Monitoring online biomass with a capacitance sensor during scale-up of industrially relevant CHO cell culture fed-batch processes in single-use bioreactors

Minimizing batch-to-batch variability of a live virus vaccine by process analytical technologies

For bioprocesses producing live virus, such as enterovirus Coxsackievirus A21, viral titer (infectivity basis) decay rates can exceed 30% within a day. Consequently, harvest timing is paramount. To optimize titer at harvest, a continuous viral product titer model was generated to elucidate kinetics. The model leveraged experimentally determined viable cell density, cell-specific viral productivity, and viral specific decay rates. Next, three separate online process analytical technology (PAT) harvest triggers were developed to predict maximal viral titer. Finally, the PAT harvest triggers were tested alongside traditional time-based harvests. The harvest triggers utilized common bioprocessing tools - dissolved oxygen (DO) and capacitance probes - to track DO and viable cell volume (VCV) and derived a third parameter, cell-specific oxygen uptake rate. Harvesting with PAT triggers allowed for significantly improved batch-to-batch consistency. The standard deviation of harvest yield was reduced by 41% (DO), 56% (OUR) and 71% (capacitance) as compared to the industry standard time-based harvest. Even when a process deviation in inoculated cell density occurred, causing a significant shift in viral titer kinetics, the PAT harvest triggers yielded greater than 87% of peak titer. By comparison, the time-based harvest yielded 16%.

Real-Time Auto Controlling of Viable Cell Density in Perfusion Cultivation Aided by In-Line Dielectric Spectroscopy With Segmented Adaptive PLS Model

Serving as a dedicated process analytical technology (PAT) tool for biomass monitoring and control, the capacitance probe, or dielectric spectroscopy, is showing great potential in robust pharmaceutical manufacturing, especially with the growing interest in integrated continuous bioprocessing. Despite its potential, challenges still exist in terms of its accuracy and applicability, particularly when it is used to monitor cells during stationary and decline phases. In this study, data pre-processing methods were first evaluated through cross-validation, where the first-order derivative emerged as the most effective method to diminish variability in prediction accuracy across different training datasets. Subsequently, a segmented adaptive partial least squares (SA-PLS) model was developed, and its accuracy and universality were demonstrated through several validation studies using different clones and culture processes. Furthermore, a real-time viable cell density (VCD) auto-control system in perfusion culture was established, where the VCD was maintained around the target with notable precision and robustness. This model enhanced the monitoring capabilities of capacitance-based PAT tools throughout the cultivation, expanded their application in cell-specific automatic control strategies, and contributed vitally to the advancement of continuous manufacturing paradigms.

Sensitivity of bulk electrical impedance spectroscopy (bio-capacitance) probes to cell and culture properties: Study on CHO cell cultures

Bulk electrical impedance spectroscopy (bio-capacitance) probes, hold significant promise for real-time cell monitoring in bioprocesses. Focusing on Chinese hamster ovary (CHO) cells, we present a sensitivity analysis framework to assess the impact of cell and culture properties on the complex permittivity spectrum, εmix, and its associated parameters, permittivity increment, Δε, critical frequency, fc, and Cole-Cole parameter, α, measured by bio-capacitance probes. Our sensitivity analysis showed that Δε is highly sensitive to cell size and concentration, making it suitable for estimating biovolume during the exponential growth phase, whereas fc provides information about cumulative changes in cell size, membrane permittivity, and cytoplasm conductivity during the transition to death phase. The analysis indicated that specific information about cell membrane permittivity or internal conductivity cannot be extracted from εmix spectrum. Based on the sensitivity analysis, we proposed two alternative parameters for monitoring cells in bioprocesses: Δε1 MHz and Δε1 MHz/Δε0.3 MHz, using measurements at 300 kHz, 1 MHz, and 10 MHz. Δε1 MHz is suitable for estimating viable cell density during the exponential growth phase due to its lower sensitivity to cell size. Δε1 MHz/Δε0.3 MHz can replace fc due to similar sensitivities to cell size and dielectric properties. These frequencies are within most bio-capacitance probes' optimal operation range, eliminating the need for low-frequency electrode polarization and high-frequency stray capacitances corrections. Experimental measurements on CHO cells confirmed the results of sensitivity analysis.

Real-Time VCC Monitoring and Forecasting in HEK-Cell-Based rAAV Vector Production Using Capacitance Spectroscopy

Recombinant adeno-associated virus (rAAV) vector production is a complex process in which the robust cultivation of human embryonic kidney cells (HEK293) plays a critical role in generating high-quality viral vectors. Tracking the viable cell concentration (VCC) during upstream production is essential for process monitoring and for implementing actions that ensure optimal process management. The advent of inline capacitance probes has introduced a crucial process analytical technology (PAT) tool for real-time VCC measurement. Here, we present the development and application of a method for real-time monitoring of VCC in HEK293-based rAAV vector production. In a first step, BioPAT Viamass probes were used to record capacitance data of individual 10 L rAAV-8 batches within a frequency range of 50 kHz-20 MHz. Based on the capacitance data, a linear single-frequency model and an orthogonal partial least square (OPLS) multifrequency model for VCC prediction were developed. Subsequently, these models were deployed inline, and predictions were exposed into BioPAT MFCS bioprocess control software, enabling real-time VCC monitoring in subsequent rAAV-8 production batches. In addition, the continuous VCC signal was used as input for an exponential cell growth model that was deployed inline to provide accurate real-time forecasting of the transfection time point. To the best of our knowledge, this is the first example of inline deployment of VCC and Time-Till-Transfection predictive models to the bioprocess control system for real-time monitoring and forecasting of these parameters in HEK-cell-based transient rAAV vector production.

Defining Golden Batches in Biomanufacturing Processes From Internal Metabolic Activity to Detect Process Changes That May Affect Product Quality

Cellular metabolism plays a role in the observed variability of a drug substance's Critical Quality Attributes (CQAs) made by biomanufacturing processes. Therefore, here we describe a new approach for monitoring biomanufacturing processes that measures a set of metabolic reaction rates (named Critical Metabolic Parameters (CMP) in addition to the macroscopic process conditions currently being used as Critical Process Parameters (CPP) for biomanufacturing. Constraint-based systems biology models like Flux Balance Analysis (FBA) are used to estimate metabolic reaction rates, and metabolic rates are used as inputs for multivariate Batch Evolution Models (BEM). Metabolic activity was reproducible among batches and could be monitored to detect a deliberately induced macroscopic process shift (i.e., temperature change). The CMP approach has the potential to enable "golden batches" in biomanufacturing processes to be defined from the internal metabolic activity and to aid in detecting process changes that may impact the quality of the product. Overall, the data suggested that monitoring of metabolic activity has promise for biomanufacturing process control.

Single-Use, Metabolite Absorbing, Resonant Transducer (SMART) Culture Vessels for Label-Free, Continuous Cell Culture Progression Monitoring

Secreted metabolites are an important class of bio-process analytical technology (PAT) targets that can correlate to cell conditions. However, current strategies for measuring metabolites are limited to discrete measurements, resulting in limited understanding and ability for feedback control strategies. Herein, a continuous metabolite monitoring strategy is demonstrated using a single-use metabolite absorbing resonant transducer (SMART) to correlate with cell growth. Polyacrylate is shown to absorb secreted metabolites from living cells containing hydroxyl and alkenyl groups such as terpenoids, that act as a plasticizer. Upon softening, the polyacrylate irreversibly conformed into engineered voids above a resonant sensor, changing the local permittivity which is interrogated, contact-free, with a vector network analyzer. Compared to sensing using the intrinsic permittivity of cells, the SMART approach yields a 20-fold improvement in sensitivity. Tracking growth of many cell types such as Chinese hamster ovary, HEK293, K562, HeLa, and E. coli cells as well as perturbations in cell proliferation during drug screening assays are demonstrated. The sensor is benchmarked to show continuous measurement over six days, ability to track different growth conditions, selectivity to transducing active cell growth metabolites against other components found in the media, and feasibility to scale out for high throughput campaigns.

Mimicking CHO large-scale effects in the single multicompartment bioreactor: A new approach to access scale-up behavior

During the scale-up of biopharmaceutical production processes, insufficiently predictable performance losses may occur alongside gradients and heterogeneities. To overcome such performance losses, tools are required to explain, predict, and ultimately prohibit inconsistencies between laboratory and commercial scale. In this work, we performed CHO fed-batch cultivations in the single multicompartment bioreactor (SMCB), a new scale-down reactor system that offers new access to study large-scale heterogeneities in mammalian cell cultures. At volumetric power inputs of 20.4-1.5 W m-3, large-scale characteristics like long mixing times and dissolved oxygen (DO) heterogeneities were mimicked in the SMCB. Compared to a reference bioreactor (REFB) set-up, the conditions in the SMCB provoked an increase in lactate accumulation of up to 87%, an increased glucose uptake, and reduced viable cell concentrations in the stationary phase. All are characteristic for large-scale performance. The unique possibility to distinguish between the effects of changing power inputs and observed heterogeneities provided new insights into the potential reasons for altered product quality attributes. Apparently, the degree of galactosylation in the evaluated glycan patterns changed primarily due to the different power inputs rather than the provoked heterogeneities. The SMCB system could serve as a potent tool to provide new insights into scale-up behavior and to predict cell line-specific drawbacks at an early stage of process development.

Maduramycin, a novel glycosylation modulator for mammalian fed-batch and steady-state perfusion processes

Controlling high-mannose (HM) content of therapeutic proteins during process intensification, reformulation for subcutaneous delivery, antibody-drug conjugate or biosimilar manufacturing represents an ongoing challenge. Even though a range of glycosylation levers to increase HM content exist, modulators specially increasing M5 glycans are still scarce. Several compounds of the polyether ionophore family were screened for their ability to selectively increase M5 glycans of mAb products and compared to the well-known α-mannosidase I inhibitor kifunensine known to increase mainly M8-M9 glycans. Maduramycin, amongst other promising polyether ionophores, showed the desired effect on different cell lines. For fed-batch processes, a double bolus addition modulator feed strategy was developed maximizing the effect on glycosylation by minimizing impact on culture performance. Further, a continuous feeding strategy for steady-state perfusion processes was successfully developed, enabling consistent product quality at elevated HM glycan levels. With kifunensine and maduramycin showing inverse effects on the relative HM distribution, a combined usage of these modulators was further evaluated to fine-tune a desired HM glycan pattern. The discovered HM modulators expand the current HM modulating toolbox for biotherapeutics. Their application not only for fed-batch processes, but also steady-state perfusion processes, make them a universal tool with regards to fully continuous manufacturing processes.

Adaptive modeling optimized by the data fusion strategy: Real-time dying cell percentage prediction using capacitance spectroscopy

The previous research showcased a partial least squares (PLS) regression model accurately predicting cell death percentages using in-line capacitance spectra. The current study advances the model accuracy through adaptive modeling employing a data fusion approach. This strategy enhances prediction performance by incorporating variables from the Cole-Cole model, conductivity and its derivatives over time, and Mahalanobis distance into the predictor matrix (X-matrix). Firstly, the Cole-Cole model, a mechanistic model with parameters linked to early cell death onset, was integrated to enhance prediction performance. Secondly, the inclusion of conductivity and its derivatives over time in the X-matrix mitigated prediction fluctuations resulting from abrupt conductivity changes during process operations. Thirdly, Mahalanobis distance, depicting spectral changes relative to a reference spectrum from a previous time point, improved model adaptability to independent test sets, thereby enhancing performance. The final data fusion model substantially decreased root-mean squared error of prediction (RMSEP) by around 50%, which is a significant boost in prediction accuracy compared to the prior PLS model. Robustness against reference spectrum selection was confirmed by consistent performance across various time points. In conclusion, this study illustrates that the data fusion strategy substantially enhances the model accuracy compared to the previous model relying solely on capacitance spectra.

Co-current filtrate flow in TFF perfusion processes: Decoupling transmembrane pressure from crossflow to improve product sieving

Hollow fiber-based membrane filtration has emerged as the dominant technology for cell retention in perfusion processes yet significant challenges in alleviating filter fouling remain unsolved. In this work, the benefits of co-current filtrate flow applied to a tangential flow filtration (TFF) module to reduce or even completely remove Starling recirculation caused by the axial pressure drop within the module was studied by pressure characterization experiments and perfusion cell culture runs. Additionally, a novel concept to achieve alternating Starling flow within unidirectional TFF was investigated. Pressure profiles demonstrated that precise flow control can be achieved with both lab-scale and manufacturing-scale filters. TFF systems with co-current flow showed up to 40% higher product sieving compared to standard TFF. The decoupling of transmembrane pressure from crossflow velocity and filter characteristics in co-current TFF alleviates common challenges for hollow fiber-based systems such as limited crossflow rates and relatively short filter module lengths, both of which are currently used to avoid extensive pressure drop along the filtration module. Therefore, co-current filtrate flow in unidirectional TFF systems represents an interesting and scalable alternative to standard TFF or alternating TFF operation with additional possibilities to control Starling recirculation flow.

Growth prolongation of human induced pluripotent stem cell aggregate in three-dimensional suspension culture system by addition of botulinum hemagglutinin

Human induced pluripotent stem cells (hiPSCs) can be used in regenerative therapy as an irresistible cell source, and so the development of scalable production of hiPSCs for three-dimensional (3D) suspension culture is required. In this study, we established a simple culture strategy for improving hiPSC aggregate growth using botulinum hemagglutinin (HA), which disrupts cell-cell adhesion mediated by E-cadherin. When HA was added to the suspension culture of hiPSC aggregates, E-cadherin-mediated cell-cell adhesion was temporarily disrupted within 24 h, but then recovered. Phosphorylated myosin light chain, a contractile force marker, was also recovered at the periphery of hiPSC aggregates. The cell aggregates were suppressed the formation of collagen type I shell-like structures at the periphery by HA and collagen type I was homogenously distributed within the cell aggregates. In addition, these cell aggregates retained the proliferation marker Ki-67 throughout the cell aggregates. The apparent specific growth rate with HA addition was maintained continuously throughout the culture, and the final cell density was 1.7-fold higher than that in the control culture. These cells retained high expression levels of pluripotency markers. These observations indicated that relaxation of cell-cell adhesions by HA addition induced rearrangement of the mechanical tensions generated by actomyosin in hiPSC aggregates and suppression of collagen type I shell-like structure formation. These results suggest that this simple and readily culture strategy is a potentially useful tool for improving the scalable production of hiPSCs for 3D suspension cultures.

In situ process analytical technology for real time viable cell density and cell viability during live-virus vaccine production

Viable cell density (VCD) and cell viability (CV) are key performance indicators of cell culture processes in biopharmaceutical production of biologics and vaccines. Traditional methods for monitoring VCD and CV involve offline cell counting assays that are both labor intensive and prone to high variability, resulting in sparse sampling and uncertainty in the obtained data. Process analytical technology (PAT) approaches offer a means to address these challenges. Specifically, in situ probe-based measurements of dielectric spectroscopy (also commonly known as capacitance) can characterize VCD and CV continuously in real time throughout an entire process, enabling robust process characterization. In this work, we propose in situ dielectric spectroscopy as a PAT tool for real time analysis of live-virus vaccine (LVV) production. Dielectric spectroscopy was collected across 25 discreet frequencies, offering a thorough evaluation of the proposed technology. Correlation of this PAT methodology to traditional offline cell counting assays was performed, in which VCD and CV were both successfully predicted using dielectric spectroscopy. Both univariate and multivariate data analysis approaches were evaluated for their potential to establish correlation between the in situ dielectric spectroscopy and offline measurements. Univariate analysis strategies are presented for optimal single frequency selection. Multivariate analysis, in the form of partial least squares (PLS) regression, produced significantly higher correlations between dielectric spectroscopy and offline VCD and CV data, as compared to univariate analysis. Specifically, by leveraging multivariate analysis of dielectric information from all 25 spectroscopic frequencies measured, PLS models performed significantly better than univariate models. This is particularly evident during cell death, where tracking VCD and CV have historically presented the greatest challenge. The results of this work demonstrate the potential of both single and multiple frequency dielectric spectroscopy measurements for enabling robust LVV process characterization, suggesting that broader application of in situ dielectric spectroscopy as a PAT tool in LVV processes can provide significantly improved process understanding. To the best of our knowledge, this is the first report of in situ dielectric spectroscopy with multivariate analysis to successfully predict VCD and CV in real time during live virus-based vaccine production.

Current and future technologies for monitoring cultured meat: A review

The high population growth rate, massive animal food consumption, fast economic progress, and limited food resources could lead to a food crisis in the future. There is a huge requirement for dietary proteins including cultured meat is being progressed to fulfill the need for meat-derived proteins in the diet. However, production of cultured meat requires monitoring numerous bioprocess parameters. This review presents a comprehensive overview of various widely adopted techniques (optical, spectroscopic, electrochemical, capacitive, FETs, resistive, microscopy, and ultrasound) for monitoring physical, chemical, and biological parameters that can improve the bioprocess control in cultured meat. The methods, operating principle, merits/demerits, and the main open challenges are reviewed with the aim to support the readers in advancing knowledge on novel sensing systems for cultured meat applications.

Capacitance sensors in cell-based bioprocesses: online monitoring of biomass and more

Biocapacitance measurement has emerged as a widely used technique for monitoring bioprocesses that involve living cells. Over time, hardware and software developments have enabled this method to move from food towards biopharma industries for improved characterisation, monitoring and control of the bioprocess, even in strictly regulated production environments. In alignment with the general trends in biopharma towards new modalities such as virus-based and cell-based therapies, biocapacitance measurement is entering this area and provides new opportunities for process development and control. Based on the recent progress, the authors strongly believe that even though biocapacitance measurement is a mature, established technology for online biomass monitoring, the nearest future will bring its new and exciting developments and applications that will enhance bioprocess understanding and bring new solutions for enhanced process understanding, monitoring and control.

Towards advanced bioprocess optimization: A multiscale modelling approach

Mammalian cells produce up to 80 % of the commercially available therapeutic proteins, with Chinese Hamster Ovary (CHO) cells being the primary production host. Manufacturing involves a train of reactors, the last of which is typically run in fed-batch mode, where cells grow and produce the required protein. The feeding strategy is decided a priori, from either past operations or the design of experiments and rarely considers the current state of the process. This work proposes a Model Predictive Control (MPC) formulation based on a hybrid kinetic-stoichiometric reactor model to provide optimal feeding policies in real-time, which is agnostic to the culture, hence transferable across CHO cell culture systems. The benefits of the proposed controller formulation are demonstrated through a comparison between an open-loop simulation and closed-loop optimization, using a digital twin as an emulator of the process.

Development of an Automated Online Flow Cytometry Method to Quantify Cell Density and Fingerprint Bacterial Communities

Cell density is an important factor in all microbiome research, where interactions are of interest. It is also the most important parameter for the operation and control of most biotechnological processes. In the past, cell density determination was often performed offline and manually, resulting in a delay between sampling and immediate data processing, preventing quick action. While there are now some online methods for rapid and automated cell density determination, they are unable to distinguish between the different cell types in bacterial communities. To address this gap, an online automated flow cytometry procedure is proposed for real-time high-resolution analysis of bacterial communities. On the one hand, it allows for the online automated calculation of cell concentrations and, on the other, for the differentiation between different cell subsets of a bacterial community. To achieve this, the OC-300 automation device (onCyt Microbiology, Zürich, Switzerland) was coupled with the flow cytometer CytoFLEX (Beckman Coulter, Brea, USA). The OC-300 performs the automatic sampling, dilution, fixation and 4',6-diamidino-2-phenylindole (DAPI) staining of a bacterial sample before sending it to the CytoFLEX for measurement. It is demonstrated that this method can reproducibly measure both cell density and fingerprint-like patterns of bacterial communities, generating suitable data for powerful automated data analysis and interpretation pipelines. In particular, the automated, high-resolution partitioning of clustered data into cell subsets opens up the possibility of correlation analysis to identify the operational or abiotic/biotic causes of community disturbances or state changes, which can influence the interaction potential of organisms in microbiomes or even affect the performance of individual organisms.

Measuring and modeling macrophage proliferation in a lab-on-CMOS capacitance sensing microsystem

We report on the use of a lab-on-CMOS biosensor platform for quantitatively tracking the proliferation of RAW 264.7 murine Balb/c macrophages. We show that macrophage proliferation correlates linearly with an average capacitance growth factor resulting from capacitance measurements at a plurality of electrodes dispersed in a sensing area of interest. We further show a temporal model that captures the cell number evolution in the area over long periods (e.g., 30 h). The model links the cell numbers and the average capacitance growth factor to describe the observed cell proliferation.

Mammalian Cell-Growth Monitoring Based on an Impedimetric Sensor and Image Processing within a Microfluidic Platform

In recent years, advancements in microfluidic and sensor technologies have led to the development of new methods for monitoring cell growth both in macro- and micro-systems. In this paper, a microfluidic (MF) platform with a microbioreactor and integrated impedimetric sensor is proposed for cell growth monitoring during the cell cultivation process in a scaled-down simulator. The impedimetric sensor with an interdigitated electrode (IDE) design was realized with inkjet printing and integrated into the custom-made MF platform, i.e., the scaled-down simulator. The proposed method, which was integrated into a simple and rapid fabrication MF system, presents an excellent candidate for the scaled-down analyses of cell growths that can be of use in, e.g., optimization of the cultivated meat bioprocess. When applied to MRC-5 cells as a model of adherent mammalian cells, the proposed sensor was able to precisely detect all phases of cell growth (the lag, exponential, stationary, and dying phases) during a 96-h cultivation period with limited available nutrients. By combining the impedimetric approach with image processing, the platform enables the real-time monitoring of biomasses and advanced control of cell growth progress in microbioreactors and scaled-down simulator systems.

Biosorption of process-equipment-related leachables (PERLs) in biomanufacturing: A quantitative approach to study partitioning of PERLs in a cell culture system

The assessment and potential risk of process equipment-related leachables (PERLs) in the production of biopharmaceuticals and cell therapeutics using single-use (SU) equipment has been discussed previously. However, potential interactions of cells with PERLs have not yet been considered. Here, we present a quantitative adsorption study of neutral, organic small-molecule leachable compounds - known for extractables & leachables (E&L) analysis of SU equipment - in aqueous suspensions of CHO and T cells. The solid-water partition coefficient K_d was obtained for all compounds that showed adsorption. The findings implied that hydrophobic interactions are dominant; however, there was no unambiguous correlation between the derived adsorption coefficient K_d and the octanol-water partition coefficient K_ow. Interestingly, a maximum affinity of both cell types to the leachable bis(2,4-di-tert-butylphenyl)phosphate, which is known to be detrimental to cell development, was observed. A comparison of both cell types revealed that they generally interact with the same compounds in most cases but to different extents. Using partition coefficients enables estimation of the concentrations of leachable compounds associated with the biomass phase and in the aqueous suspensions and could be used for risk assessment of SU systems in biopharmaceutical and cell therapy (CT) manufacturing processes.

A disposable impedance-based sensor for in-line cell growth monitoring in CAR-T cell manufacturing

This paper presents the development of low-cost, disposable impedance-based sensors for real-time, in-line monitoring of suspension cell culture. The sensors consist of electrical discharge machining (EDM) cut aluminum electrodes and polydimethylsiloxane (PDMS) spacers, both of which are low-cost materials that can be safely disposed of. Our research demonstrates the capability of these low-cost sensors for in-line, non-invasive monitoring of suspension cell growth in cell manufacturing. We use a hybrid equivalent circuit model to extract key features/parameters from intertwined impedance signals, which are then fed to a novel physics-inspired (gray-box) model designed for α-relaxation. This model determines viable cell count (VCC), a critical quality attribute (CQA) in cell manufacturing. Predicted VCC trends are then compared with image-based cell count data to verify their accuracy.

Capacitance spectroscopy enables real-time monitoring of early cell death in mammalian cell culture

BACKGROUND/AIMS

Previous work developed a quantitative model using capacitance spectroscopy in an at-line setup to predict the dying cell percentage measured from a flow cytometer. This work aimed to transfer the at-line model to monitor lab-scale bioreactors in real-time, waiving the need for frequent sampling and enabling precise controls.

METHODS AND RESULTS

Due to the difference between the at-line and in-line capacitance probes, direct application of the at-line model resulted in poor accuracy and high prediction bias. A new model with a variable range and offering similar spectral shape across all probes was first constructed, improving prediction accuracy. Moreover, the global calibration method included the variance of different probes and scales in the model, reducing prediction bias. External parameter orthogonalization, a preprocessing method, also mitigated the interference from feeding, which further improved model performance. The root-mean-square error of prediction of the final model was 6.56% (8.42% of the prediction range) with an R² of 92.4%.

CONCLUSION

The culture evolution trajectory predicted by the in-line model captured the cell death and alarmed cell death onset earlier than the trypan blue exclusion test. Additionally, the incorporation of at-line spectra following orthogonal design into the calibration set was shown to generate calibration models that are more robust than the calibration models constructed using the in-line spectra only. This is advantageous, as at-line spectral collection is easier, faster, and more material-sparing than in-line spectra collection.

Advances in bioreactor control for production of biotherapeutic products

Advanced control strategies are well established in chemical, pharmaceutical, and food processing industries. Over the past decade, the application of these strategies is being explored for control of bioreactors for manufacturing of biotherapeutics. Most of the industrial bioreactor control strategies apply classical control techniques, with the control system designed for the facility at hand. However, with the recent progress in sensors, machinery, and industrial internet of things, and advancements in deeper understanding of the biological processes, coupled with the requirement of flexible production, the need to develop a robust and advanced process control system that can ease process intensification has emerged. This has further fuelled the development of advanced monitoring approaches, modeling techniques, process analytical technologies, and soft sensors. It is seen that proper application of these concepts can significantly improve bioreactor process performance, productivity, and reproducibility. This review is on the recent advancements in bioreactor control and its related aspects along with the associated challenges. This study also offers an insight into the future prospects for development of control strategies that can be designed for industrial-scale production of biotherapeutic products.

Cell monitoring with optical coherence tomography

BACKGROUND AIMS

We evaluated a commercially available instrument, OCTiCell (chromologic.com/octicell), for monitoring cell growth in suspended agitated bioreactors based on optical coherence tomography. OCTiCell is an in-line, completely non-invasive instrument that can operate on any suspended-cell bioreactor with a window or transparent wall. In traditional optical coherence tomography, the imaging beam is rastered over the sample to form a three-dimensional image. OCTiCell, instead uses a fixed imaging beam and takes advantage of the motion of the media to move the cells across the interrogating optical beam.

RESULTS

We found strong correlations between the non-invasive, non-contact, reagent-free OCTiCell measurements of cell concentration and viability and those obtained from the automated cell counter, and the XTT viability assay, which is a colorimetric assay for quantifying metabolic activity.

CONCLUSIONS

This novel cell monitoring method can adapt to different bioreactor form factors and could reduce the labor cost and contamination risks associated with cell growth monitoring.

Measuring and Modeling Macrophage Growth using a Lab-on-CMOS Capacitance Sensing Microsystem

We report on the use of a lab-on-CMOS biosensor platform for quantitatively tracking the growth of RAW 264.7 murine Balb/c macrophages. We show that macrophage growth over a wide sensing area correlates linearly with an average capacitance growth factor resulting from capacitance measurements at a plurality of electrodes dispersed in the sensing area. We further show a temporal model that captures the cell evolution in the area of interest over long periods (e.g., 30 hours). The model links the cell numbers and the average capacitance growth factor associated with the sensing area to describe the observed growth kinetics.

Sensors and Techniques for On-Line Determination of Cell Viability in Bioprocess Monitoring

In recent years, the bioprocessing industry has experienced significant growth and is increasingly emerging as an important economic sector. Here, efficient process management and constant control of cellular growth are essential. Good product quality and yield can only be guaranteed with high cell density and high viability. Whereas the on-line measurement of physical and chemical process parameters has been common practice for many years, the on-line determination of viability remains a challenge and few commercial on-line measurement methods have been developed to date for determining viability in industrial bioprocesses. Thus, numerous studies have recently been conducted to develop sensors for on-line viability estimation, especially in the field of optical spectroscopic sensors, which will be the focus of this review. Spectroscopic sensors are versatile, on-line and mostly non-invasive. Especially in combination with bioinformatic data analysis, they offer great potential for industrial application. Known as soft sensors, they usually enable simultaneous estimation of multiple biological variables besides viability to be obtained from the same set of measurement data. However, the majority of the presented sensors are still in the research stage, and only a few are already commercially available.

Development of process analytical tools for rapid monitoring of live virus vaccines in manufacturing

In the development of end-to-end large-scale live virus vaccine (LVV) manufacturing, process analytical technology (PAT) tools enable timely monitoring of critical process parameters (CPP) and significantly guide process development and characterization. In a commercial setting, these very same tools can enable real time monitoring of CPPs on the shop floor and inform harvest decisions, predict peak potency, and serve as surrogates for release potency assays. Here we introduce the development of four advanced PAT tools for upstream and downstream process monitoring in LVV manufacturing. The first tool explores the application of capacitance probes for real time monitoring of viable cell density in bioreactors. The second tool utilizes high content imaging to determine optimum time of infection in a microcarrier process. The third tool uses flow virometry (or nanoscale flow cytometry) to monitor total virus particle counts across upstream and downstream process steps and establishes a robust correlation to virus potency. The fourth and final tool explores the use of nucleic acid dye staining to discriminate between “good” and “damaged” virus particles and uses this strategy to also monitor virus aggregates generated sometimes during downstream processing. Collectively, these tools provide a comprehensive monitoring toolbox and represent a significantly enhanced control strategy for the manufacturing of LVVs.

Advancing Raman model calibration for perfusion bioprocesses using spiked harvest libraries

BACKGROUND

Raman spectroscopy has gained popularity to monitor multiple process indicators simultaneously in biopharmaceutical processes. However, robust and specific model calibration remains a challenge due to insufficient analyte variability to train the models and high cross-correlation of various media components and artifacts throughout the process.

MAIN METHODS

A systematic Raman calibration workflow for perfusion processes enabling highly specific and fast model calibration was developed. Harvest libraries consisting of frozen harvest samples from multiple CHO cell culture bioreactors collected at different process times were established. Model calibration was subsequently performed in an offline setup using a flow cell by spiking process harvest with glucose, raffinose, galactose, mannose, and fructose.

MAJOR RESULTS

In a screening phase, Raman spectroscopy was proven capable not only to distinguish sugars with similar chemical structures in perfusion harvest but also to quantify them independently in process-relevant concentrations. In a second phase, a robust and highly specific calibration model for simultaneous glucose (RMSEP = 0.32 g/L) and raffinose (RMSEP = 0.17 g/L) real-time monitoring was generated and verified in a third phase during a perfusion process.

IMPLICATION

The proposed novel offline calibration workflow allowed proper Raman peak decoupling, reduced calibration time from months down to days, and can be applied to other analytes of interest including lactate, ammonia, amino acids, or product titer. This article is protected by copyright. All rights reserved.

N-1 Perfusion Platform Development Using a Capacitance Probe for Biomanufacturing

Fed-batch process intensification with a significantly shorter culture duration or higher titer for monoclonal antibody (mAb) production by Chinese hamster ovary (CHO) cells can be achieved by implementing perfusion operation at the N-1 stage for biomanufacturing. N-1 perfusion seed with much higher final viable cell density (VCD) than a conventional N-1 batch seed can be used to significantly increase the inoculation VCD for the subsequent fed-batch production (referred as N stage), which results in a shorter cell growth phase, higher peak VCD, or higher titer. In this report, we incorporated a process analytical technology (PAT) tool into our N-1 perfusion platform, using an in-line capacitance probe to automatically adjust the perfusion rate based on real-time VCD measurements. The capacitance measurements correlated linearly with the offline VCD at all cell densities tested (i.e., up to 130 × 10⁶ cells/mL). Online control of the perfusion rate via the cell-specific perfusion rate (CSPR) decreased media usage by approximately 25% when compared with a platform volume-specific perfusion rate approach and did not lead to any detrimental effects on cell growth. This PAT tool was applied to six mAbs, and a platform CSPR of 0.04 nL/cell/day was selected, which enabled rapid growth and maintenance of high viabilities for four of six cell lines. In addition, small-scale capacitance data were used in the scaling-up of N-1 perfusion processes in the pilot plant and in the GMP manufacturing suite. Implementing a platform approach based on capacitance measurements to control perfusion rates led to efficient process development of perfusion N-1 for supporting high-density CHO cell cultures for the fed-batch process intensification.

Rapid At-line Early Cell Death Quantification using Capacitance Spectroscopy

Cell death is one of the failure modes of mammalian cell culture. Apoptosis is a regulated cell death process mainly observed in cell culture. Timely detection of apoptosis onset allows opportunities for preventive controls that ensure high productivity and consistent product quality. Capacitance spectroscopy captures the apoptosis-related cellular properties changes and thus quantifies the percentage of dying cells. This work demonstrated a quantification model that measures the percentage of apoptotic cells using a capacitance spectrometer in an at-line setup. When predicting the independent test set collected from bench-scale bioreactors, the root-mean-squared error of prediction (RMSEP) was 8.8% (equivalent to 9.9% of the prediction range). The predicted culture evolution trajectory aligned with measured values from the flow cytometer. Furthermore, this method alarms cell death onset earlier than the traditional viability test, i.e., trypan blue exclusion test. Comparing to flow cytometry (the traditional early cell death detection method), this method is rapid, simple, and less labor-intensive. Additionally, this at-line setup can be easily transferred between scales (e.g., lab-scale for development to manufacturing-scale), which benefits process transfers between facilities, scale-up, and other process transitions. This article is protected by copyright. All rights reserved.

Off-Gas-Based Soft Sensor for Real-Time Monitoring of Biomass and Metabolism in Chinese Hamster Ovary Cell Continuous Processes in Single-Use Bioreactors

In mammalian cell culture, especially in pharmaceutical manufacturing and research, biomass and metabolic monitoring are mandatory for various cell culture process steps to develop and, finally, control bioprocesses. As a common measure for biomass, the viable cell density (VCD) or the viable cell volume (VCV) is widely used. This study highlights, for the first time, the advantages of using VCV instead of VCD as a biomass depiction in combination with an oxygen-uptake- rate (OUR)-based soft sensor for real-time biomass estimation and process control in single-use bioreactor (SUBs) continuous processes with Chinese hamster ovary (CHO) cell lines. We investigated a series of 14 technically similar continuous SUB processes, where the same process conditions but different expressing CHO cell lines were used, with respect to biomass growth and oxygen demand to calibrate our model. In addition, we analyzed the key metabolism of the CHO cells in SUB perfusion processes by exometabolomic approaches, highlighting the importance of cell-specific substrate and metabolite consumption and production rate qS analysis to identify distinct metabolic phases. Cell-specific rates for classical mammalian cell culture key substrates and metabolites in CHO perfusion processes showed a good correlation to qOUR, yet, unexpectedly, not for qGluc. Here, we present the soft-sensoring methodology we developed for qPyr to allow for the real-time approximation of cellular metabolism and usage for subsequent, in-depth process monitoring, characterization and optimization.

Systematic assessment of process analytical technologies for biologics

The application of process analytical technology (PAT) for biotherapeutic development and manufacturing has been employed owing to technological, economic, and regulatory advantages across the industry. Typically, chromatographic, spectroscopic, and/or mass spectrometric sensors are integrated into upstream and downstream unit operations in in-line, on-line, or at-line fashion to enable real-time monitoring and control of the process. Despite the widespread utility of PAT technologies at various unit operations of the bioprocess, a holistic business value assessment of PAT has not been well addressed in biologics. Thus, in this study, we evaluated PAT technologies based on predefined criteria for their technological attributes such as enablement of better process understanding, control, and high-throughput capabilities; as well as for business attributes such as simplicity of implementation, lead time, and cost reduction. The study involved an industry-wide survey, where input from subject matter industry experts on various PAT tools were collected, assessed, and ranked. The survey results demonstrated on-line liquid Chromatography (LC), in-line Raman, and gas analysis techniques are of high business value especially at the production bioreactor unit operation of upstream processing. In-line variable path-length UV/VIS measurements (VPE), on-line LC, multiangle light scattering (MALS), and automated sampling are of high business value in Protein A purification and polishing steps of the downstream process. We also provide insights, based on our experience in clinical and commercial manufacturing of biologics, into the development and implementation of some of the PAT tools. The results presented in this study are intended to be helpful for the current practitioners of PAT as well as those new to the field to gauge, prioritize and steer their projects for success.

Practical monitoring technologies for cells and substrates in biomanufacturing

Precise control over bioreactor operation is desired for optimal productivity and product quality, and there is an increased drive to automation in biomanufacturing. All of these goals require sensors, not only of the basic parameters of temperature, pH, and dissolved oxygen, but of the biomass and substrate concentrations, which directly determine the outcome of the bioprocess. While there are many innovative sensing concepts for biomass and substrate concentrations, this review focuses on sensors that are in-line with the bioreactor, providing data continuously without the removal of sample from the system. The discussion emphasizes the requirements of industry for these sensors, including performance, ease of use, and cost. As the bioeconomy grows, advances in sensing technologies will be needed to achieve the automation of the future for a wider array of bioreactors.

Taking the pulse of bioprocesses: at-line and in-line monitoring of mammalian cell cultures

Real-time and near real-time monitoring of cell culture processes are critical to the evolving process analytical technology (PAT) paradigm for upstream bioprocessing. The responses measured from these analytical instruments can enable rapid feedback to perturbations that can otherwise lead to batch failures. Historically, real-time monitoring of bioreactor processes has been relegated to parameters such as pH, dissolved oxygen, and temperature. Other analytical results, such as cell growth and metabolites, are provided through manual daily sampling. In order to reduce sample error and increase throughput, real-time and near real-time instruments have been developed. Here we discuss recent advances in these technologies. This article aims to focus on other developing at-line and in-line technologies that enable monitoring of bioreactor processes, including dielectric spectroscopy, NIR, off-gas spectrometry, integrated at-line HPLC, and nanofluidic devices for monitoring cell growth and health, metabolites, titer, and product quality.

Process analytics 4.0: A paradigm shift in rapid analytics for biologics development

Analytical testing of product quality attributes and process parameters during the biologics development (Process analytics) has been challenging due to the rapid growth of biomolecules with complex modalities to support unmet therapeutic needs. Thus, the expansion of the process analytics tool box for rapid analytics with the deployment of cutting-edge technologies and cyber-physical systems is a necessity. We introduce the term, Process Analytics 4.0; which entails not only technology aspects such as process analytical technology (PAT), assay automation, and high-throughput analytics, but also cyber-physical systems that enable data management, visualization, augmented reality, and internet of things (IoT) infrastructure for real time analytics in process development environment. This review is exclusively focused on dissecting high-level features of PAT, automation, and data management with some insights into the business aspects of implementing during process analytical testing in biologics process development. Significant technological and business advantages can be gained with the implementation of digitalization, automation, and real time testing. A systematic development and employment of PAT in process development workflows enable real time analytics for better process understanding, agility, and sustainability. Robotics and liquid handling workstations allow rapid assay and sample preparation automation to facilitate high-throughput testing of attributes and molecular properties which are otherwise challenging to monitor with PAT tools due to technological and business constraints. Cyber-physical systems for data management, visualization, and repository must be established as part of Process Analytics 4.0 framework. Furthermore, we review some of the challenges in implementing these technologies based on our expertise in process analytics for biopharmaceutical drug substance development.

Online monitoring of hiPSC expansion and hepatic differentiation in 3D culture by dielectric spectroscopy

Hepatocyte-like cells derived from human-induced pluripotent stem cells (hiPSC-HLC) are expected to have important applications in drug screening and regenerative medicine. However, hiPSC-HLC are difficult to produce on a large-scale to obtain relevant numbers for such applications. The aim of this study was to implement a novel integrated strategy for scalable production of hiPSC-HLC and demonstrate the applicability of dielectric spectroscopy to monitor hiPSC expansion/differentiation processes. We cultured hiPSC as three-dimensional (3D) aggregates in stirred-tank bioreactors (STB) operated in perfusion with an in situ capacitance probe. Dissolved oxygen concentration and dilution rate were controlled along the process and after 5 days of cell expansion, the hepatic differentiation was integrated in sequential steps for 28 days. The hiPSC were able to grow as 3D aggregates and the expression of hepatic markers and albumin production after differentiation confirmed that hepatocyte differentiation improved when compared to 2D culture. These hiPSC-HLC exhibited functional characteristics of hepatocytes including glycogen storage and drug metabolization capacity. Our results also show a good correlation between the cell permittivity measured online and the aggregate biovolume measured by standard offline methods, demonstrating for the first time the potential of dielectric spectroscopy to monitor hiPSC expansion and differentiation in STB.

Cultivating Multidisciplinarity: Manufacturing and Sensing Challenges in Cultured Meat Production

Meat cultivation via cellular agriculture holds great promise as a method for future food production. In theory, it is an ideal way of meat production, humane to the animals and sustainable for the environment, while keeping the same taste and nutritional values as traditional meat and having additional benefits such as controlled fat content and absence of antibiotics and hormones used in the traditional meat industry. However, in practice, there is still a number of challenges, such as those associated with the upscale of cultured meat (CM). CM food safety monitoring is a necessary factor when envisioning both the regulatory compliance and consumer acceptance. To achieve this, a multidisciplinary approach is necessary. This includes extensive development of the sensitive and specific analytical devices i.e., sensors to enable reliable food safety monitoring throughout the whole future food supply chain. In addition, advanced monitoring options can help in the further optimization of the meat cultivation which may reduce the currently still high costs of production. This review presents an overview of the sensor monitoring options for the most relevant parameters of importance for meat cultivation. Examples of the various types of sensors that can potentially be used in CM production are provided and the options for their integration into bioreactors, as well as suggestions on further improvements and more advanced integration approaches. In favor of the multidisciplinary approach, we also include an overview of the bioreactor types, scaffolding options as well as imaging techniques relevant for CM research. Furthermore, we briefly present the current status of the CM research and related regulation, societal aspects and challenges to its upscaling and commercialization.

High density bioprocessing of human pluripotent stem cells by metabolic control and in silico modeling

To harness the full potential of human pluripotent stem cells (hPSCs) we combined instrumented stirred tank bioreactor (STBR) technology with the power of in silico process modeling to overcome substantial, hPSC‐specific hurdles toward their mass production. Perfused suspension culture (3D) of matrix‐free hPSC aggregates in STBRs was applied to identify and control process‐limiting parameters including pH, dissolved oxygen, glucose and lactate levels, and the obviation of osmolality peaks provoked by high density culture. Media supplements promoted single cell‐based process inoculation and hydrodynamic aggregate size control. Wet lab‐derived process characteristics enabled predictive in silico modeling as a new rational for hPSC cultivation. Consequently, hPSC line‐independent maintenance of exponential cell proliferation was achieved. The strategy yielded 70‐fold cell expansion in 7 days achieving an unmatched density of 35 × 10⁶ cells/mL equivalent to 5.25 billion hPSC in 150 mL scale while pluripotency, differentiation potential, and karyotype stability was maintained. In parallel, media requirements were reduced by 75% demonstrating the outstanding increase in efficiency. Minimal input to our in silico model accurately predicts all main process parameters; combined with calculation‐controlled hPSC aggregation kinetics, linear process upscaling is also enabled and demonstrated for up to 500 mL scale in an independent bioreactor system. Thus, by merging applied stem cell research with recent knowhow from industrial cell fermentation, a new level of hPSC bioprocessing is revealed fueling their automated production for industrial and therapeutic applications.

Implementation of QbD strategies in the inoculum expansion of a mAb production process

The quality by design approach was introduced to the biopharmaceutical industry over 15 years ago. This principle is widely implemented in the characterization of monoclonal antibody production processes. Anyway, the early process phase, namely the inoculum expansion, was not yet investigated and characterized for most processes. In order to increase the understanding of early process parameter interactions and their influence on the later production process, a risk assessment followed by a design of experiments approach was conducted. The DoE included the critical parameters methotrexate (MTX) concentration, initial passage viable cell density and passage duration. Multivariate data analysis led to mathematical regression models and the establishment of a designated design space for the studied parameters. It was found that the passage duration as well as the initial viable cell density for each passage during the inoculum expansion have severe effects on the growth rate and viability of the early process phase. Furthermore, the variations during the inoculum expansion directly influenced the production process responses. This carry-over of factor effects highlights the crucial impact of early process failures and the importance of process analysis and control during the first part of mAb production processes.

Monitoring and control of E. coli cell integrity

Soluble expression of recombinant proteins in E. coli is often done by translocation of the product across the inner membrane (IM) into the periplasm, where it is retained by the outer membrane (OM). While the integrity of the IM is strongly coupled to viability and impurity release, a decrease in OM integrity (corresponding to increased "leakiness") leads to accumulation of product in the extracellular space, strongly impacting the downstream process. Whether leakiness is desired or not, differential monitoring and control of IM and OM integrity are necessary for an efficient E. coli bioprocess in compliance with the guidelines of Quality by Design and Process Analytical Technology. In this review, we give an overview of relevant monitoring tools, summarize the research on factors affecting E. coli membrane integrity and provide a brief discussion on how the available monitoring technology can be implemented in real-time control of E. coli cultivations.

Control of Specific Growth Rate in Fed-Batch Bioprocesses: Novel Controller Design for Improved Noise Management

Accurate control of the specific growth rate (µ) of microorganisms is dependent on the ability to quantify the evolution of biomass reliably in real time. Biomass concentration can be monitored online using various tools and methods, but the obtained signal is often very noisy and unstable, leading to inaccuracies in the estimation of μ. Furthermore, controlling the growth rate is challenging as the process evolves nonlinearly and is subject to unpredictable disturbances originating from the culture’s metabolism. In this work, a novel feedforward-feedback controller logic is presented to counter the problem of noise and oscillations in the control variable and to address the exponential growth dynamics more effectively. The controller was tested on fed-batch cultures of Kluyveromyces marxianus, during which μ was estimated in real time from online biomass concentration measurements obtained with dielectric spectroscopy. It is shown that the specific growth rate can be maintained at different setpoint values with an average root mean square control error of 23 ± 6%.

Development of Novel Bioreactor Control Systems Based on Smart Sensors and Actuators

Bioreactors of various forms have been widely used in environmental protection, healthcare, industrial biotechnology, and space exploration. Robust demand in the field stimulated the development of novel designs of bioreactor geometries and process control strategies and the evolution of the physical structure of the control system. After the introduction of digital computers to bioreactor process control, a hierarchical structure control system (HSCS) for bioreactors has become the dominant physical structure, having high efficiency and robustness. However, inherent drawbacks of the HSCS for bioreactors have produced a need for a more consolidated solution of the control system. With the fast progress in sensors, machinery, and information technology, the development of a flat organizational control system (FOCS) for bioreactors based on parallel distributed smart sensors and actuators may provide a more concise solution for process control in bioreactors. Here, we review the evolution of the physical structure of bioreactor control systems and discuss the properties of the novel FOCS for bioreactors and related smart sensors and actuators and their application circumstances, with the hope of further improving the efficiency, robustness, and economics of bioprocess control.