Real-time update of calibration model for better monitoring of batch processes using spectroscopy

In order to reduce the large calibration matrix usually required for calibrating multiwavelength optical sensors, a simple algorithm based on the addition in process of new standards is proposed. A small calibration model, based on 14 standards, is periodically updated by spectra collected on-line during fermentation operation. Concentrations related to these spectra are reconciled into best-estimated values, by considering carbon and oxygen balances. Using this method, fructose, acetate, and gluconacetan were monitored during batch fermentations of Gluconacetobacter xylinus 12281 using mid-infrared spectroscopy. It is shown that this algorithm compensates for noncalibrated events such as production or consumption of by-products. The standard error of prediction (SEP) values were 0.99, 0.10, and 0.90 g/L for fructose, acetate, and gluconacetan, respectively. By contrast, without an updating of the calibration model, the SEP values were 2.46, 0.92, and 1.04 g/L for fructose, acetate, and gluconacetan, respectively. Using only 14 standards, it was therefore possible to approach the performance of an 88-standard-based calibration model having SEP values of 1.11, 0.37, and 0.79 g/L for fructose, acetate, and gluconacetan, respectively. Therefore, the proposed algorithm is a valuable approach to reduce the calibration time of multiwavelength optical sensors.     

Secretion of the heat shock proteins HSP70 and HSC70 by baby hamster kidney (BHK‐21) cells

The HSPs (heat‐shock proteins) of the 70‐kDa family, the constitutively expressed HSC70 (cognate 70‐kDa heat‐shock protein) and the stress‐inducible HSP70 (stress‐inducible 70‐kDa heat‐shock protein), have been reported to be actively secreted by various cell types. The mechanisms of the release of these HSPs are obscure, since they possess no consensus secretory signal sequence. We showed that baby hamster kidney (BHK‐21) cells released HSP70 and HSC70 in a serum‐free medium and that this process was the result of an active secretion of HSPs rather than the non‐specific release of the proteins due to cell death. It was found that the secretion of HSP70 and HSC70 is independent of de novo protein synthesis. BFA (Brefeldin A) did not inhibit the basal secretion of HSPs, indicating that the secretion of HSP70 and HSC70 from cells occurs by a non‐classical pathway. Exosomes did not contribute to the secretion of HSP70 and HSC70 by cells. MBC (methyl‐β‐cyclodextrin), a substance that disrupts the lipid raft organization, considerably reduced the secretion of both HSPs, indicating that lipid rafts are involved in the secretion of HSP70 and HSC70 by BHK‐21 cells. The results suggest that HSP70 and HSC70 are actively secreted by BHK‐21 cells in a serum‐free medium through a non‐classical pathway in which lipid rafts play an important role.     

Generic Raman‐based calibration models enabling real‐time monitoring of cell culture bioreactors

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     

Intrinsic fluorescence‐based at situ soft sensor for monitoring monoclonal antibody aggregation

Intrinsic fluorescence spectroscopy, in conjunction with partial least squares regression (PLSR), was investigated as a potential technique for online quality control and quantitative monitoring of Immunoglobulin G (IgG) aggregation that occurs following exposure to conditions that emulate those that can occur during protein downstream processing. Initially, the impact of three stress factors (temperature, pH, and protein concentration) on the degree of aggregation determined using size exclusion chromatography data, was investigated by performing a central composite designexperiment and applying a fitting response surface model. This investigation identified the influence of the factors as well as the operating regions with minimum propensity to induce protein aggregation. Spectral changes pertinent to the stressed samples were also investigated and found to corroborate the high sensitivity of the intrinsic fluorescence to conformational changes of the proteins under study. Ultimately, partial least squares regression was implemented to formulate two fluorescence‐based soft sensors for quality control—product classification—and quantitative monitoring—concentration of monomer. The resulting regression models exhibited accurate prediction ability and good potential for in situ monitoring of monoclonal antibody downstream purification processes. © 2015 American Institute of Chemical Engineers Biotechnol. Prog., 31:1423–1432, 2015     

Fingerprint detection and process prediction by multivariate analysis of fed‐batch monoclonal antibody cell culture data

This work presents a sequential data analysis path, which was successfully applied to identify important patterns (fingerprints) in mammalian cell culture process data regarding process variables, time evolution and process response. The data set incorporates 116 fed‐batch cultivation experiments for the production of a Fc‐Fusion protein. Having precharacterized the evolutions of the investigated variables and manipulated parameters with univariate analysis, principal component analysis (PCA) and partial least squares regression (PLSR) are used for further investigation. The first major objective is to capture and understand the interaction structure and dynamic behavior of the process variables and the titer (process response) using different models. The second major objective is to evaluate those models regarding their capability to characterize and predict the titer production. Moreover, the effects of data unfolding, imputation of missing data, phase separation, and variable transformation on the performance of the models are evaluated. © 2015 American Institute of Chemical Engineers Biotechnol. Prog., 31:1633–1644, 2015     

Advanced monitoring and control of pharmaceutical production processes with Pichia pastoris by using Raman spectroscopy and multivariate calibration methods

This contribution includes an investigation of the applicability of Raman spectroscopy as a PAT analyzer in cyclic production processes of a potential Malaria vaccine with Pichia pastoris. In a feasibility study, Partial Least Squares Regression (PLSR) models were created off‐line for cell density and concentrations of glycerol, methanol, ammonia and total secreted protein. Relative cross validation errors RMSE_cvrel range from 2.87% (glycerol) to 11.0% (ammonia). In the following, on‐line bioprocess monitoring was tested for cell density and glycerol concentration. By using the nonlinear Support Vector Regression (SVR) method instead of PLSR, the error RMSE_Prel for cell density was reduced from 5.01 to 2.94%. The high potential of Raman spectroscopy in combination with multivariate calibration methods was demonstrated by the implementation of a closed loop control for glycerol concentration using PLSR. The strong nonlinear behavior of exponentially increasing control disturbances was met with a feed‐forward control and adaptive correction of control parameters. In general the control procedure works very well for low cell densities. Unfortunately, PLSR models for glycerol concentration are strongly influenced by a correlation with the cell density. This leads to a failure in substrate prediction, which in turn prevents substrate control at cell densities above 16 g/L.     

In‐line monitoring of amino acids in mammalian cell cultures using raman spectroscopy and multivariate chemometrics models

The application of PAT for in‐line monitoring of biopharmaceutical manufacturing operations has a central role in developing more robust and consistent processes. Various spectroscopic techniques have been applied for collecting real‐time data from cell culture processes. Among these, Raman spectroscopy has been shown to have advantages over other spectroscopic techniques, especially in aqueous culture solutions. Measurements of several process parameters such as glucose, lactate, glutamine, glutamate, ammonium, osmolality and VCD using Raman‐based chemometrics models have been reported in literature. The application of Raman spectroscopy, coupled with calibration models for amino acid measurement in cell cultures, has been assessed. The developed models cover four amino acids important for cell growth and production: tyrosine, tryptophan, phenylalanine and methionine. The chemometrics models based on Raman spectroscopy data demonstrate the significant potential for the quantification of tyrosine, tryptophan and phenylalanine. The model for methionine would have to be further refined to improve quantification.     

Quantitative modeling of viable cell density,cell size,intracellular conductivity,and membrane capacitance in batch and fed‐batch CHO processes using dielectric spectroscopy

Dielectric spectroscopy was used to analyze typical batch and fed‐batch CHO cell culture processes. Three methods of analysis (linear modeling, Cole–Cole modeling, and partial least squares regression), were used to correlate the spectroscopic data with routine biomass measurements [viable packed cell volume, viable cell concentration (VCC), cell size, and oxygen uptake rate (OUR)]. All three models predicted offline biomass measurements accurately during the growth phase of the cultures. However, during the stationary and decline phases of the cultures, the models decreased in accuracy to varying degrees. Offline cell radius measurements were unsuccessfully used to correct for the deviations from the linear model, indicating that physiological changes affecting permittivity were occurring. The β‐dispersion was analyzed using the Cole–Cole distribution parameters Δε (magnitude of the permittivity drop), f_c (critical frequency), and α (Cole–Cole parameter). Furthermore, the dielectric parameters static internal conductivity (σ_i) and membrane capacitance per area (C_m) were calculated for the cultures. Finally, the relationship between permittivity, OUR, and VCC was examined, demonstrating how the definition of viability is critical when analyzing biomass online. The results indicate that the common assumptions of constant size and dielectric properties used in dielectric analysis are not always valid during later phases of cell culture processes. The findings also demonstrate that dielectric spectroscopy, while not a substitute for VCC, is a complementary measurement of viable biomass, providing useful auxiliary information about the physiological state of a culture. © 2010 American Institute of Chemical Engineers Biotechnol. Prog., 2010     

Raman spectroscopy and chemometrics for on‐line control of glucose fermentation by Saccharomyces cerevisiae

This work presents the use of Raman spectroscopy and chemometrics for on‐line control of the fermentation process of glucose by Saccharomyces cerevisiae. In a first approach, an on‐line determination of glucose, ethanol, glycerol, and cells was accomplished using multivariate calibration based on partial least squares (PLS). The PLS models presented values of root mean square error of prediction (RMSEP) of 0.53, 0.25, and 0.02% for glucose, ethanol and glycerol, respectively, and RMSEP of 1.02 g L^?1 for cells. In a second approach, multivariate control charts based on multiway principal component analysis (MPCA) were developed for detection of fermentation fault‐batch. Two multivariate control charts were developed, based on the squared prediction error (Q) and Hotelling's T². The use of the Q control chart in on‐line monitoring was efficient for detection of the faults caused by temperature, type of substrate and contamination, but the T² control chart was not able to monitor these faults. On‐line monitoring by Raman spectroscopy in conjunction with chemometric procedures allows control of the fermentative process with advantages in relation to reference methods, which require pretreatment, manipulation of samples and are time consuming. Also, the use of multivariate control charts made possible the detection of faults in a simple way, based only on the spectra of the system. © 2012 American Institute of Chemical Engineers Biotechnol. Prog., 2012     

Mid‐infrared spectroscopy‐based analysis of mammalian cell culture Parameters

Within the framework of process analytical technology, infrared spectroscopy (IR) has been used for characterization of biopharmaceutical production processes. Although noninvasive attenuated total reflection (ATR) spectroscopy can be regarded as gold standard within IR‐based process analytics, simpler and more cost‐effective mid‐infrared (MIR) instruments might improve acceptability of this technique for high‐level monitoring of small scale experiments as well as for academia where financial restraints impede the use of costly equipment. A simple and straightforward at‐line mid‐IR instrument was used to monitor cell viability parameters, activity of lactate dehydrogenase (LDH), amount of secreted antibody, and concentration of glutamate and lactate in a Chinese hamster ovary cell culture process, applying multivariate prediction models, including only 25–28 calibration samples per model. Glutamate amount could be predicted with high accuracy (R² 0.91 for independent test‐set) while antibody concentration achieved good prediction for concentrations >0.4 mg L^?1. Prediction of LDH activity was accurate except for the low activity regime. The model for lactate monitoring was only moderately good and requires improvements. Relative cell viability between 20 and 95% could be predicted with low error (8.82%) in comparison to reference methods. An initial model for determining the number of nonviable cells displayed only acceptable accuracy and requires further improvement. In contrast, monitoring of viable cell number showed better accuracy than previously published ATR‐based results. These results prove the principal suitability of less sophisticated MIR instruments to monitor multiple parameters in biopharmaceutical production with relatively low investments and rather fast calibration procedures. © 2015 American Institute of Chemical Engineers Biotechnol. Prog., 31:578–584, 2015     

Surface Layering and Supersaturation for Top‐Down Nanostructural Development during Spin Coating of Polymer/Fullerene Thin Films

This study provides new evidence on a long postulated mechanism of phase separation in a polymer/fullerene mixture during spin coating for controlled nanodomains of oriented crystallization and heterojunctions that favor applications in polymer solar cells (PSCs). The simultaneous nanoscale phase separation and crystallization during spin coating of the mixture are traced using in situ grazing‐incidence small‐ and wide‐angle X‐ray scattering. Combined with the complimentary results from time‐resolved optical reflectance spectroscopy, transient stratification of the liquid film during the transition from the flow‐ to evaporation‐dominated stage of spin coating is disclosed; the vertical liquid–liquid phase separation incubates a supersaturated skin layer where fullerene aggregation and polymer crystallization occur and develop concomitantly. Shortly after the transition, the near‐surface structural development is largely pinned, leaving the solvent‐rich bottom layer to diminish via solvent diffusion and evaporation through the thickened skin layer that finally condenses into the spin‐coated film upon solvent depletion. The shear‐enhanced surface layering and supersaturation for the surface‐down nanostructural development are unexpected in all the existing structural models for PSCs. The mechanistic understanding of coupled vertical phase separation and local nanosegregation provides new insights and alternative strategy to the morphology control of spin‐cast PSC active layers in particular and various solution‐processed polymeric films in general.     

A novel LED‐based 2D‐fluorescence spectroscopy system for in‐line monitoring of Chinese hamster ovary cell cultivations – Part I

A new two‐dimensional fluorescence sensor system was developed for in‐line monitoring of mammalian cell cultures. Fluorescence spectroscopy allows for the detection and quantification of naturally occurring intra‐ and extracellular fluorophores in the cell broth. The fluorescence signals correlate to the cells’ current redox state and other relevant process parameters. Cell culture pretests with twelve different excitation wavelengths showed that only three wavelengths account for a vast majority of spectral variation. Accordingly, the newly developed device utilizes three high‐power LEDs as excitation sources in combination with a back‐thinned CCD‐spectrometer for fluorescence detection. This setup was first tested in a lab design of experiments study with process relevant fluorophores proving its suitability for cell culture monitoring with LOD in the μg/L range. The sensor was then integrated into a CHO‐K1 cell culture process. The acquired fluorescence spectra of several batches were evaluated using multivariate methods. The resulting batch evolution models were challenged in deviating and “golden batch” validation runs. These first tests showed that the new sensor can trace the cells’ metabolic state in a fast and reliable manner. Cellular distress is quickly detected as a deviation from the “golden batch”.     

Biophysical probing of the binding properties of a Cu(II) complex with G‐quadruplex DNA: an experimental and computational study

Telomerase inhibition through G‐quadruplex stabilization by small molecules is of great interest as a novel anticancer therapeutic strategy. Here, we show that newly synthesized Cu‐complex binds to G‐quadruplex DNA and induces changes in its stability. This biophysical interaction was investigated in vitro using spectroscopic, voltammetric and computational techniques. The binding constant for this complex to G‐quadruplex using spectroscopic and electrochemical methods is in the order of 10⁵. The binding stoichiometry was investigated using spectroscopic techniques and corresponded to a ratio of 1: 1. Fluorescence titration results reveal that Cu‐complex is quenched in the presence of G‐quadruplex DNA. Analysis of the fluorescence emission at different temperatures shows that ΔH° > 0, ΔS° > 0 and ΔG° < 0, and indicates that hydrophobic interactions played a major role in the binding processes. MD simulation results suggested that this ligand could stabilize the G‐quadruplex structure. An optimized docked model of the G‐quadruplex–ligand mixture confirmed the experimental results. Based on the results, we conclude that Cu‐complex as an anticancer candidate can bind and stabilize the G‐quadruplex DNA structure. Copyright © 2015 John Wiley & Sons, Ltd.     

Methodology for real-time,multianalyte monitoring of fermentations using an in-situ mid-infrared sensor

An in-situ, mid-infrared sensor was used to monitor the major analyte concentrations involved in the cultivation of Gluconacetobacter xylinus and the production of gluconacetan, a food-grade exopolysaccharide. To predict the analyte concentrations, three different sets of standard spectra were used to develop calibration models, applying partial least-squares regression. It was possible to build a valid calibration model to predict the 700 spectra collected during the complete time course of the cultivation, using only 12 spectra collected every 10 h as standards. This model was used to reprocess the concentration profiles from 0 to 15 g/L of nine different analytes with a mean standard error of validation of 0.23 g/L. However, this calibration model was not suitable for real-time monitoring as it was probably based on non-specific spectral features, which were correlated only with the measured analyte concentrations. Valid calibration models capable of real-time monitoring could be established by supplementing the set of 12 fermentation spectra with 42 standards of measured analytes. A pulse of 5 g/L ethanol showed the robustness of the model to sudden disturbances. The prediction of the models drifted, however, toward the end of the fermentation. The most robust calibration model was finally obtained by the addition of 34 standard spectra of non-measured analytes. Although the spectra did not contain analyte-specific information, it was believed that this addition would increase the variability space of the calibration model. Therefore, an expanded calibration model containing 88 spectra was used to monitor, in real time, the concentration profiles of fructose, acetic acid, ethanol and gluconacetan and allowed standard errors of prediction of 1.11, 0.37, 0.22, and 0.79 g/L, respectively.     

Rapid monitoring of recombinant antibody production by mammalian cell cultures using fourier transform infrared spectroscopy and chemometrics

Fourier transform infrared (FT‐IR) spectroscopy combined with multivariate statistical analyses was investigated as a physicochemical tool for monitoring secreted recombinant antibody production in cultures of Chinese hamster ovary (CHO) and murine myeloma non‐secreting 0 (NS0) cell lines. Medium samples were taken during culture of CHO and NS0 cells lines, which included both antibody‐producing and non‐producing cell lines, and analyzed by FT‐IR spectroscopy. Principal components analysis (PCA) alone, and combined with discriminant function analysis (PC‐DFA), were applied to normalized FT‐IR spectroscopy datasets and showed a linear trend with respect to recombinant protein production. Loadings plots of the most significant spectral components showed a decrease in the C–O stretch from polysaccharides and an increase in the amide I band during culture, respectively, indicating a decrease in sugar concentration and an increase in protein concentration in the medium. Partial least squares regression (PLSR) analysis was used to predict antibody titers, and these regression models were able to predict antibody titers accurately with low error when compared to ELISA data. PLSR was also able to predict glucose and lactate amounts in the medium samples accurately. This work demonstrates that FT‐IR spectroscopy has great potential as a tool for monitoring cell cultures for recombinant protein production and offers a starting point for the application of spectroscopic techniques for the on‐line measurement of antibody production in industrial scale bioreactors. Biotechnol. Bioeng. 2010; 106: 432–442. © 2010 Wiley Periodicals, Inc.