J.; Cakouros, B.E.; Chen, S.-I.; Claypool, E.G.; Haidari, L.A.; Karir, V.; et al. Landscaping the structures of GAVI country vaccine supply chains and testing the effects of radical redesign. Vaccine 2015, 33, 4451–4458. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  39. Chen, S.-I.; Norman, B.A.; Rajgopal, J.; Assi, T.M.; Lee, B.Y.; Brown, S. A planning model for the WHO-EPI vaccine distribution network in developing countries. IIE Trans. 2014, 46, 853–865. [Google Scholar] [CrossRef]
  40. Haidari, L.A.; Connor, D.L.; Wateska, A.R.; Brown, S.T.; Mueller, L.E.; Norman, B.A.; Schmitz, M.M.; Paul, P.; Rajgopal, J.; Welling, J.S.; et al. Augmenting Transport versus Increasing Cold Storage to Improve Vaccine Supply Chains. PLoS ONE 2013, 8, e64303. [Google Scholar] [CrossRef]
  41. Lemmens, S.; Decouttere, C.; Vandaele, N.; Bernuzzi, M. A review of integrated supply chain network design models: Key issues for vaccine supply chains. Chem. Eng. Res. Des. 2016, 109, 366–384. [Google Scholar] [CrossRef]
Figure 1. Process description of influenza vaccine production.
Figure 1. Process description of influenza vaccine production.
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Figure 2. Flow diagram of the production, procurement, and purification process of influenza vaccine.
Figure 2. Flow diagram of the production, procurement, and purification process of influenza vaccine.
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Table 1. Total direct plant cost (TPDC) (infrastructure costs).
Table 1. Total direct plant cost (TPDC) (infrastructure costs).
Items(USD $)
1. Equipment Purchase Cost7,755,000.00
2. Installation2,004,000.00
3. Process Piping1,680,000.00
4. Instrumentation1,921,000.00
5. Insulation144,000.00
6. Electrical480,000.00
7. Buildings2,161,000.00
8. Yard Improvement720,000.00
9. Auxiliary Facilities1,921,000.00
Table 2. Total Plant Indirect Cost (TAC).
Table 2. Total Plant Indirect Cost (TAC).
10. Engineering3,958,000.00
11. Construction5,541,000.00
Table 3. Contractor’s Fee & Contingency (CFC).
Table 3. Contractor’s Fee & Contingency (CFC).
12. Contractor’s Fee1,267,000.00
13. Contingency2,533,000.00
CFC = 12 + 133,800,000.00
Table 4. Equipment’s Purchase (Cost).
Table 4. Equipment’s Purchase (Cost).
OperatorLabor (h/yr)Labor (h/h)Labor (h/kg MP)
50 L:R-3.11,314.291.43N/A
Section Total123,728.8615.62NIA
Table 5. Materials Cost.
Table 5. Materials Cost.
Bulk MaterialUnit Cost ($)Annual Amount (kg)Annual Cost ($)%
Potassium alum0.18616,713.92111,008.510.02
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MDPI and ACS Style

Contreras-Ropero, J.E.; Ruiz-Roa, S.L.; García-Martínez, J.B.; Urbina-Suarez, N.A.; López-Barrera, G.L.; Barajas-Solano, A.F.; Zuorro, A. A Simulation Analysis of an Influenza Vaccine Production Plant in Areas of High Humanitarian Flow. A Preliminary Study for the Region of Norte de Santander (Colombia). Appl. Sci. 2022, 12, 183.

AMA Style

Contreras-Ropero JE, Ruiz-Roa SL, García-Martínez JB, Urbina-Suarez NA, López-Barrera GL, Barajas-Solano AF, Zuorro A. A Simulation Analysis of an Influenza Vaccine Production Plant in Areas of High Humanitarian Flow. A Preliminary Study for the Region of Norte de Santander (Colombia). Applied Sciences. 2022; 12(1):183.

Chicago/Turabian Style

Contreras-Ropero, Jefferson E., Silvia L. Ruiz-Roa, Janet B. García-Martínez, Néstor A. Urbina-Suarez, Germán L. López-Barrera, Andrés F. Barajas-Solano, and Antonio Zuorro. 2022. "A Simulation Analysis of an Influenza Vaccine Production Plant in Areas of High Humanitarian Flow. A Preliminary Study for the Region of Norte de Santander (Colombia)" Applied Sciences 12, no. 1: 183.

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