Fed‐batch and perfusion culture processes: Economic,environmental, and operational feasibility under uncertainty

This article evaluates the current and future potential of batch and continuous cell culture technologies via a case study based on the commercial manufacture of monoclonal antibodies. The case study compares fed‐batch culture to two perfusion technologies: spin‐filter perfusion and an emerging perfusion technology utilizing alternating tangential flow (ATF) perfusion. The operational, economic, and environmental feasibility of whole bioprocesses based on these systems was evaluated using a prototype dynamic decision‐support tool built at UCL encompassing process economics, discrete‐event simulation and uncertainty analysis, and combined with a multi‐attribute decision‐making technique so as to enable a holistic assessment. The strategies were compared across a range of scales and titres so as to visualize how their ranking changes in different industry scenarios. The deterministic analysis indicated that the ATF perfusion strategy has the potential to offer cost of goods savings of 20% when compared to conventional fed‐batch manufacturing processes when a fivefold increase in maximum viable cell densities was assumed. Savings were also seen when the ATF cell density dropped to a threefold increase over the fed‐batch strategy for most combinations of titres and production scales. In contrast, the fed‐batch strategy performed better in terms of environmental sustainability with a lower water and consumable usage profile. The impact of uncertainty and failure rates on the feasibility of the strategies was explored using Monte Carlo simulation. The risk analysis results demonstrated the enhanced robustness of the fed‐batch process but also highlighted that the ATF process was still the most cost‐effective option even under uncertainty. The multi‐attribute decision‐making analysis provided insight into the limited use of spin‐filter perfusion strategies in industry. The resulting sensitivity spider plots enabled identification of the critical ratio of weightings of economic and operational benefits that affect the choice between ATF perfusion and fed‐batch strategies. Biotechnol. Bioeng. 2013; 110: 206–219. © 2012 Wiley Periodicals, Inc.     

Optimal invasive species management under multiple uncertainties

The management programs for invasive species have been proposed and implemented in many regions of the world. However, practitioners and scientists have not reached a consensus on how to control them yet. One reason is the presence of various uncertainties associated with the management. To give some guidance on this issue, we characterize the optimal strategy by developing a dynamic model of invasive species management under uncertainties. In particular, focusing on (i) growth uncertainty and (ii) measurement uncertainty, we identify how these uncertainties affect optimal strategies and value functions. Our results suggest that a rise in growth uncertainty causes the optimal strategy to involve more restrained removals and the corresponding value function to shift up. Furthermore, we also find that a rise in measurement uncertainty affects optimal policies in a highly complex manner, but their corresponding value functions generally shift down as measurement uncertainty rises. Overall, a rise in growth uncertainty can be beneficial, while a rise in measurement uncertainty brings about an adverse effect, which implies the potential gain of precisely identifying the current stock size of invasive species.     

Establishing a Fed‐Batch Process for Protease Expression with Bacillus licheniformis in Polymer‐Based Controlled‐Release Microtiter Plates

Introducing fed‐batch mode in early stages of development projects is crucial for establishing comparable conditions to industrial fed‐batch fermentation processes. Therefore, cost efficient and easy to use small‐scale fed‐batch systems that can be integrated into existing laboratory equipment and workflows are required. Recently, a novel polymer‐based controlled‐release fed‐batch microtiter plate is described. In this work, the polymer‐based controlled‐release fed‐batch microtiter plate is used to investigate fed‐batch cultivations of a protease producing Bacillus licheniformis culture. Therefore, the oxygen transfer rate (OTR) is online‐monitored within each well of the polymer‐based controlled‐release fed‐batch microtiter plate using a µRAMOS device. Cultivations in five individual polymer‐based controlled‐release fed‐batch microtiter plates of two production lots show good reproducibility with a mean coefficient of variation of 9.2%. Decreasing initial biomass concentrations prolongs batch phase while simultaneously postponing the fed‐batch phase. The initial liquid filling volume affects the volumetric release rate, which is directly translated in different OTR levels of the fed‐batch phase. An increasing initial osmotic pressure within the mineral medium decreases both glucose release and protease yield. With the volumetric glucose release rate as scale‐up criterion, microtiter plate‐ and shake flask‐based fed‐batch cultivations are highly comparable. On basis of the small‐scale fed‐batch cultivations, a mechanistic model is established and validated. Model‐based simulations coincide well with the experimentally acquired data.     

Spreadsheet Method for Evaluation of Biochemical Reaction Rate Coefficients and Their Uncertainties by Weighted Nonlinear Least-Squares Analysis of the Integrated Monod Equation

A convenient method for evaluation of biochemical reaction rate coefficients and their uncertainties is described. The motivation for developing this method was the complexity of existing statistical methods for analysis of biochemical rate equations, as well as the shortcomings of linear approaches, such as Lineweaver-Burk plots. The nonlinear least-squares method provides accurate estimates of the rate coefficients and their uncertainties from experimental data. Linearized methods that involve inversion of data are unreliable since several important assumptions of linear regression are violated. Furthermore, when linearized methods are used, there is no basis for calculation of the uncertainties in the rate coefficients. Uncertainty estimates are crucial to studies involving comparisons of rates for different organisms or environmental conditions. The spreadsheet method uses weighted least-squares analysis to determine the best-fit values of the rate coefficients for the integrated Monod equation. Although the integrated Monod equation is an implicit expression of substrate concentration, weighted least-squares analysis can be employed to calculate approximate differences in substrate concentration between model predictions and data. An iterative search routine in a spreadsheet program is utilized to search for the best-fit values of the coefficients by minimizing the sum of squared weighted errors. The uncertainties in the best-fit values of the rate coefficients are calculated by an approximate method that can also be implemented in a spreadsheet. The uncertainty method can be used to calculate single-parameter (coefficient) confidence intervals, degrees of correlation between parameters, and joint confidence regions for two or more parameters. Example sets of calculations are presented for acetate utilization by a methanogenic mixed culture and trichloroethylene cometabolism by a methane-oxidizing mixed culture. An additional advantage of application of this method to the integrated Monod equation compared with application of linearized methods is the economy of obtaining rate coefficients from a single batch experiment or a few batch experiments rather than having to obtain large numbers of initial rate measurements. However, when initial rate measurements are used, this method can still be used with greater reliability than linearized approaches.     

Application of uncertainty and variability in LCA

As yet, the application of an uncertainty and variability analysis is not common practice in LCAs. A proper analysis will be facilitated when it is clear which types of uncertainties and variabilities exist in LCAs and which tools are available to deal with them. Therefore, a framework is developed to classify types of uncertainty and variability in LCAs. Uncertainty is divided in (1) parameter uncertainty, (2) model uncertainty, and (3) uncertainty due to choices, while variability covers (4) spatial variability, (5) temporal variability, and (6) variability between objects and sources. A tool to deal with parameter uncertainty and variability between objects and sources in both the inventory and the impact assessment is probabilistic simulation. Uncertainty due to choices can be dealt with in a scenario analysis or reduced by standardisation and peer review. The feasibility of dealing with temporal and spatial variability is limited, implying model uncertainty in LCAs. Other model uncertainties can be reduced partly by more sophisticated modelling, such as the use of non-linear inventory models in the inventory and multi media models in the characterisation phase.     

Partitioning and mapping uncertainties in ensembles of forecasts of species turnover under climate change

Forecasts of species range shifts under climate change are fraught with uncertainties and ensemble forecasting may provide a framework to deal with such uncertainties. Here, a novel approach to partition the variance among modeled attributes, such as richness or turnover, and map sources of uncertainty in ensembles of forecasts is presented. We model the distributions of 3837 New World birds and project them into 2080. We then quantify and map the relative contribution of different sources of uncertainty from alternative methods for niche modeling, general circulation models (AOGCM), and emission scenarios. The greatest source of uncertainty in forecasts of species range shifts arises from using alternative methods for niche modeling, followed by AOGCM, and their interaction. Our results concur with previous studies that discovered that projections from alternative models can be extremely varied, but we provide a new analytical framework to examine uncertainties in models by quantifying their importance and mapping their patterns.     

流加发酵提高产胡萝卜素红酵母产量的研究

本文对产胡萝卜素的红酵母进行了间歇、恒速及变速流加发酵实验,建立了简单的数学模型控制流加。实验结果表明,变速流加可显著地提高红酵母的产量,当流加控制因子K为88×10－5,变速流水发酵比间歇发酵红酵母产量提高了56．2％。     

A computational model of limb impedance control based on principles of internal model uncertainty

Efficient human motor control is characterized by an extensive use of joint impedance modulation, which is achieved by co-contracting antagonistic muscles in a way that is beneficial to the specific task. While there is much experimental evidence available that the nervous system employs such strategies, no generally-valid computational model of impedance control derived from first principles has been proposed so far. Here we develop a new impedance control model for antagonistic limb systems which is based on a minimization of uncertainties in the internal model predictions. In contrast to previously proposed models, our framework predicts a wide range of impedance control patterns, during stationary and adaptive tasks. This indicates that many well-known impedance control phenomena naturally emerge from the first principles of a stochastic optimization process that minimizes for internal model prediction uncertainties, along with energy and accuracy demands. The insights from this computational model could be used to interpret existing experimental impedance control data from the viewpoint of optimality or could even govern the design of future experiments based on principles of internal model uncertainty.     

Precultures Grown under Fed‐Batch Conditions Increase the Reliability and Reproducibility of High‐Throughput Screening Results

One essential task in bioprocess development is strain selection. A common screening procedure consists of three steps: first, the picking of colonies; second, the execution of a batch preculture and main culture, e.g., in microtiter plates (MTPs); and third, the evaluation of product formation. Especially during the picking step, unintended variations occur due to undefined amounts and varying viability of transferred cells. The aim of this study is to demonstrate that the application of polymer‐based controlled‐release fed‐batch MTPs during preculture eliminates these variations. The concept of equalizing growth through fed‐batch conditions during preculture is theoretically discussed and then tested in a model system, namely, a cellulase‐producing Escherichia coli clone bank containing 32 strains. Preculture is conducted once in the batch mode and once in the fed‐batch mode. By applying the fed‐batch mode, equalized growth is observed in the subsequent main culture. Furthermore, the standard deviation of cellulase activity is reduced compared to that observed in the conventional approach. Compared with the strains in the batch preculture process, the first‐ranked strain in the fed‐batch preculture process is the superior cellulase producer. These findings recommend the application of the fed‐batch MTPs during preculture in high‐throughput screening processes to achieve accurate and reliable results.     

Simultaneous saccharification and co‐fermentation of paper sludge to ethanol by Saccharomyces cerevisiae RWB222. Part II: Investigation of discrepancies between predicted and observed performance at high solids concentration

The simultaneous saccharification and co‐fermentation (SSCF) kinetic model described in the companion paper can predict batch and fed batch fermentations well at solids concentrations up to 62.4 g/L cellulose paper sludge but not in batch fermentation at 82.0 g/L cellulose paper sludge. Four hypotheses for the discrepancy between observation and model prediction at high solids concentration were examined: ethanol inhibition, enzyme deactivation, inhibition by non‐metabolizable compounds present in paper sludge, and mass transfer limitation. The results show that mass transfer limitation was responsible for the discrepancy between model and experimental data. The model can predict the value of high paper sludge SSCF in the fermentation period with no mass transfer limitation. The model predicted that maximum ethanol production of fed‐batch fermentation was achieved when it was run as close to batch mode as possible with the initial solids loading below the mass transfer limitation threshold. A method for measuring final enzyme activity at the end of fermentation was also developed in this study. Biotechnol. Bioeng. 2009; 104: 932–938. © 2009 Wiley Periodicals, Inc.     

Robust parameter estimation during logistic modeling of batch and fed‐batch culture kinetics

Methods for robust logistic modeling of batch and fed‐batch mammalian cell cultures are presented in this study. Linearized forms of the logistic growth, logistic decline, and generalized logistic equation were derived to obtain initial estimates of the parameters by linear least squares. These initial estimates facilitated subsequent determination of refined values by nonlinear optimization using three different algorithms. Data from BHK, CHO, and hybridoma cells in batch or fed‐batch cultures at volumes ranging from 100 mL–300 L were tested with the above approach and solution convergence was obtained for all three nonlinear optimization approaches for all data sets. This result, despite the sensitivity of logistic equations to parameter variation because of their exponential nature, demonstrated that robust estimation of logistic parameters was possible by this combination of linearization followed by nonlinear optimization. The approach is relatively simple and can be implemented in a spreadsheet to robustly model mammalian cell culture batch or fed‐batch data. © 2009 American Institute of Chemical Engineers Biotechnol. Prog., 2009     

A dynamic fed batch strategy for a Pichia pastoris mixed feed system to increase process understanding

Mixed substrate feeding strategies are frequently investigated to enhance the productivity of recombinant Pichia pastoris processes. For this purpose, numerous fed batch experiments or time-consuming continuous cultivations are required to optimize control parameters such as the substrate mixing ratio and the applied methanol concentration. In this study, we decoupled the feeding of methanol and glycerol in a mixed substrate fed batch environment to gain process understanding for a recombinant P. pastoris Muts strain producing the model enzyme horseradish peroxidase. Specific substrate uptake rates (qs) were controlled separately, and a stepwise increased qGly-control scheme was applied to investigate the effect of various substrate fluxes on the culture. The qs-controlled strategy allowed a parallel characterization of the metabolism and the recombinant protein expression in a fed batch environment. A critical-specific glycerol uptake rate was determined, where a decline of the specific productivity occurred, and a time-dependent acceleration of protein expression was characterized with the dynamic fed batch approach. Based on the observations on recombinant protein expression, propositions for an optimal feeding design to target maximal productivities were stated. Thus, the dynamic fed batch strategy was found to be a valuable tool for both process understanding and optimization of product formation for P. pastoris in a mixed substrate environment.     

Feedback Control of an Achiral Robotic Microswimmer

Magnetic microswimmers are useful for navigating and performing tasks at small scales.To demonstrate effective control over such microswimmers,we implemented feedback control of the three-bead achiral microswimmers in both simulation and experiment.The achiral microswimmers with the ability to swim in bulk fluid are controlled wirelessly using magnetic fields generated from electromagnetic coils.The achirality of the microswimmers introduces unknown handedness resulting in uncertainty in swimming direction.We use a combination of rotating and static magnetic fields generated from an approximate Helmholtz coil system to overcome such uncertainty.There are also movement uncertainties due to environmental factors such as unsteady flow conditions.A kinematic model based feedback controller was created based on data fitting of experimental data.However,the controller was unable to yield satisfactory performance due to uncertainties from environmental factors;i.e.,the time to reach target pose under adverse flow condition is too long.Following the implementation of an integral controller to control the microswimmers' swimming velocity,the microswimmers were able to reach the target in roughly half the time.Through simulation and experiments,we show that the feedback control law can move an achiral microswimmer from any initial conditions to a target pose.     

Microfluidic biolector—microfluidic bioprocess control in microtiter plates

In industrial‐scale biotechnological processes, the active control of the pH‐value combined with the controlled feeding of substrate solutions (fed‐batch) is the standard strategy to cultivate both prokaryotic and eukaryotic cells. On the contrary, for small‐scale cultivations, much simpler batch experiments with no process control are performed. This lack of process control often hinders researchers to scale‐up and scale‐down fermentation experiments, because the microbial metabolism and thereby the growth and production kinetics drastically changes depending on the cultivation strategy applied. While small‐scale batches are typically performed highly parallel and in high throughput, large‐scale cultivations demand sophisticated equipment for process control which is in most cases costly and difficult to handle. Currently, there is no technical system on the market that realizes simple process control in high throughput. The novel concept of a microfermentation system described in this work combines a fiber‐optic online‐monitoring device for microtiter plates (MTPs)—the BioLector technology—together with microfluidic control of cultivation processes in volumes below 1 mL. In the microfluidic chip, a micropump is integrated to realize distinct substrate flow rates during fed‐batch cultivation in microscale. Hence, a cultivation system with several distinct advantages could be established: (1) high information output on a microscale; (2) many experiments can be performed in parallel and be automated using MTPs; (3) this system is user‐friendly and can easily be transferred to a disposable single‐use system. This article elucidates this new concept and illustrates applications in fermentations of Escherichia coli under pH‐controlled and fed‐batch conditions in shaken MTPs. Biotechnol. Bioeng. 2010;107: 497–505. © 2010 Wiley Periodicals, Inc.     

Methods for displaying macromolecular structural uncertainty: Application to the globins

Most molecular graphics programs ignore any uncertainty in the atomic coordinates being displayed. Structures are displayed in terms of perfect points, spheres, and lines with no uncertainty. However, all experimental methods for defining structures, and many methods for predicting and comparing structures, associate uncertainties with each atomic coordinate. We have developed graphical representations that highlight these uncertainties. These representations are encapsulated in a new interactive display program, PROTEAND. PROTEAND represents structural uncertainty in three ways: (1) The traditional way: The program shows a collection of structures as superposed and overlapped stick-figure models. (2) Ellipsoids: At each atom position, the program shows an ellipsoid derived from a three-dimensional Gaussian model of uncertainty. This probabilistic model provides additional information about the relationship between atoms that can be displayed as a correlation matrix. (3) Rigid-body volumes: Using clouds of dots, the program can show the range of rigid-body motion of selected substructures, such as individual α helices. We illustrate the utility of these display modalities by the applying PROTEAND to the globin family of proteins, and show that certain types of structural variation are best illustrated with different methods of display.     

Model‐based optimization and pO2 control of fed‐batch Escherichia coli and Saccharomyces cerevisiae cultivation processes

A model‐based approach for optimization and cascade control of dissolved oxygen partial pressure (pO₂) and maximization of biomass in fed‐batch cultivations is presented. The procedure is based on the off‐line model‐based optimization of the optimal feeding rate profiles and the subsequent automatic pO₂ control using a proposed cascade control technique. During the model‐based optimization of the process, feeding rate profiles are optimized with respect to the imposed technological constraints (initial and maximal cultivation volume, cultivation time, feeding rate range, maximal oxygen transfer rate and pO₂ level). The cascade pO₂ control is implemented using activation of cascades for agitation, oxygen enrichment, and correction of the preoptimized feeding rate profiles. The proposed approach is investigated in two typical fed‐batch processes with Escherichia coli and Saccharomyces cerevisiae. The obtained results show that it was possible to achieve sufficiently high biomass levels with respect to the given technological constraints and to improve controllability of the investigated processes.     

Framework for modelling data uncertainty in life cycle inventories

Modelling data uncertainty is not common practice in life cycle inventories (LCI), although different techniques are available for estimating and expressing uncertainties, and for propagating the uncertainties to the final model results. To clarify and stimulate the use of data uncertainty assessments in common LCI practice, the SETAC working group ‘Data Availability and Quality’ presents a framework for data uncertainty assessment in LCI. Data uncertainty is divided in two categories: (1) lack of data, further specified as complete lack of data (data gaps) and a lack of representative data, and (2) data inaccuracy. Filling data gaps can be done by input-output modelling, using information for similar products or the main ingredients of a product, and applying the law of mass conservation. Lack of temporal, geographical and further technological correlation between the data used and needed may be accounted for by applying uncertainty factors to the non-representative data. Stochastic modelling, which can be performed by Monte Carlo simulation, is a promising technique to deal with data inaccuracy in LCIs.     

Current Practices in Reporting Uncertainty in Ecosystem Ecology

Ecosystem budgets of water and elements can be difficult to estimate and are often unreplicated, making it challenging to provide confidence in estimates of ecosystem pools and fluxes. We conducted a survey to learn about current practices in reporting uncertainties in precipitation, streamflow, soils, and vegetation. Uncertainty derives from natural variation, which is commonly characterized by replicate samples, and from imperfect knowledge, which includes measurement error and model error (model fit and model selection). We asked questions about whether researchers report uncertainties in these sources, whether they know how to do so, and how important they believe the sources to be. We also asked questions about identifying missing or unusable values, filling gaps in data, and dealing with analytical concentrations below detection limits. We obtained responses from 140 researchers representing 90 research sites around the world. Natural variation was the most important source of uncertainty in calculations of biomass and soil pools, according to respondents in these fields, and sampling error was the source they most often reported. In contrast, uncertainty in the chemical analysis of precipitation and stream water was the source most commonly reported by hydrologists, although they rated this one of the least important sources of uncertainty to calculations of hydrologic flux. Awareness of types of uncertainty can help identify sources of uncertainty that may have been overlooked, and quantifying them will help determine which sources are most important to report.