Progress toward forecasting product quality and quantity of mammalian cell culture processes by performance‐based modeling

The production of biopharmaceuticals requires highly sophisticated, complex cell based processes. Once a process has been developed, acceptable ranges for various control parameters are typically defined based on process characterization studies often comprising several dozens of small scale bioreactor cultivations. A lot of data is generated during these studies and usually only the information needed to define acceptable ranges is processed in more detail. Making use of the wealth of information contained in such data sets, we present here a methodology that uses performance data (such as metabolite profiles) to forecast the product quality and quantity of mammalian cell culture processes based on a toolbox of advanced statistical methods. With this performance based modeling (PBM) the final product concentration and 12 quality attributes (QAs) for two different biopharmaceutical products were predicted in daily intervals throughout the main stage process. The best forecast was achieved for product concentration in a very early phase of the process. Furthermore, some glycan isoforms were predicted with good accuracy several days before the bioreactor was harvested. Overall, PBM clearly demonstrated its capability of early process endpoint prediction by only using commonly available data, even though it was not possible to predict all QAs with the desired accuracy. Knowing the product quality prior to the harvest allows the manufacturer to take counter measures in case the forecasted quality or quantity deviates from what is expected. This would be a big step towards real‐time release, an important element of the FDA's PAT initiative. © 2015 American Institute of Chemical Engineers Biotechnol. Prog., 31:1119–1127, 2015     

Recursive on-line estimation of the specific growth rate from off-gas analysis for the adaptive control of fed-batch processes

A recursive estimation algorithm for the specific growth rate of aerobic fed-batch processes was developed. The estimate (t) is independent of the state estimates X(t) of the process. This improves the stability of the closed loop system. The performance of the nonlinear control system was tested on fermentations with streptomyces tendae with great success. The methodology of the nonlinear control system is very general. Thus, it can be applied to substrate control problems of any other aerobic fed-batch process.     

Side-by-side comparability of batch and continuous downstream for the production of monoclonal antibodies

Continuous processing is the future production method for monoclonal antibodies (mAbs). A fully continuous, fully automated downstream process based on disposable equipment was developed and implemented inside the MoBiDiK pilot plant. However, a study evaluating the comparability between batch and continuous processing based on product quality attributes was not conducted before. The work presented fills this gap comparing both process modes experimentally by purifying the same harvest material (side-by-side comparability). Samples were drawn at different time points and positions in the process for batch and continuous mode. Product quality attributes, product-related impurities, as well as process-related impurities were determined. The resulting polished material was processed to drug substance and further evaluated regarding storage stability and degradation behavior. The in-process control data from the continuous process showed the high degree of accuracy in providing relevant process parameters such as pH, conductivity, and protein concentration during the entire process duration. Minor differences between batch and continuous samples are expected as different processing conditions are unavoidable due to the different nature of batch and continuous processing. All tests revealed no significant differences in the intermediates and comparability in the drug substance between the samples of both process modes. The stability study of the final product also showed no differences in the stability profile during storage and forced degradation. Finally, online data analysis is presented as a powerful tool for online-monitoring of chromatography columns during continuous processing.     

Preliminary Retrospective Analysis of Daily Tomotherapy Output Constancy Checks Using Statistical Process Control

The purpose of this study was to retrospectively evaluate the results from a Helical TomoTherapy Hi-Art treatment system relating to quality controls based on daily static and dynamic output checks using statistical process control methods. Individual value X-charts, exponentially weighted moving average charts, and process capability and acceptability indices were used to monitor the treatment system performance. Daily output values measured from January 2014 to January 2015 were considered. The results obtained showed that, although the process was in control, there was an out-of-control situation in the principal maintenance intervention for the treatment system. In particular, process capability indices showed a decreasing percentage of points in control which was, however, acceptable according to AAPM TG148 guidelines. Our findings underline the importance of restricting the acceptable range of daily output checks and suggest a future line of investigation for a detailed process control of daily output checks for the Helical TomoTherapy Hi-Art treatment system.     

On-line HPLC-measurement and control of substrate in a continuously operated biological tank reactor

This paper presents a concept for the measurement and control of the substrate concentration in a continuously operated biological tank reactor (CBTR). The concept was successfully applied in the degradation of Naphthalenesulfonic acid by the culture Pseudomonas testosteroni. The measurement of the substrate concentration was carried out by means of an automated HPLC (high performance liquid chromatography) analysis of the contents of the reactor. The methods of cyclic sampling, sample filtration and evaluation of the chromatograms during the process control are explained. In addition the characteristics of the measuring system (linearity of measurement, noise disturbance data, sampling rates, transient behavior) are described in detail. The feed-back control of the substrate concentration was carried out by variations in the dilution rate with a constant substrate feed concentration. The control results were achieved with a controller which was specially developed to be used in connection with automated cyclic analysis processes. The control algorithm is explained and the conditions necessary for maintaining stability of the control loop are given.     

Bioprocess control from a multivariate process trajectory

A multivariate bioprocess control approach, capable of tracking a pre-set process trajectory correlated to the biomass or product concentration in the bioprocess is described. The trajectory was either a latent variable derived from multivariate statistical process monitoring (MSPC) based on partial least squares (PLS) modeling, or the absolute value of the process variable. In the control algorithm the substrate feed pump rate was calculated from on-line analyzer data. The only parameters needed were the substrate feed concentration and the substrate yield of the growth-limiting substrate. On-line near-infrared spectroscopy data were used to demonstrate the performance of the control algorithm on an Escherichia coli fed-batch cultivation for tryptophan production. The controller showed good ability to track a defined biomass trajectory during varying process dynamics. The robustness of the control was high, despite significant external disturbances on the cultivation and control parameters.     

Identification and estimation algorithm for stochastic neural system. II

The algorithm for identifying the stochastic neural system and estimating the system process which reflects the dynamics of the neural network are presented in this papar. The analogous algorithm has been proposed in our preceding paper (Nakao et al., 1984), which was based on the randomly missed observations of a system process only. Since the previous algorithm mentioned above was subject to an unfavorable effect of consecutively missed observations, to reduce such an effect the algorithm proposed here is designed additionally to observe an intensity process in a neural spike train as the information for the estimation.The algorithm is constructed with the extended Kalman filters because it is naturally expected that a nonlinear and time variant structure is necessary for the filters to realize the observation of an intensity process by means of mapping from a system process to an intensity process. The performance of the algorithm is examined by applying it to some artificial neural systems and also to cat's visual nervous systems. The results in these applications are thought to prove the effectiveness of the algorithm proposed here and its superiority to the algorithm proposed previously.     

Maximizing power production in a stack of microbial fuel cells using multiunit optimization method

This study demonstrates real‐time maximization of power production in a stack of two continuous flow microbial fuel cells (MFCs). To maximize power output, external resistances of two air–cathode membraneless MFCs were controlled by a multiunit optimization algorithm. Multiunit optimization is a recently proposed method that uses multiple similar units to optimize process performance. The experiment demonstrated fast convergence toward optimal external resistance and algorithm stability during external perturbations (e.g., temperature variations). Rate of the algorithm convergence was much faster than in traditional maximum power point tracking algorithms (MPPT), which are based on temporal perturbations. A power output of 81–84 mW/L_A (A = anode volume) was achieved in each MFC. © 2009 American Institute of Chemical Engineers Biotechnol. Prog., 2009     

O-12The use of control samples in the PAPANICOLAOU technical external quality assessment scheme

Technical external quality assessment (TEQA) in Wales is based on NHSCSP publication 19, which sets out policy and procedures for the scheme. The purpose of EQA is to sustain and improve the quality of patient care by promoting a high standard of performance. Following the introduction of liquid base cytology (LBC) technical limitations, particularly in assessing counterstaining, have been noted. LBC provides the means to address these limitations - As part of a development plan for TEQA in Wales, a control sample procedure was introduced to the scheme. A pooled control sample was composed, containing residual material from six 'matched' negative samples, re-suspended in collection fluid. Aliquots of this sample were distributed for processing and staining, to the 13 laboratories registered with the scheme. The slides produced were assessed at a scheduled TEQA assessment in accordance with the standard criteria. Initial overall scoring for these control samples produced acceptable levels of staining for 12 of the laboratories - one laboratory produced a marginal score. Repeat distributions have shown maintained or improved results. This method provides a prospective quality assessment tool, which counters the emphasis on slide selection and eliminates potential selection bias, whilst introducing consistency and improving comparability across participant laboratories. The method may also prove helpful in identifying technical inconsistencies such as equipment or handling errors that may occur during sample processing prior to or during staining. The control process, which is now used routinely in the Welsh TEQA scheme; is considered complimentary to, and not a replacement for, the selection process established in NHSCSP #19. However, we feel that this development could be considered as a new initiative in the National TEQA scheme. The control process is applicable to all LBC systems in current use.     

Ionic liquid-based preparation of cellulose-dendrimer films as solid supports for enzyme immobilization

Surface-active cellulose films for covalent attachment of bioactive moieties were achieved by codissolution of cellulose with polyamidoamine (PAMAM) dendrimers in an ionic liquid followed by regeneration of the composite as a film. Different generations of PAMAM were used for the formation of cellulose-dendrimer composites, as well as films with the dendrimer covalently bonded to the cellulose by means of the linker 1,3-phenylene diisocyanate. Surface characterization, thermal stability, and utility for immobilization of laccase were determined. The presence of the dendrimer amino groups was confirmed by detailed characterization of the films' surfaces. These modified films exhibit acceptable thermal stability, comparable to that of other regenerated cellulose films, but the number of active functional groups on the surface is much smaller than the theoretical amount expected. Films made with 1,3-phenylene diisocyanate as linker for covalently bound cellulose and dendrimers exhibit a better performance for immobilization of laccase than those prepared by simple mixing of the cellulose and dendrimer. In general, a linear correspondence between the dendrimer generation within the films and the specific activity of immobilized laccase in such films was not observed.     

Characterising the searchability of continuous optimisation problems for PSO

The focus of research in swarm intelligence has been largely on the algorithmic side with relatively little attention being paid to the study of problems and the behaviour of algorithms in relation to problems. When a new algorithm or variation on an existing algorithm is proposed in the literature, there is seldom any discussion or analysis of algorithm weaknesses and on what kinds of problems the algorithm is expected to fail. Fitness landscape analysis is an approach that can be used to analyse optimisation problems. By characterising problems in terms of fitness landscape features, the link between problem types and algorithm performance can be studied. This article investigates a number of measures for analysing the ability of a search process to improve fitness on a particular problem (called evolvability in literature but referred to as searchability in this study to broaden the scope to non-evolutionary-based search techniques). A number of existing fitness landscape analysis techniques originally proposed for discrete problems are adapted to work in continuous search spaces. For a range of benchmark problems, the proposed searchability measures are viewed alongside performance measures for a traditional global best particle swarm optimisation (PSO) algorithm. Empirical results show that no single measure can be used as a predictor of PSO performance, but that multiple measures of different fitness landscape features can be used together to predict PSO failure.     

Adaptive pole placement control algorithm for DO-control in beta-lactamase production

The dissolved oxygen (DO) is an important variable in aerobic fermentations and affects the cell growth and product formation. Dissolved oxygen control is difficult in batch fermentations because of the time-varying conditions, time delays, and the probe dynamics. Modeling of the various patterns of biological activity in fermentations and their impact on the DO process dynamics is essential to both achieve a satisfactory control and to track the aforementioned patterns. An adaptive pole placement algorithm with time-delay compensation was used for controlling the DO, coupled with system identification using recursively estimated autoregressive models with exogeneous inputs (ARX). The flow rate of O2 in a constant flow rate gas inlet mixture is used as the manipulated variable. Supervision and coordination techniques are applied to improve the control performance. The control performance is affected by the accuracy of the model prediction and the selected time delay. The effect of DO level on the productivity of beta-lactamase using Bacillus subtilis under oxygen-limited conditions is investigated. Beta-lactamase stability is improved under prolonged growth conditions with low DO levels.     

Estimating maximum and psychophysically acceptable hand forces using a biomechanical weakest link approach

Accurate estimation of occupational performance capability facilitates better job (re-) design by informing workplace parties about the potential mismatches between job demands and the capability of their labour force. However, estimating occupational performance requires consideration of multiple factors that may govern capacity. In this paper, a novel model is described that uses a stochastic algorithm to estimate how variability in underlying biomechanical constraints affects hand force capability. In addition, the model estimates psychophysically acceptable hand force capacity thresholds by applying a biomechanical weakest link approach. Model estimates were tested against experimentally determined maximal and psychophysically determined hand forces in two exertion directions in constrained postures. The model underestimated maximum hand force capacity relative to measured maximum hand force by 30% and 35% during downward pressing and horizontal pulling, respectively. These values are consistent with those observed using previous two-dimensional models. Psychophysically acceptable hand forces were also underestimated by 29% during both pressing and pulling. Since the psychophysical estimates were scaled as a percentage of the estimated maximum capacity, this suggests that the underestimation in both predictions may be corrected by improving estimates of maximum hand force. Psychophysically acceptable forces were observed to be partially governed by demands at the biomechanical weakest link.     

Modeling and Design of H-Infinity Controller for Piezoelectric Actuator LIPCA

<正> We proposed a dynamic model identification and design of an H-Infinity (i.e.H_∞) controller using a LightweightPiezo-Composite Actuator (LIPCA).A second-order dynamic model was obtained by using input and output data, and applyingan identification algorithm.The identified model coincides well with the real LIPCA.To reduce the resonating mode that istypical of piezoelectric actuators, a notch filter was used.A feedback controller using the H_∞ control scheme was designed basedon the identified dynamic model; thus, the LIPCA can be easily used as an actuator for biomemetic applications such as artificialmuscles or macro/micro positioning in bioengineering.The control algorithm was implemented using a microprocessor, analogfilters, and power amplifying drivers.Our simulation and experimental results demonstrate that the proposed control algorithmworks well in real environment, providing robust performance and stability with uncertain disturbances.     

Development of renewable surface biosensors to meet industrial needs for measurement of glucose in fruit juices.

Most biosensors reported to date have been prepared, studied and used under laboratory conditions. The feasibility of a very great number of biosensors seems to be demonstrated and their characteristics, very often, established as corresponding to the demands of the modern analysis. The operational stability of the biosensors, according to authors, is almost always acceptable. The long term storage, with analytical quality conservation that is necessary to commercialise products, has rarely been studied. The stability of biosensors has to remain not only during the fabrication step or their subsequent utilisation, but also throughout the whole commercial shelf-life of the sensor, from producer to end user, through wholesaler and/or retailer. We developed the manufacturing processes, on a large scale, of renewable surface electrodes modified with enzymes such as oxidoreductases. The process consisting of several steps is described and the analytical behaviours of resulting biosensors is studied and correlated with the effects of different constraints applied during the fabrication process.     

Exercise of mechanisms for dynamic stability control increases stability performance in the elderly

Old adults show a decreased recovery performance compared to young ones after unexpected perturbations increasing the risk of falls. Therefore, the purpose of the present study was to examine the effect of a specific training of mechanisms responsible for dynamic stability on the recovery performance of old adults after simulated forward falls and the contribution of muscle strength exercise. 38 old adults (two experimental groups each n=13 and a control group, n=12) participated in the study. Group 1 exercised the mechanisms responsible for dynamic stability like increase in base of support and counter-rotating segments around the centre of mass by practicing specific tasks including these mechanisms. Group 2 exercised these mechanisms of dynamic stability and muscle strength. The exercise volume was equal in both interventions (14 weeks, two times per week and ～1.5 h per session). Stability performance has been examined by simulated forward falls before and after the intervention. The two experimental groups improved in a similar extent (～35%) their ability to regain balance during forward falls after the intervention. The reason was a faster increase in base of support. Further, the performance enhancement was related to an increase in the rate of hip moment generation. Exercising the mechanisms responsible for dynamic stability control in old adults affects their ability to regain balance after forward falls. A faster utilization of these mechanisms due to improved neuromuscular coordination resulted in the significant performance enhancement.     

Cooperative optimal control: broadening the reach of bio-inspiration

Inspired by the process by which ants gradually optimize their foraging trails, this paper investigates the cooperative solution of a class of free final time, partially constrained final state optimal control problems by a group of dynamical systems. We propose an iterative, pursuit-based algorithm which generalizes previously proposed models and converges to an optimal solution by iteratively optimizing an initial feasible trajectory/control pair. The proposed algorithm requires only short-range, limited interactions between group members, avoids the need for a 'global map' of the environment in which the group evolves, and solves an optimal control problem in 'small' pieces, in a manner which will be made precise. The performance of the algorithm is illustrated in a series of simulations and laboratory experiments.     

Adaptive control of anaerobic digestion processes-a pilot-scale application

A simple adaptive control algorithm, for which theoretical stability and convergence properties had been previously demonstrated, has been successfully implemented on a biomethanation pilot reactor. The methane digester, operated in the CSTR mode was submitted to a shock load, and successfully computer controlled during the subsequent transitory state.