Fed-batch Operation Research Articles

Enhanced hyperin production from Euryale ferox seed shell using fed-batch operation by cellulase and xylanase hydrolysis

Enhanced hyperin production from Euryale ferox seed shell using fed-batch operation by cellulase and xylanase hydrolysis

Clavulanic Acid Overproduction: A Review of Environmental Conditions, Metabolic Fluxes, and Strain Engineering in Streptomyces clavuligerus

Clavulanic acid is a potent β-lactamase inhibitor produced by Streptomyces clavuligerus, widely used in combination with β-lactam antibiotics to combat antimicrobial resistance. This systematic review analyzes the most successful methodologies for clavulanic acid overproduction, focusing on the highest yields reported in bench-scale and bioreactor-scale fermentations. Studies have demonstrated that glycerol is the preferred carbon source for clavulanic acid production over other sources like starch and dextrins. The optimization of feeding strategies, especially in fed-batch operations, has improved glycerol utilization and extended the clavulanic acid production phase. Organic nitrogen sources, particularly soybean protein isolates and amino acid supplements such as L-arginine, L-threonine, and L-glutamate, have been proven effective at increasing CA yields both in batch and fed-batch cultures, especially when balanced with appropriate carbon sources. Strain engineering approaches, including mutagenesis and targeted genetic modifications, have allowed for the obtainment of overproducer S. clavuligerus strains. Specifically, engineering efforts that overexpress key regulatory genes such as ccaR and claR, or that disrupt competing pathways, redirect the metabolic flux towards CA biosynthesis, leading to high clavulanic acid titers. The fed-batch operation at the bioreactor scale emerges as the most feasible alternative for prolonged clavulanic acid production with both wild-type and mutant strains, allowing for the attainment of high titers during cultivations.

A coupled metabolic flux/compartmental hydrodynamic model for large-scale aerated bioreactors

Spatial variation of microorganism populations in stirred-tank bioreactors, caused by the interactions of complex multiphase flows and microorganism metabolism, results in undesirable performance characteristics and significant challenges in scale-up activities. In this work, a novel modelling approach is developed to investigate these coupled processes in bioreactors, which involves the integration of a computational fluid dynamics-informed compartmental hydrodynamic and a dynamic flux balance (DFB) model. This coupling poses significant computational challenges especially when dealing with transient scenarios. To tackle these challenges we developed a fast point-location algorithm to solve the DFB model at different bioreactor locations. To validate the presented modelling approach, a binary search tree-based metabolic model for E. coli was developed and integrated with a flow-informed compartmental model of a large-scale four-impeller aerated bioreactor in fed-batch operation. The model results exhibit favorable agreement with the concentration profiles reported in literature for both lab-scale and industrial scale bioreactors. Furthermore, the ability of the approach to deal with transient scenarios permitted to study the effect of oxygen closed loop control responses and the occurrence of oscillatory behaviour which were crucial to explain part of the data.

Metabolomic characterization of monoclonal antibody-producing Chinese hamster lung (CHL)-YN cells in glucose-controlled serum-free fed-batch operation.

The fast-growing Chinese hamster lung (CHL)-YN cell line was recently developed for monoclonal antibody production. In this study, we applied a serum-free fed-batch cultivation process to immunoglobulin (Ig)G1-producing CHL-YN cells, which were then used to design a dynamic glucose supply system to stabilize the extracellular glucose concentration based on glucose consumption. Glucose consumption of the cultures rapidly oscillated following three phases of glutamine metabolism: consumption, production, and re-consumption. Use of the dynamic glucose supply prolonged the viability of the CHL-YN-IgG1 cell cultures and increased IgG1 production. Liquid chromatography with tandem mass spectrometry-based target metabolomics analysis of the extracellular metabolites during the first glutamine shift was conducted to search for depleted compounds. The results suggest that the levels of four amino acids, namely arginine, aspartate, methionine, and serine, were sharply decreased in CHL-YN cells during glutamine production. Supporting evidence from metabolic and gene expression analyses also suggest that CHL-YN cells acquired ornithine- and cystathionine-production abilities that differed from those in Chinese hamster ovary-K1 cells, potentially leading to proline and cysteine biosynthesis.

An event triggered control scheme for enhanced production of Escherichia coli and biomass concentration during fed-batch cultivation

Control of a bioprocess is a challenging task mainly due to the nonlinearity of the process, the complex nature of microorganisms, and variations in critical parameters such as temperature, pH, and agitator speed. Generally, the optimum values chosen for critical parameters during Escherichia coli (E.coli) K-12fed-batch fermentation are37 ᵒC for temperature, 7 for pH, and 35 % for Dissolved Oxygen (DO). The objective of this research is to enhance biomass concentration while minimizing energy consumption. To achieve this, an Event-Triggered Control (ETC) scheme based on feedback-feed forward control is proposed. The ETC system dynamically adjusts the substrate feed rate in response to variations in critical parameters. We compare the performance of classical Proportional Integral (PI) controllers and advanced Model Predictive Control (MPC) controllers in terms of bioprocess yield. Initially, the data are collected from a laboratory-scaled 3L bioreactor setup under fed-batch operating conditions, and data-driven models are developed using system identification techniques. Then, classical Proportional Integral (PI) and advanced Model Predictive Control (MPC) based feedback controllers are developed for controlling the yield of bioprocess by manipulating substrate flow rate, and their performances are compared. PI and MPC-based Event Triggered Feed Forward Controllers are designed to increase the yield and to suppress the effect of known disturbances due to critical parameters. Whenever there is a variation in the value of a critical parameter, it is considered an event, and ETC initiates a control action by manipulating the substrate feed rate. PI and MPC-based ETC controllers are developed in simulation, and their closed-loop performances are compared. It is observed that the Integral Square Error (ISE) is notably minimized to 4.668 for MPC with disturbance and 4.742 for MPC with Feed Forward Control. Similarly, the Integral Absolute Error (IAE) reduces to 2.453 for MPC with disturbance and 0.8124 for MPC with Feed Forward Control. The simulation results reveal that the MPC-based ETC control scheme enhances the biomass yield by 7 %, and this result is verified experimentally. This system dynamically adjusts the substrate feed rate in response to variations in critical parameters, which is a novel approach in the field of bioprocess control. Also, the proposed control schemes help reduce the frequency of communication between controller and actuator, which reduces power consumption.

Optimizing microbioreactor cultivation strategies for Trichoderma reesei: from batch to fed-batch operations

BackgroundFilamentous fungi have long been recognized for their exceptional enzyme production capabilities. Among these, Trichoderma reesei has emerged as a key producer of various industrially relevant enzymes and is particularly known for the production of cellulases. Despite the availability of advanced gene editing techniques for T. reesei, the cultivation and characterization of resulting strain libraries remain challenging, necessitating well-defined and controlled conditions with higher throughput. Small-scale cultivation devices are popular for screening bacterial strain libraries. However, their current use for filamentous fungi is limited due to their complex morphology.ResultsThis study addresses this research gap through the development of a batch cultivation protocol using a microbioreactor for cellulase-producing T. reesei strains (wild type, RutC30 and RutC30 TR3158) with offline cellulase activity analysis. Additionally, the feasibility of a microscale fed-batch cultivation workflow is explored, crucial for mimicking industrial cellulase production conditions. A batch cultivation protocol was developed and validated using the BioLector microbioreactor, a Round Well Plate, adapted medium and a shaking frequency of 1000 rpm. A strong correlation between scattered light intensity and cell dry weight underscores the reliability of this method in reflecting fungal biomass formation, even in the context of complex fungal morphology. Building on the batch results, a fed-batch strategy was established for T. reesei RutC30. Starting with a glucose concentration of 2.5 g l-1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^{-1}$$\\end{document} in the batch phase, we introduced a dual-purpose lactose feed to induce cellulase production and prevent carbon catabolite repression. Investigating lactose feeding rates from 0.3 to 0.75 g (l h)-1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^{-1}$$\\end{document}, the lowest rate of 0.3 g (l h)-1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^{-1}$$\\end{document} revealed a threefold increase in cellobiohydrolase and a fivefold increase in β\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\upbeta$$\\end{document}-glucosidase activity compared to batch processes using the same type and amount of carbon sources.ConclusionWe successfully established a robust microbioreactor batch cultivation protocol for T. reesei wild type, RutC30 and RutC30 TR3158, overcoming challenges associated with complex fungal morphologies. The study highlights the effectiveness of microbioreactor workflows in optimizing cellulase production with T. reesei, providing a valuable tool for simultaneous assessment of critical bioprocess parameters and facilitating efficient strain screening. The findings underscore the potential of microscale fed-batch strategies for enhancing enzyme production capabilities, revealing insights for future industrial applications in biotechnology.

Industrial Production and Therapeutic Application of Botulinum Neurotoxin: The Role of C. botulinum Type A.

Botulinum neurotoxin has remarkably transitioned from a food safety hazard and biological warfare to an effective therapeutic drug. Currently, botulinum neurotoxins have seven serotypes (BoNT/A-G) in the form of protein complexes produced by Clostridium, a gram-positive and sporeforming bacteria. The conversion of toxins into useful drug substances of choice using the biotechnological process is tremendously increasing. Recent studies have shown that Botulinum neurotoxin-A (BoNT/A) has different biological activities and potencies in experimental and clinical conditions. They also indicate that the manufacturing process influences the potency and efficacy of BoNT/A drugs. Thus, this review focuses on the following criteria: detailed Fed-batch operation that includes the upstream and downstream processing of BoNT/A, the underlying mechanism behind the neurotoxic effect, and commercially available FDA-approved BoNT/A products and their therapeutic uses. Still, some research gaps exist in the mechanism for the treatment of psychiatric disorders.

Comparison of batch, fed-batch and continuous operation modes for scalable polyhydroxyalkanoate (PHA) production and carbon sequestration from phenol

Polyhydroxyalkanoates (PHA) are biodegradable intracellular polymers, and a renewable alternative to conventional plastics. To reduce PHA's cost, this study combined an unconventional carbon source, i.e. a toxic aromatics phenol, with an acclimated consortium, to develop a scalable PHA production process. The resultant process performance was systematically compared across three operational modes: batch, fed-batch, and continuous. Phenol toxicity caused inhibition in the batch mode, reducing the PHA synthesis rate but resulting in a high PHA content in cells (PHA% > 50 %). Fed-batch feeding alleviated such inhibition, facilitating a high PHA titer and yield from the substrate. Interestingly, a higher feeding rate in the fed-batch reactor improved its performance, probably by providing a suitable food-to-microbe ratio for the biomass. Using a continuous mode also reduced phenol toxicity, but resulted in more synthesis of non-PHA cellular materials (NPCM). The difference might have been caused by different metabolic states and the presence of intermediates in the reactors. Comparing all 14 conditions under the three modes, feeding phenol more gradually tended to channel substrate away from PHA to NPCM synthesis. The volumetric productivity generally ranged from 3 to 12 mg L−1 min−1, while the biomass productivity was between 2 and 11 mg g initial CDW−1 min−1. A 3-stage, production-harvest and starvation-production process was then designed to simulate real industrialized manufacturing, where the operational modes had a long-term effect on biomass' productivity. Fed-batch mode performed the best, as it fixed 1/3 of phenol's organic carbon in PHA product, suggesting high potential for future application.

Algebraic surrogate-based flexibility analysis of process units with complicating process constraints

Flexibility analyses are widespread in chemical engineering to quantify allowed deviations from nominal conditions. Standard approaches to perform flexibility analysis can be hard to apply if process constraints are difficult to handle, as it happens in bioprocesses with dynamic constraints. Here, focusing on the computation of the traditional flexibility index in problems with complicating constraints, we apply symbolic regression to build algebraic expressions of the said complicating constraints, simplifying the flexibility analysis of complex process models by enabling the application of state-of-the-art deterministic solvers. Our approach is applied to ethanol production in fed-batch operation mode and a chromatographic process. The performance is assessed in terms of model building time, predictive accuracy of the model, and the time required to solve the flexibility formulations. Overall, our approach, which focuses on computing the original flexibility index proposed in the literature, provides an alternative way to analyse the flexibility of processes entailing complicating constraints.

Flux dynamics of C-5 amino acid precursors in fed-batch cultures of Streptomyces clavuligerus during clavulanic acid biosynthesis

Clavulanic acid (CA) is a well-known β-lactamase inhibitor that is mainly obtained from submerged cultures of Streptomyces clavuligerus. Dynamic genome-scale in silico studies were performed to gain insights into the intracellular metabolic fluxes of C-5 precursors during the cultivation of wild-type S. clavuligerus in batch and fed-batch operation. A preliminary literature screening was conducted for media selection and determination of culture conditions for further cultivation in a 5-L bioreactor. Simulations provided insights into the metabolism of C-5 precursors in CA biosynthesis. In addition, carbon utilization for CA biosynthesis was assessed in terms of the ratio of total carbon used in CA biosynthesis to the total carbon influx in batch and feed media. Based on simulation results, we proposed a modification of the glycerol-sucrose-proline-glutamate medium for fed-batch cultivation to improve the carbon utilization for CA biosynthesis. The proposed fed-batch scenario achieved higher specific CA concentration at lower biomass production, indicating better carbon utilization for its synthesis. The dynamic in silico fluxes suggests that metabolic fluxes in this scenario would be stable, favoring a longer stage of continued antibiotic secretion.

Application of an oxidative-biological treatment strategy for production of lactic acid and biomass from vinasse of sugarcane bioethanol industry

In this study, the cultivation of lactic acid bacteria was done using vinasse (with a chemical oxygen demand of 378 ± 5 g O2/L) to harness its organic content. The potential for biomass and lactic acid production was evaluated by using strains Lactococcus lactis subsp. Cremoris and Lactococcus lactis subsp. Lactis. Before medium preparation, vinasse was pretreated with air and ozone to reduce inhibitory load. The effects of pretreated vinasse addition on lactic acid bacteria growth were in the range of 0–33% v/v. The optimal vinasse concentration for obtaining high biomass and lactic acid concentrations was 17% v/v, leading to maximum concentrations of biomass and lactic acid of 2.2 ± 0.14 and 16.0 ± 0.9 g/L, respectively. Fed-batch operation was also studied as a strategy for extending the production phase of lactic acid bacteria using vinasse (17% v/v) as feeding. These results highlight the underexplored potential of vinasse as an economical source of raw material for obtaining value-added products through biotechnological processes.

Modeling large-scale bioreactors with diffusion equations. Part II: Characterizing substrate, oxygen, temperature, carbon dioxide, and pH profiles.

Large-scale fermentation processes involve complex dynamic interactions between mixing, reaction, mass transfer, and the suspended biomass. Empirical correlations or case-specific computational simulations are usually used to predict and estimate the performance of large-scale bioreactors based on data acquired at bench scale. In this two-part-study, one-dimensional axial diffusion equations were studied as a general and predictive model of large-scale bioreactors. This second part focused on typical fed-batch operations where substrate gradients are known to occur, and characterized the profiles of substrate, pH, oxygen, carbon dioxide, and temperature. The physically grounded steady-state axial diffusion equations with first- and zeroth-order kinetics yielded analytical solutions to the relevant variables. The results were compared with large-scale Escherichia coli and Saccharomyces cerevisiae experiments and simulations from the literature, and good agreement was found in substrate profiles. The analytical profiles obtained for dissolved oxygen, temperature, pH, and were also consistent with the available data. Distribution functions for the substrate were defined, and efficiency factors for biomass growth and oxygen uptake rate were derived. In conclusion, this study demonstrated that axial diffusion equations can be used to model the effects of mixing and reaction on the relevant variables of typical large-scale fed-batch fermentations.

Hydrodynamic cavitation-assisted acid pretreatment and fed-batch simultaneous saccharification and co-fermentation for ethanol production from sugarcane bagasse using immobilized cells of Scheffersomyces parashehatae

A new alternative for hydrodynamic cavitation-assisted pretreatment of sugarcane bagasse was proposed, along with a simultaneous saccharification and co-fermentation (SSCF) process performed in interconnected columns. Influential variables in the pretreatment were evaluated using a statistical design, indicating that an ozone flow rate of 10 mg min−1 and a pH of 5.10 resulted in 86 % and 72 % glucan and xylan hydrolysis yields, respectively, in the subsequent enzymatic hydrolysis process. Under these optimized conditions, iron sulfate (15 mg L−1) was added to assess Fenton pretreatment, resulting in glucan and xylan hydrolysis yields of 92 % and 71 %, respectively, in a material pretreated for 10 min. In SSCF, ethanol volumetric productivities of 0.33 g L−1 h−1 and of 0.54 g L−1 h−1 were obtained in batch and fed-batch operation modes, achieving 26 g L−1 of ethanol in 48 h in the latter mode.

Intensified Influenza Virus Production in Suspension HEK293SF Cell Cultures Operated in Fed-Batch or Perfusion with Continuous Harvest.

Major efforts in the intensification of cell culture-based viral vaccine manufacturing focus on the development of high-cell-density (HCD) processes, often operated in perfusion. While perfusion operations allow for higher viable cell densities and volumetric productivities, the high perfusion rates (PR) normally adopted-typically between 2 and 4 vessel volumes per day (VVD)-dramatically increase media consumption, resulting in a higher burden on the cell retention device and raising challenges for the handling and disposal of high volumes of media. In this study, we explore high inoculum fed-batch (HIFB) and low-PR perfusion operations to intensify a cell culture-based process for influenza virus production while minimizing media consumption. To reduce product retention time in the bioreactor, produced viral particles were continuously harvested using a tangential flow depth filtration (TFDF) system as a cell retention device and harvest unit. The feeding strategies developed-a hybrid fed-batch with continuous harvest and a low-PR perfusion-allowed for infections in the range of 8-10 × 106 cells/mL while maintaining cell-specific productivity comparable to the batch control, resulting in a global increase in the process productivity. Overall, our work demonstrates that feeding strategies that minimize media consumption are suitable for large-scale influenza vaccine production.

Triple Space-Time Yield in Discontinuous Antibody Biomanufacturing by Combination of Synergetic Process Intensification Strategies.

Monoclonal antibodies are the workhorse of the pharmaceutical industry due to their potential to treat a variety of different diseases while providing high specificity and efficiency. As a consequence, a variety of production processes have been established within the biomanufacturing industry. However, the rapidly increasing demand for therapeutic molecules amid the recent COVID-19 pandemic demonstrated that there still is a clear need to establish novel, highly productive, and flexible production processes. Within this work, we designed a novel discontinuous process by combining two intensification strategies, thus increasing inoculation density and media exchange via a fluidized bed centrifuge, to fulfill the need for a flexible and highly productive production process for therapeutic molecules. To establish this new process, firstly, a small-scale experiment was conducted to verify synergies between both intensification strategies, followed by a process transfer towards the proof-of-concept scale. The combination of these two-process intensification measures revealed overall synergies resulting in decreased process duration (-37%) and strongly enhanced product formation (+116%) in comparison to the not-intensified standard operation. This led to an impressive threefold increase in space-time yield, while only negligible differences in product quality could be observed. Overall, this novel process not only increases the ways to react to emergency situations thanks to its flexibility and possible short development times, but also represents a possible alternative to the current established processes due to high increases in productivity, in comparison to standard fed-batch operations.

Transforming liquid flow fuel cells to controllable reactors for highly-efficient oxidation of 5-hydroxymethylfurfural to 2, 5-furandicarboxylic acid at low temperature

Highly-efficient oxidation of 5-hydroxymethylfurfural (HMF) to 2,5-furandicarboxylic acid (FDCA) at low temperature with air as the oxidant is still challenging. Herein, inspired by the respiratory electron transport chain (ETC) of living cells mediated by electron carriers, we constructed artificial ETCs and transformed liquid flow fuel cells (LFFCs) to flexible reactors for efficient oxidation of HMF to produce FDCA under mild conditions. This LFFC reactor employed an electrodeposition modified nickel foam as an anode to promote HMF oxidation and (VO2)2SO4 as a cathode electron carrier to facilitate the electron transfer to air. The reaction rate could be easily controlled by selecting the anode catalyst, adjusting the external loading and changing the cathodic electron carrier or oxidants. A maximal power density of 44.9 mW cm−2 at room temperature was achieved, while for FDCA production, short-circuit condition was preferred to achieve quick transfer of electrons. For a single batch operation with 0.1 M initial HMF, FDCA yield reached 97.1%. By fed-batch operation, FDCA concentration reached 144.5 g L–1 with a total yield of 96%. Ni2+/Ni3+ redox couple was the active species mediating the electron transfer, while both experimental and DFT calculation results indicated that HMFCA pathway was the preferred reaction mechanism.

A two-phase approach optimizing productivity for a mAb-producing CHO cell culture process using dynamic response surface methodology models

Fed-batch cell culture processes are common in the biomanufacturing industry due to their ease of development and simplicity of execution in the cGMP environment. One challenge of fed-batch operation is that the physiochemical conditions within the bioreactor do not remain constant throughout a batch but change over time as the viable cell density changes. It is well accepted that fed-batch cultures are multi-phasic, divided into “growth, stationary, and death phases”. Yet, using empirical modeling methods such as response surface models (RSMs) for optimization is still common. While RSMs can identify local performance maxima, they are limited by the time-invariant factors (input parameters) they use. These factors do not change throughout the run. Dynamic RSM (DRSM) models predict the time-dependent impact of the process inputs allowing for the identification of optimized process operations that change with time. Starting with the data sets generated via a traditional Design of Experiments (DoE) design, the DRSM model successfully optimized the peak cell count during the growth phase of culture and then identified a second set of process parameters that optimized productivity during the stationary phase. The resulting process achieved a harvest titer improvement of 28% relative to the base process condition.

Optimizing the switching operation in monoclonal antibody production: Economic MPC and reinforcement learning

Monoclonal antibodies (mAbs), crucial in medicine and biopharmaceuticals, require optimized large-scale production to meet high clinical dosage demands. Most of the processes for industrial mAb production rely on fed-batch operations, resulting in significant downtime. Transitioning to fully continuous and integrated processes holds the potential to boost product yield, enhance quality, and reduce storage costs for intermediate products. The integrated continuous mAb production process can be divided into the upstream and downstream processes. One crucial aspect that ensures the continuity of the integrated process is the switching of the capture columns, which are typically chromatography columns operated in a fed-batch manner downstream. Due to the discrete nature of the switching operation, advanced process control algorithms such as economic MPC (EMPC) are computationally difficult to implement. This is because an integer nonlinear program (INLP) needs to be solved online at each sampling time.This paper introduces two computationally-efficient approaches for EMPC implementation, namely, a sigmoid function approximation approach and a rectified linear unit (ReLU) approximation approach. It also explores the application of deep reinforcement learning (DRL). These three methods are compared to the traditional switching approach which is based on a 1 % product breakthrough rule and which involves no optimization.

Identification of optimal flow rate for culture media, cell density, and oxygen toward maximization of virus production in a fed-batch baculovirus-insect cell system.

In recent times, it has been realized that novel vaccines are required to combat emerging disease outbreaks, and faster optimization is required to respond to global vaccine demands. Although, fed-batch operations offer better productivity, experiment-based optimization of a new fed-batch process remains expensive and time-consuming. In this context, we propose a novel computational framework that can be used for process optimization and control of a fed-batch baculovirus-insect cell system. Since the baculovirus expression vector system (BEVS) is known to be widely used platforms for recombinant protein/vaccine production, we chose this system to demonstrate the identification of optimal profile. Toward this, first, we constructed a mathematical model that captures the time course of cell and virus growth in a baculovirus-insect cell system. Second, the proposed model was used for numerical analysis to determine the optimal operating profiles of control variables such as culture media, cell density, and oxygen based on a multiobjective optimal control formulation. Third, a detailed comparison between batch and fed-batch culture was perfromed along with a comparison between various alternatives of fed-batch operation. Finally, we demonstrate that a model-based quantification of controlled feed addition in fed-batch culture is capable of providing better productivity as compared to a batch culture. The proposed framework can be utilized for the estimation of optimal operating regions of different control variables to achieve maximum infected cell density and virus yield while minimizing the substrate/media, uninfected cell, and oxygen consumption.

Single and multi-objective dynamic optimization study of an industrial scale fed batch reactor

Abstract The present work focuses on obtaining optimal operational policies of an industrial scale penicillin fed-batch fermentation process using dynamic optimization (DO). The three process objectives considered in this work include, maximization of total penicillin formed (J 1), minimization of total biomass formed (J 2), and minimization of fed-batch operation time (J 3). The control variables for the optimization study include, the feed flowrates of sugar, soyabean oil, and phenylacetic. We perform a single-objective optimization study with J 1 as the objective function and showcased the importance of DO. Consequently, we solve three multi-objective optimization (MOO) problems corresponding to all the pairwise combinations of the aforementioned three objectives. Outcomes of MOO problems are presented in terms of several non-dominated Pareto-optimal solutions. Furthermore, descriptive analysis of three representative Pareto points for all the MOO problems is presented, which highlights the importance of MOO study of the penicillin bio-reactor.