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In this study, we developed a method to build Raman calibration models without culture data for cell culture monitoring. First, Raman spectra were collected and then analyzed for the signals of all the mentioned analytes: glucose, lactate, glutamine, glutamate, ammonia, antibody, viable cells, media, and feed agent. Using these spectral data, the specific peak positions and intensities for each factor were detected. Next, according to the design of the experiment method, samples were prepared by mixing the above-mentioned factors. Raman spectra of these samples were collected and were used to build calibration models. Several combinations of spectral pretreatments and wavenumber regions were compared to optimize the calibration model for cell culture monitoring without culture data. The accuracy of the developed calibration model was evaluated by performing actual cell culture and fitting the in-line measured spectra to the developed calibration model. As a result, the calibration model achieved sufficiently good accuracy for the three components, glucose, lactate, and antibody (root mean square errors of prediction, or RMSEP = 0.23, 0.29, and 0.20 g/L, respectively). This study has presented innovative results in developing a culture monitoring method without using culture data, while using a basic conventional method of investigating the Raman spectra of each component in the culture media and then utilizing a design of experiment approach. Graphical Abstract This is a visual representation of the abstract. [ABSTRACT FROM AUTHOR]

Lab-on-a-chip sensing technologies have changed how cell biology research is conducted. This review summarises the progress in the lab-on-a-chip devices implemented for the detection of cellular metabolites. The review is divided into two subsections according to the methods used for the metabolite detection. Each section includes a table which summarises the relevant literature and also elaborates the advantages of, and the challenges faced with that particular method. The review continues with a section discussing the achievements attained due to using lab-on-a-chip devices within the specific context. Finally, a concluding section summarises what is to be resolved and discusses the future perspectives.

ABSTRACT Following the Process Analytical Technology (PAT) of the Food and Drug Administration (FDA), drug manufacturers are encouraged to develop innovative techniques in order to monitor and understand their processes in a better way. Within this framework, it has been demonstrated that Raman spectroscopy coupled with chemometric tools allow to predict critical parameters of mammalian cell cultures in-line and in real time. However, the development of robust and predictive regression models clearly requires many batches in order to take into account inter-batch variability and enhance models accuracy. Nevertheless, this heavy procedure has to be repeated for every new line of cell culture involving many resources. This is why we propose in this paper to develop global regression models taking into account different cell lines. Such models are finally transferred to any culture of the cells involved. This article first demonstrates the feasibility of developing regression models, not only for mammalian cell lines (CHO and HeLa cell cultures), but also for insect cell lines (Sf9 cell cultures). Then global regression models are generated, based on CHO cells, HeLa cells, and Sf9 cells. Finally, these models are evaluated considering a fourth cell line(HEK cells). In addition to suitable predictions of glucose and lactate concentration of HEK cell cultures, we expose that by adding a single HEK-cell culture to the calibration set, the predictive ability of the regression models are substantially increased. In this way, we demonstrate that using global models, it is not necessary to consider many cultures of a new cell line in order to obtain accurate models. Biotechnol. Bioeng. 2017;114: 2550-2559. © 2017 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

In recent years, as a result of the process analytical technology initiative of the US Food and Drug Administration, many different works have been carried out on direct and in situ monitoring of critical parameters for mammalian cell cultures by Raman spectroscopy and multivariate regression techniques. However, despite interesting results, it cannot be said that the proposed monitoring strategies, which will reduce errors of the regression models and thus confidence limits of the predictions, are really optimized. Hence, the aim of this article is to optimize some critical steps of spectroscopic acquisition and data treatment in order to reach a higher level of accuracy and robustness of bioprocess monitoring. In this way, we propose first an original strategy to assess the most suited Raman acquisition time for the processes involved. In a second part, we demonstrate the importance of the interbatch variability on the accuracy of the predictive models with a particular focus on the optical probes adjustment. Finally, we propose a methodology for the optimization of the spectral variables selection in order to decrease prediction errors of multivariate regressions. © 2017 American Institute of Chemical Engineers Biotechnol. Prog., 33:308-316, 2017 [ABSTRACT FROM AUTHOR]

A surface plasmon resonance (SPR)-based assay has been developed in order to quantify the monoclonal antibody (Mab) Trastuzumab within the supernatant of a mammalian cell culture using the ectodomain of FcγRI (CD64) and confirm Mab bioactivity, i.e. binding to its antigen Her2, in a single biosensing experiment. Under partial mass transport limitation, we were able to quantify Mab present in unpurified samples taken throughout the cell culture. While Mab capture on the biosensor surface confirmed the ability of its Fc region to bind to FcγRI, the binding activity of its Fab region was also tested by injecting increasing concentrations of the Mab antigen (Her2). The kinetics of the interactions we recorded from 48 h post transfection until the end of the culture, were superimposable, which highly suggested that the quality attributes of the antibody were conserved throughout the process. This SPR methodology is thus of great interest for atline quality control analysis during Mab production campaign. [ABSTRACT FROM AUTHOR]

In light of the large-scale expansion of human periosteum derived stem cells for the treatment of large bone defects, a multiplate bioreactor system (Pall Integrity Xpansion) in combination with an integrated holographic imaging platform (Ovizio iLine S microscope) was evaluated. The culture process was quantitatively characterized by imaging data, metabolite concentrations and a breakdown of the cell recovery fractions. The resulting cell quality was assessed based on the minimal criteria for mesenchymal stem cells, including viability on cell culture plastic, identity markers and tri-lineage differentiation potential. Additionally, an in vivo bone forming potency assay was used in an ectopic mice model that resulted in compelling bone formation (11.6 ± 3.1% and 12.8 ± 3.3% for the bioreactor and control tissue culture flask condition, respectively). Therefore, it was shown that the bioreactor is able to produce large quantities of cells, while maintaining satisfactory cell quality. [ABSTRACT FROM AUTHOR]

The ability to measure all process variables is of great importance in the field of bioprocess monitoring and control, and continuous, real-time measurements are highly desired. The more complete and real-time the measurements are, the more stable, reproducible, and efficient the process can be, leading to reproducibly high-quality products. This additional information allows the operator to better document the entire process. The process analytical technologies initiative of the US Food and Drug Administration is strongly related to the analysis and control of biopharmaceutical processes. The aim of the initiative is to create processes, generating products of ensured quality by measuring quality-related process variables. The quality of the product is enhanced by a deep understanding of the process, which is enabled by an effective and suitable sensor system. The aim of this review is to provide an overview of current and emerging sensors for bioprocess monitoring. Sensors directly interfaced to bioreactors for measuring important variables from the gas phase, such as oxygen and carbon dioxide concentration, are discussed, as well as sensors for the monitoring of the biomass concentration and morphology and of the changing medium composition. Furthermore, sensor systems are discussed. These involve sensors (especially biosensors) that are not implemented directly inside the bioreactor but rather are used in conjunction with sample-taking systems such as flow injection analysis. A major focus is given to spectroscopic sensors, which are noninvasive and offer interesting options for a simultaneous analysis of various compounds. Since data handling is extremely important for this kind of sensor, chemometrics are also included. Soft sensors are discussed as technology that allows a user to incorporate more process data as it become available. Finally, the current state of disposable sensor technology is presented. These sensors are needed for the growing area of disposable and continuous biomanufacturing. [ABSTRACT FROM AUTHOR]

Raman-based multivariate calibration models have been developed for real-time in situ monitoring of multiple process parameters within cell culture bioreactors. Developed models are generic, in the sense that they are applicable to various products, media, and cell lines based on Chinese Hamster Ovarian (CHO) host cells, and are scalable to large pilot and manufacturing scales. Several batches using different CHO-based cell lines and corresponding proprietary media and process conditions have been used to generate calibration datasets, and models have been validated using independent datasets from separate batch runs. All models have been validated to be generic and capable of predicting process parameters with acceptable accuracy. The developed models allow monitoring multiple key bioprocess metabolic variables, and hence can be utilized as an important enabling tool for Quality by Design approaches which are strongly supported by the U.S. Food and Drug Administration. © 2015 American Institute of Chemical Engineers Biotechnol. Prog., 31:1004-1013, 2015 [ABSTRACT FROM AUTHOR]

Mass spectrometry has been frequently applied to monitor the O2 and CO2 content in the off-gas of animal cell culture fermentations. In contrast to classical mass spectrometry the proton transfer reaction mass spectrometry (PTR-MS) provides additional information of volatile organic compounds by application of a soft ionization technology. Hence, the spectra show less fragments and can more accurately assigned to particular compounds. In order to discriminate between compounds of non-metabolic and metabolic origin cell free experiments and fed-batch cultivations with a recombinant CHO cell line were conducted. As a result, in total eight volatiles showing high relevance to individual cultivation or cultivation conditions could be identified. Among the detected compounds methanethiol, with a mass-to-charge ratio of 49, qualifies as a key candidate in process monitoring due to its strong connectivity to lactate formation. Moreover, the versatile and complex data sets acquired by PTR MS provide a valuable resource for statistical modeling to predict non direct measurable parameters. Hence, partial least square regression was applied to the complete spectra of volatiles measured and important cell culture parameters such as viable cell density estimated ( R2 = 0.86). As a whole, the results of this study clearly show that PTR-MS provides a powerful tool to improve bioprocess-monitoring for mammalian cell culture. Thus, specific volatiles emitted by cells and measured online by the PTR-MS and complex variables gained through statistical modeling will contribute to a deeper process understanding in the future and open promising perspectives to bioprocess control. © 2013 American Institute of Chemical Engineers Biotechnol. Prog., 30:496-504, 2014 [ABSTRACT FROM AUTHOR]

Abstract: In the present study near infrared (NIR) spectroscopy was used to monitor the cultivation of mammalian Chinese hamster ovary (CHO) cells producing a monoclonal antibody in a fed-batch cell culture process. A temperature shift was applied during the cultivation. The cells were incubated at 37°C and 33°C. The Fourier transform near infrared (FT-NIR) multiplex process analyzer spectroscopy was investigated to monitor cultivation variables of the CHO cell culture from 10 independent batches using two channels of the FT-NIR. The measurements were performed on production scale bioreactors of 12,500L. The cell cultures were analyzed with the spectrometer coupled to a transflection sterilizable fiber optic probe inserted into the bioreactors. Multivariate data analysis (MVDA) employing unsupervised principal component analysis (PCA) and partial least squares regression methods (PLS) were applied. PCA demonstrated that 96% of the observed variability was explained by the process trajectory and the inter-batch variability. PCA was found to be a significant tool in identifying batch homogeneity between lots and in detecting abnormal fermentation runs. Seven different cell culture parameters such as osmolality, glucose concentration, product titer, packed cell volume (PCV), integrated viable packed cell volume (ivPCV), viable cell density (VCD), and integrated viable cell count (iVCC) were monitored inline and predicted by NIR. NIR spectra and reference analytics data were computed using control charts to evaluate the monitoring abilities. Control charts of each media component were under control by NIR spectroscopy. The PLS calibration plots offered accurate predictive capabilities for each media. This paper underlines the capability for inline prediction of multiple cultivation variables during bioprocess monitoring. [Copyright &y& Elsevier]

In this study, the application of Raman spectroscopy to the simultaneous quantitative determination of glucose, glutamine, lactate, ammonia, glutamate, total cell density (TCD), and viable cell density (VCD) in a CHO fed-batch process was demonstrated in situ in 3 L and 15 L bioreactors. Spectral preprocessing and partial least squares (PLS) regression were used to correlate spectral data with off-line reference data. Separate PLS calibration models were developed for each analyte at the 3 L laboratory bioreactor scale before assessing its transferability to the same bioprocess conducted at the 15 L pilot scale. PLS calibration models were successfully developed for all analytes bar VCD and transferred to the 15 L scale. © 2012 American Institute of Chemical Engineers Biotechnol. Prog., 2012 [ABSTRACT FROM AUTHOR]

The newly developed in situ oxygen uptake rate (in situ OUR) probe presented in this article is based on the in situ microscope technology platform. It is designed to measure the oxygen uptake rate (OUR) of mammalian cells, an important parameter for metabolic flux analysis, inside a reactor (in situ) and in real-time. The system isolates a known volume of cell culture from the bulk inside the bioreactor, monitors the oxygen consumption over time, and releases the sample again. The sample is mixed during the measurement with a new agitation system to keep the cells in suspension and prevent oxygen concentration gradients. The OUR measurement system also doubles as a standard dissolved oxygen (DO) probe for process monitoring when it is not performing OUR measurements. It can be equipped with two different types of optical sensors (i.e., DO, pH) simultaneously or a conventional polarographic DO-probe (Clark type). This new probe was successfully tested in baby hamster kidney perfusion cell cultures. © 2011 American Institute of Chemical Engineers Biotechnol. Prog., 2012 [ABSTRACT FROM AUTHOR]

Abstract: A silicon-based biosensor chip consisting of an array of amperometric enzyme sensors has been developed for monitoring the concentration of glutamate and glutamine in cell-culture fermentation processes. The glutamate sensor was constructed by immobilising glutamate oxidase, while the glutamine sensor by sequential coupling of glutaminase and glutamate oxidase. The enzymes were immobilised by means of cross-linking with glutaraldehyde on the surface of the patterned platinum thin-film electrodes. The developed biosensors have been electrochemically characterised in solutions with different concentrations of glutamate and glutamine in terms of sensitivity, response time, linear working range and lifetime. A high sensitivity of 96nA/mM and 100nA/mM was registered for the glutamate and glutamine sensors, respectively. The preliminary experiments in cell-culture medium have shown a good correlation between the glutamine and glutamate concentrations measured with the biosensor chip and the commercially available biochemistry analyser. The obtained results demonstrate the feasibility of the realised biosensor chip for monitoring the glutamine and glutamate concentrations in fermentation processes. [Copyright &y& Elsevier]

The article discusses research on the use of Raman spectroscopy for the real time monitoring of mammalian cell culture bioreactors. The model calibration results gathered for various nutrient and metabolite concentrations are cited. A comparison between viable cell counts, total cell counts, and viabilities is presented. The model predictions concluded following the administration of Raman spectra for several values including glutamate, glucose, and lactate are also described.

Since a culture increases in cell number when dividing cells separate into two newborn cells, the fraction of mitotic cells in a growing cell population directly reflects the overall growth behavior of a cell culture. To rapidly assess the effects of growth conditions on the fraction of mitotic cells we have employed an antibody specific for the phosphorylated form of histone H3 for the identification of mitotic cells using flow cytometry. The phosphorylation of histone H3 closely correlates with the chromosomal condensation that accompanies the onset of mitosis, and, therefore, it represents a convenient marker for dividing cells. We have optimized the protocol for the staining of mitotic cells for both Chinese hamster ovary and hybridoma cell cultures. Fluorescence micrographs taken of stained cells show that cells in the various stages of mitosis can be detected based on the morphological characteristics of the chromosomes. The variation in the mitotic cell fraction has been determined throughout the batch growth phases of cultures under different growth conditions. The dynamics of the mitotic index show that balanced growth was never truly reached and that the growth rate is in fact quite variable for these cultures since large variations in the mitotic index are observed. In addition, a large increase in the fraction of mitotic cells just prior to the exponential growth phase for all cultures indicates that they are partially synchronized at the exit from the lag phase. According to a two-staged, age structured population balance model, the mitotic index is directly proportional to the growth rate of a culture. The proportionality constant for this case is shown to be the time required for cells to progress through mitosis. This time is believed to be constant for a particular cell line, as shown by experimental data. Thus, growth rates can be determined solely by measurement of the fraction of cells in mitosis. The mitotic index measurements were then used to calculate the growth in cell number of the cultures, and these simulations accurately reflect observed cell counts. Other simulations also show that changes in cell growth can be predicted before they are reflected in the cell count data. This technique can be used as a sensitive indicator of cell growth and could be useful as a process monitoring technique and for developing better feeding strategies for animal cell cultures. [Copyright &y& Elsevier]

Lab-on-a-chip sensing technologies have changed how cell biology research is conducted. This review summarises the progress in the lab-on-a-chip devices implemented for the detection of cellular metabolites. The review is divided into two subsections according to the methods used for the metabolite detection. Each section includes a table which summarises the relevant literature and also elaborates the advantages of, and the challenges faced with that particular method. The review continues with a section discussing the achievements attained due to using lab-on-a-chip devices within the specific context. Finally, a concluding section summarises what is to be resolved and discusses the future perspectives. [ABSTRACT FROM AUTHOR]