On-line biomass monitoring of CHO perfusion culture with scanning dielectric spectroscopy

2PP-Hydrogel Covered Electrodes to Compensate for Media Effects in the Determination of Biomass in a Capillary Wave Micro Bioreactor

Microbioreactors increase information output in biopharmaceutical screening applications because they can be operated in parallel without consuming large quantities of the pharmaceutical formulations being tested. A capillary wave microbioreactor (cwMBR) has recently been reported, allowing cost-efficient parallelization in an array that can be activated for mixing as a whole. Although impedance spectroscopy can directly distinguish between dead and viable cells, the monitoring of cells in suspension within bioreactors is challenging because the signal is influenced by the potentially varying properties of the culture medium. In order to address this challenge, an impedance sensor consisting of two sets of microelectrodes in a cwMBR is presented. Only one set of electrodes was covered by a two-photon cross-linked hydrogel to become insensitive to the influence of cells while remaining sensitive to the culture medium. With this impedance sensor, the biomass of Saccharomyces cerevisiae could be measured in a range from 1 to 20 g L-1. In addition, the sensor can compensate for a change in the conductivity of the suspension of 5 to 15 mS cm-1. Moreover, the two-photon cross-linking of hydroxyethyl starch methacrylate hydrogel, which has been studied in detail, recommends itself for even much broader sensing applications in miniaturized bioreactors and biosensors.

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.

Influence of cell specific parameters in a dielectric spectroscopy conversion model used to monitor viable cell density in bioreactors

In the biopharmaceutical industry, the use of mammalian cells to produce therapeutic proteins is becoming increasingly widespread. Monitoring of these cultures via different analysis techniques is essential to ensure a good quality product while respecting good manufacturing practice (GMP) regulations. Process Analytical Technologies (PAT) tools provide real-time measurements of the physiological state of the culture and enable process automation. Dielectric spectroscopy is a PAT that can be used to monitor the viable cell concentration (VCC) of living cells after processing raw permittivity data. Several modeling approaches exist and estimate biomass with different accuracy. The accuracy of the Cole-Cole and Maxwell Wagner's equations are studied here in the determination of the VCC and cell radius in Chinese hamster ovary (CHO) culture. A sensitivity analysis performed on the parameters entering the equations highlighted the importance of the cell specific parameters such as internal conductivity (σi ) and membrane capacitance (Cm ) in the accuracy of the estimation of VCC and cell radius. The most accurate optimization method found to improve the accuracy involves in-process adjustments of Cm and σi in the model equations with samplings from the bioreactor. This combination of offline and in situ data improved the estimation precision of the VCC by 69% compared to a purely mechanistic model without offline adjustments.

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.

Modern Sensor Tools and Techniques for Monitoring, Controlling, and Improving Cell Culture Processes

The growing biopharmaceutical industry has reached a level of maturity that allows for the monitoring of numerous key variables for both process characterization and outcome predictions. Sensors were historically used in order to maintain an optimal environment within the reactor to optimize process performance. However, technological innovation has pushed towards on-line in situ continuous monitoring of quality attributes that could previously only be estimated off-line. These new sensing technologies when coupled with software models have shown promise for unique fingerprinting, smart process control, outcome improvement, and prediction. All this can be done without requiring invasive sampling or intervention on the system. In this paper, the state-of-the-art sensing technologies and their applications in the context of cell culture monitoring are reviewed with emphasis on the coming push towards industry 4.0 and smart manufacturing within the biopharmaceutical sector. Additionally, perspectives as to how this can be leveraged to improve both understanding and outcomes of cell culture processes are discussed.

Two-methods approach to follow up biomass by impedance spectroscopy: Bacillus thuringiensis fermentations as a study model

Impedance spectroscopy is used for the characterization of electrochemical systems as well as for the monitoring of bioprocesses. However, the data obtained using this technique allow multiple interpretations, depending on the methodology implemented. Hence, it is necessary to establish a robust methodology to reliably follow-up biomass in fermentations. In the present work, two methodological approaches, mainly used for the characterization of electrochemical systems, were employed to characterize and determine a frequency that allows the monitoring of biomass in Bacillus thuringiensis fermentations by impedance spectroscopy. The first approach, based on a conventional analysis, revealed a single distribution with a characteristic frequency of around 2 kHz. In contrast, the second approach, based on the distribution of relaxation times, gave three distributions (A, B, and C). The C distribution, found near 9 kHz, was more related to the microbial biomass than the distribution at 2 kHz using the equivalent circuits. The time course of the B. thuringiensis fermentation was followed; bacilli, spores, glucose, and acid and base consumption for pH were determined out of line; and capacitance at 9 kHz was monitored. The correlation between the time course data and the capacitance profile indicated that the monitoring of B. thuringiensis at 9 kHz mainly corresponds to extracellular activity and, in a second instance, to the cellular concentration. These results show that it is necessary to establish a robust and reliable methodology to monitor fermentation processes by impedance spectroscopy, and the distribution of relaxation times was more appropriate. KEY POINTS: • Application of impedance spectroscopy for bioprocess monitoring • Low-frequency monitoring of biomass in fermentations • Analysis of impedance data by two methodological approaches.

On-line monitoring of industrial interest Bacillus fermentations, using impedance spectroscopy

Impedance spectroscopy is a technique used to characterize electrochemical systems, increasing its applicability as well to monitor cell cultures. During their growth, Bacillus species have different phases which involve the production and consumption of different metabolites, culminating in the cell differentiation process that allows the generation of bacterial spores. In order to use impedance spectroscopy as a tool to monitor industrial interest Bacillus cultures, we conducted batch fermentations of Bacillus species such as B. subtilis, B. amyloliquefaciens, and B. licheniformis coupled with this technique. Each fermentation was characterized by the scanning of 50 frequencies between 0.5 and 5 MHz every 30 min. Pearson's correlation between impedance and phase angle profiles (obtained from each frequency scanned) with the kinetic profiles of each strain allowed the selection of fixed frequencies of 0.5, 1.143, and 1.878 MHz to follow-up of the fermentations of B. subtilis, B. amyloliquefaciens and B. licheniformis, respectively. Dielectric profiles of impedance, phase angle, reactance, and resistance obtained at the fixed frequency showed consistent changes with exponential, transition, and spore release phases.

Cole-Cole modeling of real-time capacitance data for estimation of cell physiological properties in recombinant Escherichia coli cultivation

Real-time estimation of physiological properties of the cell during recombinant protein production would ensure enhanced process monitoring. In this study, we explored the application of dielectric spectroscopy to track the fed-batch phase of recombinant Escherichia coli cultivation for estimating the physiological properties, viz. cell diameter and viable cell concentration (VCC). The scanning capacitance data from the dielectric spectroscopy were pre-processed using moving average (MA). Later, it was modelled through a nonlinear theoretical Cole-Cole model and further solved using a global evolutionary genetic algorithm (GA). The parameters obtained from the GA were further applied for the estimation of the aforementioned physiological properties. The offline cell diameter and cell viability data were obtained from particle size analyzer and flow cytometry measurements to validate the Cole-Cole model. The offline VCC was calculated from the cell viability % from flow cytometry data and dry cell weight concentration (DCW). The Cole-Cole model predicted the cell diameter and VCC with an error of 1.03% and 7.72%, respectively. The proposed approach can enable the operator to take real-time process decisions in order to achieve desired productivity and product quality. This article is protected by copyright. All rights reserved.

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.

Monte Carlo-Based Error Propagation for a More Reliable Regression Analysis across Specific Rates in Bioprocesses

During process development, bioprocess data need to be converted into applicable knowledge. Therefore, it is crucial to evaluate the obtained data under the usage of transparent and reliable data reduction and correlation techniques. Within this contribution, we show a generic Monte Carlo error propagation and regression approach applied to two different, industrially relevant cultivation processes. Based on measurement uncertainties, errors for cell-specific growth, uptake, and production rates were determined across an evaluation chain, with interlinked inputs and outputs. These uncertainties were subsequently included in regression analysis to derive the covariance of the regression coefficients and the confidence bounds for prediction. The usefulness of the approach is shown within two case studies, based on the relations across biomass-specific rate control limits to guarantee high productivities in E. coli, and low lactate formation in a CHO cell fed-batch could be established. Besides the possibility to determine realistic errors on the evaluated process data, the presented approach helps to differentiate between reliable and unreliable correlations and prevents the wrong interpretations of relations based on uncertain data.

Towards optimization of plant cell detection in suspensions using impedance-based analyses and the unified equivalent circuit model

An improved approach for comparative study of plant cells for long term and continuous monitoring using electrical impedance spectroscopy is demonstrated for tomato and tobacco plant cells (MSK8 and BY2) in suspensions. This approach is based on the locations and magnitudes of defining features in the impedance spectra of the recently reported unified equivalent circuit model. The ultra-wide range (4 Hz to 20 GHz) impedance spectra of the cell lines were measured using custom probes, and were analyzed using the unified equivalent circuit model, highlighting significant negative phase peaks in the ~ 1 kHz to ~ 10 MHz range. These peaks differ between the tomato and tobacco cells, and since they can be easily defined, they can potentially be used as the signal for differentiating between different cell cultures or monitoring them over time. These findings were further analysed, showing that ratios relating the resistances of the media and the resistance of the cells define the sensitivity of the method, thus affecting its selectivity. It was further shown that cell agglomeration is also an important factor in the impedance modeling in addition to the overall cell concentration. These results can be used for optimizing and calibrating electrical impedance spectroscopy-based sensors for long term monitoring of cell lines in suspension for a given specific cell and media types.

A high cell density perfusion process for Modified Vaccinia virus Ankara production: Process integration with inline DNA digestion and cost analysis

By integrating continuous cell cultures with continuous purification methods, process yields and product quality attributes have been improved over the last 10 years for recombinant protein production. However, for the production of viral vectors such as Modified Vaccinia virus Ankara (MVA), no such studies have been reported although there is an increasing need to meet the requirements for a rising number of clinical trials against infectious or neoplastic diseases. Here, we present for the first time a scalable suspension cell (AGE1.CR.pIX cells) culture-based perfusion process in bioreactors integrating continuous virus harvesting through an acoustic settler with semi-continuous chromatographic purification. This allowed obtaining purified MVA particles with a space-time yield more than 600% higher for the integrated perfusion process (1.05 × 10¹¹ TCID₅₀ /L_bioreactor /day) compared to the integrated batch process. Without further optimization, purification by membrane-based steric exclusion chromatography resulted in an overall product recovery of 50.5%. To decrease the level of host cell DNA before chromatography, a novel inline continuous DNA digestion step was integrated into the process train. A detailed cost analysis comparing integrated production in batch versus production in perfusion mode showed that the cost per dose for MVA was reduced by nearly one-third using this intensified small-scale process.

Differential Inductive Sensing System for Truly Contactless Measuring of Liquids' Electromagnetic Properties in Tubing

Certain applications require a contactless measurement to eliminate the risk of sensor-induced sample contamination. Examples can be found in chemical process control, biotechnology or medical technology. For instance, in critically ill patients requiring renal replacement therapy, continuous in-line monitoring of blood conductivity as a measure for sodium should be considered. A differential inductive sensing system based on a differential transformer using a specific flow chamber has already proven suitable for this application. However, since the blood in renal replacement therapy is carried in plastic tubing, a direct measurement through the tubing offers a contactless method. Therefore, in this work we present a differential transformer for measuring directly through electrically non-conductive tubing by winding the tube around the ferrite core of the transformer. Here, the dependence of the winding type and the number of turns of the tubing on the sensitivity has been analyzed by using a mathematical model, simulations and experimental validation. A maximum sensitivity of 364.9 mV/mol/L is measured for radial winding around the core. A longitudinal winding turns out to be less effective with 92.8 mV/mol/L. However, the findings prove the ability to use the differential transformer as a truly contactless sensing system.

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.

Raman spectroscopic based chemometric models to support a dynamic capacitance based cell culture feeding strategy

Multiple process analytical technology (PAT) tools are now being applied in tandem for cell culture. Research presented used two in-line probes, capacitance for a dynamic feeding strategy and Raman spectroscopy for real-time monitoring. Data collected from eight batches at the 15,000 L scale were used to develop process models. Raman spectroscopic data were modelled using Partial Least Squares (PLS) by two methods-(1) use of the full dataset and (2) split the dataset based on the capacitance feeding strategy. Root mean square error of prediction (RMSEP) for the first model method of capacitance was 1.54 pf/cm and the second modelling method was 1.40 pf/cm. The second Raman method demonstrated results within expected process limits for capacitance and a 0.01% difference in total nutrient feed compared to the capacitance probe. Additional variables modelled using Raman spectroscopy were viable cell density (VCD), viability, average cell diameter, and viable cell volume (VCV).

Multivariate data analysis of capacitance frequency scanning for online monitoring of viable cell concentrations in small-scale bioreactors

Viable cell concentration (VCC) is one of the most important process attributes during mammalian cell cultivations. Current state-of-the-art measurements of VCC comprise offline methods which do not allow for continuous process data. According to the FDA's process analytical technology initiative, process monitoring and control should be applied to gain process understanding and to ensure high product quality. In this work, the use of an inline capacitance probe to monitor online VCCs of a mammalian CHO cell culture process in small-scale bioreactors (250 mL) was investigated. Capacitance sensors using single frequency are increasingly common for biomass monitoring. However, the single-frequency signal corresponds to the cell polarization that represents the viable cell volume. Therefore single-frequency measurements are dependent on cell diameter changes. Measuring the capacitance across various frequencies (frequency scanning) can provide information about the VCC and cope with changing cell diameter. Applying multivariate data analysis on the frequency scanning data successfully enabled direct online monitoring of VCCs in this study. The multivariate model was trained with data from 5 standard cultivations. The model provided a prediction of VCCs with relative errors from 5.5 to 11%, which is a good agreement with the acceptance criterion based on the offline reference method accuracy (approximately 10% relative error) and strongly improved compared with single-frequency results (16 to 23% relative error). Furthermore, robustness trials were conducted to demonstrate the model's predictive ability under challenging conditions. The process deviations in regard to dilution steps and feed variations were detected immediately in the online prediction of the VCC with relative errors between 6.7 and 13.2%. Thus in summary, the presented method on capacitance frequency scanning demonstrates its suitability for process monitoring and control that can save batches, time, and cost. Graphical abstract.

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

In 2004, the FDA published a guideline to implement process analytical technologies (PAT) in biopharmaceutical processes for process monitoring to gain process understanding and for the control of important process parameters. Viable cell concentration (VCC) is one of the most important key performance indicator (KPI) during mammalian cell cultivation processes. Commonly, this is measured offline. In this work, we demonstrated the comparability and scalability of linear regression models derived from online capacitance measurements. The linear regressions were used to predict the VCC and other familiar offline biomass indicators, like the viable cell volume (VCV) and the wet cell weight (WCW), in two different industrially relevant CHO cell culture processes (Process A and Process B). Therefore, different single-use bioreactor scales (50–2000 L) were used to prove feasibility and scalability of the in-line sensor integration. Coefficient of determinations of 0.79 for Process A and 0.99 for Process B for the WCW were achieved. The VCV was described with high coefficients of determination of 0.96 (Process A) and 0.98 (Process B), respectively. In agreement with other work from the literature, the VCC was only described within the exponential growth phase, but resulting in excellent coefficients of determination of 0.99 (Process A) and 0.96 (Process B), respectively. Monitoring these KPIs online using linear regression models appeared to be scale-independent, enabled deeper process understanding (e.g. here demonstrated in monitoring, the feeding profile) and showed the potential of this method for process control.

Trends in Process Analytical Technology: Present State in Bioprocessing

Process analytical technology (PAT), the regulatory initiative for incorporating quality in pharmaceutical manufacturing, is an area of intense research and interest. If PAT is effectively applied to bioprocesses, this can increase process understanding and control, and mitigate the risk from substandard drug products to both manufacturer and patient. To optimize the benefits of PAT, the entire PAT framework must be considered and each elements of PAT must be carefully selected, including sensor and analytical technology, data analysis techniques, control strategies and algorithms, and process optimization routines. This chapter discusses the current state of PAT in the biopharmaceutical industry, including several case studies demonstrating the degree of maturity of various PAT tools. Graphical Abstract Hierarchy of QbD components.

High level extracellular production of recombinant human interferon alpha 2b in glycoengineered Pichia pastoris: culture medium optimization, high cell density cultivation and biological characterization

AIMS

The present study was aimed at design of experiments (DoE)- and artificial intelligence-based culture medium optimization for high level extracellular production of a novel recombinant human interferon alpha 2b (huIFNα2b) in glycoengineered Pichia pastoris and its characterization.

METHODS AND RESULTS

The artificial neural network-genetic algorithm model exhibited improved huIFNα2b production and better predictability compared to response surface methodology. The optimized medium exhibited a fivefold increase in huIFNα2b titre compared to the complex medium. A maximum titre of huIFNα2b (436 mg l^-1 ) was achieved using the optimized medium in the bioreactor. Real-time capacitance data from dielectric spectroscopy were utilized to model the growth kinetics with unstructured models. Biological characterization by antiproliferative assay proved that the purified recombinant huIFNα2b was biologically active, exhibiting growth inhibition on breast cancer cell line.

CONCLUSIONS

Culture medium optimization resulted in enhanced production of huIFNα2b in glycoengineered P. pastoris at both shake flask and bioreactor level. The purified huIFNα2b was found to be N-glycosylated and biologically active.

SIGNIFICANCE AND IMPACT OF THE STUDY

DoE-based medium optimization strategy significantly improved huIFNα2b production. The antiproliferative activity of huIFNα2b substantiates its potential scope for application in cancer therapy.

Control of IgG glycosylation by in situ and real-time estimation of specific growth rate of CHO cells cultured in bioreactor

The cell-specific growth rate (µ) is a critical process parameter for antibody production processes performed by animal cell cultures, as it describes the cell growth and reflects the cell physiological state. When there are changes in these parameters, which are indicated by variations of µ, the synthesis and the quality of antibodies are often affected. Therefore, it is essential to monitor and control the variations of µto assure the antibody production and achieve high product quality. In this study, a novel approach for on-line estimation of µ was developed based on the process analytical technology initiative by using an in situ dielectric spectroscopy. Critical moments, such as significant µ decreases, were successfully detected by this method, in association with changes in cell physiology as well as with an accumulation of nonglycosylated antibodies. Thus, this method was used to perform medium renewals at the appropriate time points, maintaining the values of µ close to its maximum. Using this method, we demonstrated that the physiological state of cells remained stable, the quantity and the glycosylation quality of antibodies were assured at the same time, leading to better process performances compared with the reference feed-harvest cell cultures carried out by using off-line nutrient measurements.

Label free process monitoring of 3D bioprinted engineered constructs via dielectric impedance spectroscopy

Biofabrication processes can affect biological quality attributes of encapsulated cells within constructs. Currently, assessment of the fabricated constructs is performed offline by subjecting the constructs to destructive assays that require staining and sectioning. This drawback limits the translation of biofabrication processes to industrial practice. In this work, we investigate the dielectric response of viable cells encapsulated in bioprinted 3D hydrogel constructs to an applied alternating electric field as a label-free non-destructive monitoring approach. The relationship between β-dispersion parameters (permittivity change-Δε, Cole-Cole slope factor-α, critical polarization frequency-f _c ) over the frequency spectrum and critical cellular quality attributes are investigated. Results show that alginate constructs containing a higher number of viable cells (human adipose derived stem cells-hASC and osteosarcoma cell line-MG63) were characterized by significantly higher Δε and α (both p < 0.05). When extended to bioprinting, results showed that changes in hASC proliferation and viability in response to changes in critical bioprinting parameters (extrusion pressure, temperature, processing time) significantly affected ∆ε, α, and f _c . We also demonstrated monitoring of hASC distribution after bioprinting and changes in proliferation over time across the cross-section of a bioprinted medial knee meniscus construct. The trends in ∆ε over time were in agreement with the alamarBlue assay results for the whole construct, but this measurement approach provided a localized readout on the status of encapsulated cells. The findings of this study support the use of dielectric impedance spectroscopy as a label-free and non-destructive method to characterize the critical quality attributes of bioprinted constructs.

Dielectric Spectroscopy and Optical Density Measurement for the Online Monitoring and Control of Recombinant Protein Production in Stably Transformed Drosophila melanogaster S2 Cells

The production of recombinant proteins in bioreactors requires real-time process monitoring and control to increase process efficiency and to meet the requirements for a comprehensive audit trail. The combination of optical near-infrared turbidity sensors and dielectric spectroscopy provides diverse system information because different measurement principles are exploited. We used this combination of techniques to monitor and control the growth and protein production of stably transformed Drosophila melanogaster S2 cells expressing antimicrobial proteins. The in situ monitoring system was suitable in batch, fed-batch and perfusion modes, and was particularly useful for the online determination of cell concentration, specific growth rate (µ) and cell viability. These data were used to pinpoint the optimal timing of the key transitional events (induction and harvest) during batch and fed-batch cultivation, achieving a total protein yield of ~25 mg at the 1-L scale. During cultivation in perfusion mode, the OD₈₈₀ signal was used to control the bleed line in order to maintain a constant cell concentration of 5 × 10⁷ cells/mL, thus establishing a turbidostat/permittistat culture. With this setup, a five-fold increase in productivity was achieved and 130 mg of protein was recovered after 2 days of induced perfusion. Our results demonstrate that both sensors are suitable for advanced monitoring and integration into online control strategies.

Fed-Batch Production of Bacterial Ghosts Using Dielectric Spectroscopy for Dynamic Process Control

The Bacterial Ghost (BG) platform technology evolved from a microbiological expression system incorporating the ϕX174 lysis gene E. E-lysis generates empty but structurally intact cell envelopes (BGs) from Gram-negative bacteria which have been suggested as candidate vaccines, immunotherapeutic agents or drug delivery vehicles. E-lysis is a highly dynamic and complex biological process that puts exceptional demands towards process understanding and control. The development of a both economic and robust fed-batch production process for BGs required a toolset capable of dealing with rapidly changing concentrations of viable biomass during the E-lysis phase. This challenge was addressed using a transfer function combining dielectric spectroscopy and soft-sensor based biomass estimation for monitoring the rapid decline of viable biomass during the E-lysis phase. The transfer function was implemented to a feed-controller, which followed the permittivity signal closely and was capable of maintaining a constant specific substrate uptake rate during lysis phase. With the described toolset, we were able to increase the yield of BG production processes by a factor of 8–10 when compared to currently used batch procedures reaching lysis efficiencies >98%. This provides elevated potentials for commercial application of the Bacterial Ghost platform technology.

Metabolic Control in Mammalian Fed-Batch Cell Cultures for Reduced Lactic Acid Accumulation and Improved Process Robustness

Biomass and cell-specific metabolic rates usually change dynamically over time, making the "feed according to need" strategy difficult to realize in a commercial fed-batch process. We here demonstrate a novel feeding strategy which is designed to hold a particular metabolic state in a fed-batch process by adaptive feeding in real time. The feed rate is calculated with a transferable biomass model based on capacitance, which changes the nutrient flow stoichiometrically in real time. A limited glucose environment was used to confine the cell in a particular metabolic state. In order to cope with uncertainty, two strategies were tested to change the adaptive feed rate and prevent starvation while in limitation: (i) inline pH and online glucose concentration measurement or (ii) inline pH alone, which was shown to be sufficient for the problem statement. In this contribution, we achieved metabolic control within a defined target range. The direct benefit was two-fold: the lactic acid profile was improved and pH could be kept stable. Multivariate Data Analysis (MVDA) has shown that pH influenced lactic acid production or consumption in historical data sets. We demonstrate that a low pH (around 6.8) is not required for our strategy, as glucose availability is already limiting the flux. On the contrary, we boosted glycolytic flux in glucose limitation by setting the pH to 7.4. This new approach led to a yield of lactic acid/glucose (Y L/G) around zero for the whole process time and high titers in our labs. We hypothesize that a higher carbon flux, resulting from a higher pH, may lead to more cells which produce more product. The relevance of this work aims at feeding mammalian cell cultures safely in limitation with a desired metabolic flux range. This resulted in extremely stable, low glucose levels, very robust pH profiles without acid/base interventions and a metabolic state in which lactic acid was consumed instead of being produced from day 1. With this contribution, we wish to extend the basic repertoire of available process control strategies, which will open up new avenues in automation technology and radically improve process robustness in both process development and manufacturing.

On-line monitoring of the aggregate size distribution of Carthamus tinctorius L. cells with multi-frequency capacitance measurements

This study provided an effective methodology for the aggregate size distribution measurement of Carthamus tinctorius L. cells during suspension culture.

Controlling the feed rate of propanol to optimize erythromycin fermentation by on-line capacitance and oxygen uptake rate measurement

The aim of the present study was to optimize the feeding proportion of glucose and propanol for erythromycin biosynthesis by real-time monitoring and exploring its limited ratio by the on-line multi-frequency permittivity measurement. It was found that the capacitance values were sensitive to the variation of biomass concentration and microbial morphology as well as the true state of cell growth. It was most favorable to both cell growth and secondary metabolism to keep the ratio of glucose to propanol at 4.3 (g/g). The specific growth rate calculated by the capacitance measurement correctly and accurately reflected the cell physiological state. An appropriate feed rate of propanol was crucial for cell growth and secondary metabolism, as well as to improve the quality of erythromycin-A. In addition, the erythromycin production titer (10,950 U/mL) was further enhanced by 4 % when the propanol feed was regulated by step-down strategy based on both OUR (oxygen uptake rate) and the on-line monitoring capacitance.

Flexible Bioimpedance Sensor for Label-Free Detection of Cell Viability and Biomass

We introduce a flexible microfluidic bioimpedance sensor that is capable of detecting biomass and cell viability variations in a cell suspension. The sensor is developed on indium tin oxide (ITO) coated polyethylene terephthalate (PET) substrate and is devoid of gold, silicon, PDMS, or glass. In conjugation with a custom built PCB read-out module, the impedance characteristics of a cell suspension can be measured within one minute of sample introduction using liquid volumes less than 5 μL. The portable sensor system occupies very little bench space and has the potential to be developed as a disposable electrical bioimpedance probe for rapid detection of dielectric variations in a biological suspension. The sensor is designed to generate a differential impedance spectra exclusive to a cell suspension with a dual-electrode-pair system. The potential of the sensor to discriminate between live and heat treated Saccharomyces cerevisiae is demonstrated in this study. The disposable sensor along with the distance variation technique is touted to be an inexpensive alternative to some of the existing online disposable biomass detection probes and electrochemical sensors.

Universal Capacitance Model for Real-Time Biomass in Cell Culture

: Capacitance probes have the potential to revolutionize bioprocess control due to their safe and robust use and ability to detect even the smallest capacitors in the form of biological cells. Several techniques have evolved to model biomass statistically, however, there are problems with model transfer between cell lines and process conditions. Errors of transferred models in the declining phase of the culture range for linear models around +100% or worse, causing unnecessary delays with test runs during bioprocess development. The goal of this work was to develop one single universal model which can be adapted by considering a potentially mechanistic factor to estimate biomass in yet untested clones and scales. The novelty of this work is a methodology to select sensitive frequencies to build a statistical model which can be shared among fermentations with an error between 9% and 38% (mean error around 20%) for the whole process, including the declining phase. A simple linear factor was found to be responsible for the transferability of biomass models between cell lines, indicating a link to their phenotype or physiology.

In silico validation procedure for cell volume fraction estimation through dielectric spectroscopy

Dielectric spectroscopy has proved to be a good tool for analyzing the passive electrical properties of biological tissues as well as those of inhomogeneous materials. This technique promises to be a valid alternative to the classical ones based on metabolites to monitor the growth and cell volume fraction of cell cultures in a simple and minimally invasive way. In order to obtain an accurate estimation of the cell volume fraction as a function of the permittivity of the suspension, a simple in silico procedure is proposed. The procedure is designed to perform homogenization from the micro-scale to the macro-scale using simple analytical models and simulation setups hypothesizing the properties of diluted suspension (cell volume fraction less than 0.2). Results obtained show the possibility to overcome some trouble involving the analytical treatment of the cellular shape by considering a sphere with the same permittivity in the quantitative analysis of the cell volume fraction. The entire study is based on computer simulations performed in order to verify the correctness of the procedure. Obtained data are used in a cell volume fraction estimation scenario to show the effectiveness of the procedure.

A novel approach for using dielectric spectroscopy to predict viable cell volume (VCV) in early process development

Online monitoring of viable cell volume (VCV) is essential to the development, monitoring, and control of bioprocesses. The commercial availability of steam-sterilizable dielectricspectroscopy probes has enabled successful adoption of this technology as a key noninvasive method to measure VCV for cell-culture processes. Technological challenges still exist, however. For some cell lines, the technique’s accuracy in predicting the VCV from probepermittivity measurements declines as the viability of the cell culture decreases. To investigate the cause of this decrease in accuracy, divergences in predicted vs. actual VCV measurements were directly related to the shape of dielectric frequency scans collected during a cell culture. The changes in the shape of the beta dispersion, which are associated with changes in cell state, are quantified by applying a novel “area ratio” (AR) metric to frequency-scanning data from the dielectric-spectroscopy probes. The AR metric is then used to relate the shape of the beta dispersion to single-frequency permittivity measurements to accurately predict the offline VCV throughout an entire fed-batch run, regardless of cell state. This work demonstrates the possible feasibility of quantifying the shape of the beta dispersion, determined from frequency-scanning data, for enhanced measurement of VCV in mammalian cell cultures by applying a novel shape-characterization technique. In addition, this work demonstrates the utility of using changes in the shape of the beta dispersion to quantify cell health.

Configuration of bioreactors

Lab-scale stirred-tank bioreactors (0.2-20 l) are used for fundamental research on animal cells and in process development and troubleshooting for large-scale production. In this chapter, different configurations of bioreactor systems are shortly discussed and setting up these different configurations is described. In addition, online measurement and control of bioreactor parameters is described, with special attention to controller settings (PID) and online measurement of oxygen consumption and carbon dioxide production. Finally, methods for determining the oxygen transfer coefficient are described.

Addressing the challenge of optimum polyhydroxyalkanoate harvesting: monitoring real time process kinetics and biopolymer accumulation using dielectric spectroscopy

In this study, dielectric spectroscopy was utilised to evaluate and define the optimum harvesting time for polyhydroxyalkanoates (PHA) production. It is essential to harvest PHA at the optimum time during fermentation for maximum yield, otherwise cells start degrading. Two carbon sources (acetic and butyric acids) were used in laboratory based experiments and a number of samples were measured ex situ for PHA production. The real-time measured capacitance in addition of identifying the cells growth phase, it correlated very well with ex situ measured PHA produced within the cells. The probe has proven to be a useful tool to assess process kinetics, to monitor real-time cell growth, PHA produced and defining the optimum harvesting time.

Label-free hybridoma cell culture quality control by a chip-based impedance flow cytometer

Impedance flow cytometry (IFC) was evaluated as a possible alternative to fluorescence-based methods for on-line quality monitoring of hybridoma cells. Hybridoma cells were cultured at different cell densities and viability was estimated by means of IFC and fluorescence-based flow cytometry (FCM). Cell death was determined by measuring the impedance phase value at high frequency in low conductivity buffer. IFC data correlate well with reference FCM measurements using AnnexinV and 7-AAD staining. Hybridoma cells growing at different densities in cell culture revealed a density-dependent subpopulation pattern. Living cells of high density cultures show reduced impedance amplitudes, indicating particular cellular changes. Dead cell subpopulations become evident in cultures with increasing cell densities. In addition, a novel intermediate subpopulation, which most probably represents apoptotic cells, was identified. These results emphasize the extraordinary sensitivity of high frequency impedance measurements and their suitability for hybridoma cell culture quality control.

Real-time monitoring of adherent Vero cell density and apoptosis in bioreactor processes

This study proposes an easy to use in situ device, based on multi-frequency permittivity measurements, to monitor the growth and death of attached Vero cells cultivated on microporous microcarriers, without any cell sampling. Vero cell densities were on-line quantified up to 10(6) cell mL(-1). Some parameters which could potentially impact Vero cell morphological and physiological states were assessed through different culture operating conditions, such as media formulation or medium feed-harvest during cell growth phase. A new method of in situ cell death detection with dielectric spectroscopy was also successfully implemented. Thus, through permittivity frequency scanning, major rises of the apoptotic cell population in bioreactor cultures were detected by monitoring the characteristic frequency of the cell population, f(c), which is one of the culture dielectric parameters. Both cell density quantification and cell apoptosis detection are strategic information in cell-based production processes as they are involved in major events of the process, such as scale-up or choice of the viral infection conditions. This new application of dielectric spectroscopy to adherent cell culture processes makes it a very promising tool for risk-mitigation strategy in industrial processes. Therefore, our results contribute to the development of Process Analytical Technology in cell-based industrial processes.