EA042735B1 - IN SITU RAMAN SPECTROSCOPY SYSTEMS AND METHODS FOR MONITORING PROCESS VARIABLES IN CELL CULTURES - Google Patents

Description

Cross-reference to related applications

The present application claims the benefit of the priority of the U.S. Provisional Application

62/572828 filed October 16, 2018 and 62/662322 filed April 25, 2018, all of which are incorporated by reference in their entirety where appropriate.

Technical field

The invention generally relates to bioreactor systems and methods, including in situ Raman spectroscopy methods and systems for monitoring and controlling one or more process variables in bioreactor cell culture.

State of the art

The Process Analytical Technology (PAT) Framework of the Food and Drug Administration (FDA) encourages the voluntary development and implementation of innovative process development, process analysis, and process control solutions to better understand processes and control product quality. Process parameters are monitored and controlled during production. For example, the supply of nutrients to a cell culture in a bioreactor during the production of bioproducts is an important process parameter. The modern production of bioproducts includes the strategy of feeding with daily bolus feeds. In accordance with current methods, daily bolus feeds increase the concentration of nutrients in cell cultures at least five times a day. To ensure that the culture does not deplete nutrients between feeds, daily bolus feeds keep nutrient concentrations high. Indeed, each feed is designed to have all the nutrients the crop needs to sustain it until the next feed. However, a large amount of nutrients in the daily bolus feed can cause significant fluctuations in nutrient levels in the bioreactor, resulting in inconsistencies in the quality of the product produced by the production crop.

In addition, the high concentration of nutrients in each daily bolus feed contributes to an increase in post-translational modifications of the resulting bioproduct. For example, high concentrations of glucose in cell culture can lead to increased glycation of the final bioproduct. Glycation is the non-enzymatic attachment of a reducing sugar to an amino acid residue of a protein, commonly found at the N-terminal amine of proteins and the positively charged amino group. The resulting glycation products may be yellow or brown, which may result in staining of the drug product (Hodge J.E. (1953) J Agric Food Chem. 1:928-943). Glycation can also lead to charge variations in one production batch of a therapeutic monoclonal antibody (mAb) and lead to binding inhibition (Haberger M. et al. (2014) MAbs. 6:327-339).

Accordingly, in an effort to advance the PAT initiative, there remains a need for a method or system capable of optimizing nutrient concentrations in cell culture, resulting in higher quality products.

The essence of the invention

Disclosed herein are in situ Raman spectroscopy methods and systems for monitoring and controlling one or more process variables in bioreactor cell culture.

One embodiment of the present invention includes a method for monitoring cell culture media conditions, comprising quantifying one or more analytes in the cell culture media using in situ Raman spectroscopy; and adjusting one or more analyte concentrations in the cell culture medium to match predetermined analyte concentrations that support post-translational modifications of proteins in the cell culture medium up to 1.0-30%. In some embodiments, the post-translational modification includes glycation. In other embodiments, the proteins in the cell culture include an antibody, an antigen-binding fragment thereof, or a fusion protein. In other embodiments, the cell culture medium comprises mammalian cells, such as Chinese hamster ovary cells.

In some embodiments, the analyte is glucose. In this aspect, the predetermined glucose concentration is 0.5 to 8.0 g/l. In another embodiment, the predetermined glucose concentration is 1.0 to 3.0 g/L. In yet another embodiment, the glucose concentration is 2.0 or 1.0 g/L. In other embodiments, predetermined analyte concentrations support post-translational modifications of proteins in the cell culture medium up to 1.0-20%, or 5.0 to 10%. In still other embodiments, the quantification of analytes is carried out continuously, periodically, or at intervals. For example, analytes are quantified at 5-, 10-, or 15-minute intervals. In yet other embodiments, analyte quantitation is performed hourly or at least daily. In some embodiments, the regulation of analyte concentrations is automatic. In still other embodiments, at least two, or at least three, or at least four different analytes are quantified.

- 1 042735

Another embodiment of the present invention includes a method for reducing post-translational modifications of a secreted protein, comprising culturing protein-secreting cells in a cell culture medium comprising 0.5-8.0 g/L glucose; gradually determining the glucose concentration in the cell culture medium during cell culture using in situ Raman spectroscopy; and adjusting the glucose concentration to maintain the glucose concentration at 0.5 to 8.0 g/l by automatically supplying several doses of glucose per 1 hour to maintain post-translational modifications of the secreted protein to 1.0-30.0%. In one embodiment, the glucose concentration is 1.0-3.0 g/L.

Another embodiment of the present invention includes a cell culture environmental control system comprising one or more processors interacting with a computer-readable medium storing program code for execution by one or more processors to cause the system to receive data including: the concentration of one or more analytes in cell culture medium using an in situ Raman spectrometer; and adjusting one or more analyte concentrations in the cell culture medium to match predetermined analyte concentrations that support post-translational modifications of proteins in the cell culture medium up to 1.0-30%. In one embodiment, the software code is further configured to cause the system to perform a chemometric analysis, such as fractional least squares data regression modeling. In other implementations, the program code is further configured to cause the system to perform one or more signal processing techniques, such as a data denoising technique.

Another embodiment of the present invention includes a system for reducing post-translational modifications of a secreted protein, comprising one or more processors interacting with a computer-readable medium storing program code for execution by one or more processors to cause the system to gradually increase the acquisition of spectral data, including the concentration of glucose in the culture medium. cells during the cultivation of cells secreting the protein from the in situ Raman analyzer; and adjusting the glucose concentration to maintain a glucose concentration of 0.5 to 8.0 g/L, such as 1.0 to 3.0 g/L, by automatically delivering several doses of glucose per hour to maintain post-translational modifications of the secreted protein up to 1.030.0%. In one embodiment, the software code is further configured to cause the system to correlate peaks in the spectral data with glucose concentrations. In another implementation, the program code is further configured to perform fractional least squares regression modeling of the spectral data. In yet another implementation, the software code is further configured to perform a spectral data denoising method. In other embodiments, regulation of glucose concentration is performed using automatic feedback control software.

Brief description of graphic materials

Additional features and advantages of the invention may be ascertained from the following detailed description, which is provided in connection with the drawings described below:

fig. 1 is a flow diagram of a method for monitoring process variables in cell culture, in accordance with one embodiment of the present invention;

fig. 2 is a schematic diagram of a cell culture process variable control system associated with FIG. 1, in accordance with the present invention;

fig. 3 is a graph showing the predicted values of the nutrient supply process confirmed by offline nutrient samples;

fig. 4 is a graph showing filtered feed process nutrient concentration endpoints after signal processing in accordance with the present invention;

fig. 5 is a graph showing predicted process nutrient concentrations and filtered final process nutrient concentration values after a shift in a predetermined nutrient concentration setpoint;

fig. 6 is a line graph showing the effect of glucose concentration on post-translational modifications with continuous controlled-feedback nutrient feeding according to the present invention and bolus nutrient feeding;

fig. 7 is a graph showing Raman's predicted in situ glucose concentration values for continuous, controlled-feedback nutrient feeding according to the present invention and bolus nutrient feeding;

fig. 8 is a line graph showing antibody titer during continuous, controlled feedback nutrient feeding according to the present invention and during bolus nutrient feeding;

- 2 042735 fig. 9 is a bar graph showing the normalized percentage of post-translational modifications as a result of the glucose concentration value;

fig. 10 is a graph showing glucose concentrations during continuous, controlled-feedback nutrient feeding in accordance with the present invention and during bolus nutrient feeding;

fig. 11 is a graph showing that cell culture with feedback can reduce PTM by up to 50% compared to cell culture with a bolus feed strategy.

Detailed description of the invention

Definitions.

As used herein, the singular forms also include the plural forms, unless the context clearly dictates otherwise.

The listing of ranges of values in this document is merely intended to serve as a concise way of individually referring to each individual value falling within that range, unless otherwise noted in this document, and each individual value is included in the description as if it were separately specified. in this document.

The use of the term about is intended to describe values above or below the stated value, in the range of approximately +/- 10%; in other embodiments, the values may be in the range either above or below the declared value in the range of approximately +/- 5%; in other embodiments, the values may be in the range either above or below the declared value in the range of approximately +/- 2%; in other embodiments, the values may be in the range either above or below the declared value in the range of approximately +/-1%. The previous ranges are intended to be clear from context and no further restrictions are intended. All of the methods described herein may be performed in any suitable order, unless otherwise specified herein or otherwise clearly contradicts the context. The use of any and all examples or exemplary language (eg, such as) provided herein is intended merely to better illuminate the invention and does not limit the scope of the invention unless otherwise stated. None of the language in the specification is to be construed as indicating any element not claimed to be essential to the practice of the invention.

The term bioproduct refers to any antibody, antibody fragment, modified antibody, protein, glycoprotein, or fusion protein, as well as drug end products produced in a bioreactor process.

The terms control and control refer to adjusting the amount or concentration level of a process variable in a cell culture to a predetermined set point.

The term monitoring refers to the regular checking of the amount or concentration level of a process parameter in a cell culture or the state of a process in a cell culture.

The term steady state refers to maintaining the concentration of nutrients, process parameters or traits in cell culture at a constant, constant or stable level. It is understood that a constant, constant or stable level refers to a level within predetermined predetermined values. Certain values, and therefore steady state levels, can be shifted by the operator during cell culture cultivation.

Methods for the production of bioproducts.

One embodiment provides methods for monitoring and controlling one or more process variables in a cell culture bioreactor to improve product quality and consistency. Process variables include, but are not limited to, concentration of glucose, amino acids, vitamins, growth factors, proteins, viable cell count, oxygen, nitrogen, pH, dead cell count, cytokines, lactate, glutamine, other sugars such as fructose and galactose, ammonium, osmolality and combinations thereof. The disclosed methods and systems utilize in situ Raman spectroscopy and chemometric modeling techniques for real-time cell culture evaluation in combination with signal processing techniques for accurate continuous feedback and predictive control of cell culture process variable parameters. In situ Raman spectroscopy of the contents of a bioreactor allows the analysis of one or more process variables in a bioreactor without physically removing the sample contained in the bioreactor for testing. Through the use of real-time data from Raman spectroscopy, process variables in cell culture can be monitored continuously or intermittently, and automated feedback controllers maintain process variables at setpoints or support a dedicated feed protocol that feeds variable amounts of agents into the bioreactor to maximize bioproduct quality. .

The disclosed methods and systems control one or more process variables during cell culture. The terms cell culture and cell culture medium can be used interchangeably and include any solid, liquid or semi-solid substance intended to support the growth and maintenance of microorganisms, cells or cell lines. Components such as polypeptides, sugars, salts, nucleic acids, cellular debris, acids, bases, pH buffers, oxygen, nitrogen, viscosity modulating agents, amino acids, growth factors, cytokines, vitamins, cofactors, and nutrients may be present in the medium for cell culture. One embodiment provides a mammalian cell culture process and includes mammalian cells or cell lines. For example, a mammalian cell culture process may use a Chinese Hamster Ovary (CHO) cell line grown in a chemically defined basal medium.

The cell culture process can be carried out in a bioreactor. Bioreactors include a system of seed fermenters, make-up and continuous bioreactors. Bioreactors may have a volume of from about 2 to about 10,000 liters. In one embodiment, the bioreactor may be a 60 L stainless steel bioreactor. In another embodiment, the bioreactor may be a 250 L bioreactor. Each bioreactor must also maintain a cell count in the range of about 5x106 to about 100x106 cells/mL. For example, the bioreactor should maintain a cell count from about 20x106 cells/mL to about 80 cells/mL.

The disclosed methods and systems can monitor and control any analyte that is present in cell culture and has a detectable Raman spectrum. For example, the methods of the present invention can be used to monitor and control any component of the cell culture medium, including components added to the cell culture, substances released from the cell, and components of the cell present at cell death. Components of the cell culture medium that can be monitored and/or controlled by the disclosed systems and methods include, but are not limited to, nutrients such as amino acids and vitamins, lactate, cofactors, growth factors, cell growth rate, pH, oxygen, nitrogen , number of viable cells, acids, bases, cytokines, antibodies and metabolites.

One embodiment provides methods for monitoring and controlling nutrient concentrations in cell culture. As used herein, the term nutrient can refer to any compound or substance that provides nutrition necessary for growth and survival. Examples of nutrients include, but are not limited to, simple sugars such as glucose, galactose, lactose, fructose, or maltose; amino acids; and vitamins such as vitamin A, B vitamins, and vitamin E. In another embodiment, the methods of the present invention may include monitoring and controlling glucose concentrations in cell culture. By controlling nutrient concentrations, such as glucose concentration in cell culture, it has been found that bioproducts such as proteins can be produced at a lower range of concentrations than was previously possible using a daily nutrient bolus strategy.

In addition, by controlling nutrient concentrations and other process variables in cell culture, the methods of the present invention further provide for the modulation of one or more post-translational protein modifications. Without being bound by any particular theory, it is believed that by providing lower nutrient concentrations in cell culture, post-translational modifications of proteins and antibodies can be reduced. Examples of post-translational modifications that may be modulated by the present invention include, but are not limited to, glycation, glycosylation, acetylation, phosphorylation, amidation, derivatization with known protecting/blocking groups, proteolytic cleavage, and modification by unnatural amino acids. In another embodiment, methods and systems are provided for modulating protein glycation. For example, by providing lower ranges of glucose concentrations in the cell culture medium, glycation levels in the secreted protein or antibody can be reduced in the final bioproduct.

Fig. 1 is a flowchart of an exemplary method for controlling one or more process variables, such as nutrient concentration, in a bioreactor cell culture. Predefined values for each of the process variables to be monitored and controlled can be programmed into the system. Preset setpoints represent the number of cell culture process variables that must be maintained or adjusted throughout the entire process. Glucose concentration is one example of a nutrient that can be controlled and modulated. As briefly discussed above, it has been found that bioproducts (e.g., proteins, antibodies, fusion proteins, and drugs) can be produced by cells in a culture medium that contains low levels of glucose compared to the glucose concentrations in the medium using a daily bolus strategy. doses of nutrients. In one embodiment, the specific nutrient concentration setpoint is the lowest nutrient concentration required for growth and expansion of the cell line. Disclosed methods

- 4 042735 would and systems can introduce many small doses of nutrients into the cell culture medium over a certain period of time, or can provide a constant flow of nutrient into the cell culture medium. In some embodiments, the preset value may be increased or decreased during the process, depending on the conditions in the cell culture medium. For example, if the nutrient concentration preset value results in cell death or suboptimal growth conditions in the cell culture medium, the preset value may be increased. However, the nutrient concentration should be maintained at a predetermined value of about 0.5 to about 10 g/L. In another embodiment, the nutrient concentration should be maintained at a predetermined value of about 0.5 to about 8 g/L. In another embodiment, the nutrient concentration should be maintained at a predetermined value of about 1 to about 3 g/L. In yet another embodiment, the nutrient concentration should be maintained at a predetermined value of about 2 g/l. These preset values essentially provide a baseline at which the nutrient concentration must be maintained throughout the process.

In one embodiment, the monitoring of one or more process variables, such as nutrient concentrations, in cell culture is performed by Raman spectroscopy (step 101). Raman spectroscopy is a form of vibrational spectroscopy that provides information about molecular vibrations that can be used to identify and quantify samples. In some embodiments, monitoring of process variables is performed using in situ Raman spectroscopy. In situ Raman analysis is a method of analyzing a sample at its original location without having to remove a portion of the sample for analysis in a Raman spectrometer. In situ Raman analysis has the advantage that Raman spectroscopy spectrometers are non-invasive, which reduces the risk of contamination and is non-destructive, does not affect cell culture viability or protein quality.

Raman analysis in situ can provide a real-time assessment of one or more process variables in cell cultures. For example, raw spectral data obtained by in situ Raman spectroscopy can be used to obtain and monitor the current amount of nutrient concentration in a cell culture. In this aspect, to ensure that the raw spectral data is constantly updated, spectral data from Raman spectroscopy should be taken approximately every 10 minutes to 2 hours. In another implementation, spectral data should be taken approximately every 15 minutes to 1 hour. In an embodiment, spectral data should be taken approximately every 20 to 30 minutes.

In this aspect, the monitoring of one or more process variables in cell culture can be analyzed using any commercially available Raman spectroscopic analyzer that allows in situ Raman analysis. The in situ Raman analyzer must be capable of obtaining raw spectral data in cell culture (eg, the Raman analyzer must be equipped with a probe that can be inserted into the bioreactor). Suitable Raman analyzers include, but are not limited to, the RamanRXN2 and RamanRXN4 analyzers (Kaiser Optical Systems, Inc. Ann Arbor, MI).

In step 102, the raw spectral data obtained from in situ Raman spectroscopy can be compared with offline measurements of the specific process variable to be monitored or controlled (e.g., offline nutrient concentration measurements) to correlate peaks in the spectral data with the process variable. . For example, if the process variable to be monitored or controlled is glucose concentration, offline glucose concentration measurements can be used to determine which spectral regions show the glucose signal. Offline measurement data can be collected by any suitable analytical method. In addition, any type of multivariate software package, such as SIMCA 13 (MKS Data Analytic Solutions, Umea, Sweden), can be used to correlate peaks in raw spectral data with offline measurements of the specific process variable to be monitored or controlled. However, in some implementations, it may be necessary to pre-process the raw spectral data with spectral filters to remove any changing baselines. For example, the raw spectral data may be pre-processed with any type of point smoothing technique or normalization technique. Normalization may be required to correct for any change in laser power and exposure time using a Raman analyzer. In one embodiment, the raw spectral data can be processed with point smoothing, such as 1st derivative with 21 cm ^-1 point smoothing, and normalization, such as Standard Normal Variate (SNV) normalization.

Chemometric modeling can also be performed on the acquired spectral data. In this aspect, one or more multivariate methods, including, but not limited to,

- 5 042735 fractional least squares (DNA), principal component analysis (PCA), orthogonal fractional least squares (ODLS), multivariate regression, canonical correlation, factor analysis, cluster analysis, graphical procedures, etc., can be used with respect to spectral data. In one embodiment, the resulting spectral data is used to generate a DNA regression model. A DNA regression model can be created by projecting predicted variables and observed variables into a new space. In this aspect, a DNA regression model can be generated using measurement values obtained from Raman analysis and offline measurement values. The DNA regression model provides process predictions, such as nutrient concentration predictions.

After the chemometric simulation, a signal processing method can be applied to the process predictions (eg, nutrient concentration predictions) (step 103). In one embodiment, the signal processing technique includes a noise reduction technique. In this aspect, one or more noise reduction techniques may be applied to the predicted process values. Any noise reduction method known to those skilled in the art may be used. For example, the noise reduction method may include data smoothing and/or signal suppression. Smoothing is achieved using a range of smoothing algorithms and filters, while signal suppression uses signal characteristics to identify data that should not be included in the analyzed spectral data. In one embodiment, the process predictions are noise reduced by the noise reduction filter. The denoising filter provides the final filtered values of the process (for example, the final filtered values of nutrient concentration). In this aspect, the denoising method combines the raw measurements with a model-based estimate of what the measurement should give according to the model. In one implementation, the noise reduction method combines the current predicted value of the process with its uncertainties. Uncertainties can be determined by the repeatability of predicted process values and current process conditions. After the next process predictor is obtained, the process predictor estimate (eg, nutrient concentration predictor) is updated using a weighted average, with more weight given to higher confidence estimates. Using an iterative approach, final process values can be updated based on previous measurement and current process conditions. In this aspect, the algorithm must be recursive and able to work in real time in order to use the current predicted value of the process, the previous value and experimentally determined constants. The noise reduction method improves the reliability of the measurements obtained from the Raman analysis and DNA predictions by reducing the noise that will be affected by the automatic feedback controller.

Once the final filtered process values (eg, final filtered nutrient concentration values) are received, the final values may be sent to an automatic feedback controller (step 104). An automatic feedback controller can be used to control and maintain a process variable (eg nutrient concentration) at a predetermined setpoint. An automatic feedback controller may include any type of controller that is capable of calculating an error value as the difference between a desired setpoint (eg, a preset value) and a measured process variable and automatically apply an accurate and responsive correction. The automatic feedback controller should also have controls that can be changed in real time from the platform interface. For example, an automatic feedback controller should have a user interface that allows the preset value to be adjusted. The automatic feedback controller must be able to respond to a change in the preset value.

In one embodiment, the automatic feedback controller may be a proportional-integral derivative (PID) controller. In this aspect, the PID controller operates to calculate the difference between a predetermined value and a measured process variable (eg, measured nutrient concentration) and automatically applies a fine correction. For example, when it is necessary to control the concentration of nutrients in a cell culture, a PID controller may be able to calculate the difference between a filtered nutrient value and a preset value and provide a correction in the amount of nutrients. In this aspect, the PID controller may be operatively connected to a feed pump on the bioreactor such that a corrective amount of nutrient may be pumped into the bioreactor (step 105).

Through the use of real-time Raman analysis and feedback control, the methods of the present invention are able to provide a continuous and reduced concentration of nutrients for cell culture. Thus, the method of the present invention is able to provide a sustainable addition of nutrients to the cell culture. In one implementation

- 6 042735 In order to maintain a given concentration of nutrients, nutrients can be continuously pumped into the cell culture through a nutrient pump for a certain period of time. In another embodiment, nutrients may be added to the cell culture via a feed pump in an operating cycle. For example, in this aspect, the addition of nutrients may be intermittent or occur intermittently over a period of time.

The disclosed methods and systems also allow the production of bioproducts in a culture medium that contains a lower range of nutrient concentrations, such as a range of glucose concentrations, than nutrient concentrations in the culture medium using a daily nutrient bolus strategy. In one embodiment, nutrient concentrations, such as glucose concentrations, are at least 3 g/L lower than when fed with a bolus. In another embodiment, nutrient concentrations, such as glucose concentrations, are at least 5 g/L lower than nutrient concentrations in the culture medium obtained using a nutrient bolus. In yet another embodiment, nutrient concentrations, eg, glucose concentrations, are at least 6 g/L lower than nutrient concentrations obtained using a nutrient bolus.

In addition, the lower culture media nutrient concentrations and steady state addition achieved by the disclosed systems and methods allow for reduced post-translational modification of proteins and monoclonal antibodies. In one embodiment, the implementation of the disclosed methods and systems provide for the introduction of nutrients at or at the rate at which nutrients are taken up or consumed by cells in culture. The continuous addition of small doses of nutrients over time allows bioproducts to be obtained having lower levels of post-translational modifications, such as lower levels of glycation, compared to a standard bolus feed. It is important that the constant addition of reduced concentrations of nutrients does not affect the production of antibodies. In one embodiment, reduced nutrient concentrations provide as much as a 30% reduction in post-translational modification compared to post-translational modifications seen with standard bolus feeding. In another embodiment, reduced nutrient concentrations provide a reduction in post-translational modification by as much as 40% compared to the post-translational modifications seen with standard bolus feeding. In yet another embodiment, reduced nutrient concentrations provide as much as a 50% reduction in post-translational modification compared to post-translational modifications seen with standard bolus feeding.

bioreactor systems.

Another embodiment provides systems for monitoring and controlling one or more process variables in a cell culture bioreactor. Several components are integrated into a single system with a single user interface. Referring to FIG. 2, a Raman analyzer 200 may be operatively connected to a bioreactor 300. In this aspect, a Raman probe may be inserted into the bioreactor 300 to obtain raw spectral data of one or more process variables, such as nutrient concentration, in cell culture. The Raman analyzer 200 can also be operatively connected to the computer system 500 so that the resulting raw spectral data can be acquired and processed.

Computer system 500 may typically be implemented using one or more general purpose programmable computer systems such as embedded processors, systems on a chip, personal computers, workstations, server systems, and minicomputers or mainframe computers, or in distributed networked computing environments. Computer system 500 may include one or more processors (CPUs) 502A-502N, I/O circuitry 504, network adapter 506, and memory 508. CPUs 502A-502N execute program instructions to perform the functions of the present systems and methods. Typically, CPUs 502A-502N are one or more microprocessors, such as an INTEL CORE® processor.

The input/output circuit 504 allows data to be input or output from the computer system 500. For example, the input/output circuit may include input devices such as keyboards, mice, touch pads, trackballs, scanners, A/D converters, etc., output devices such as video adapters, monitors, printers, etc. and input/output devices such as modems, etc. Network adapter 506 couples device 500 to network 510. Network 510 can be any public or proprietary LAN or WAN, including but not limited to the Internet.

Memory 508 stores program instructions that are executed and data that is used and processed by processor 502 to perform the functions of computer system 500. Memory 508 may include, for example, electronic storage devices such as random access memory (RAM), read only memory (ROM) , programmable read-only memory (PROM), electrically erasable programmable read-only memory

- 7 042735 Main device (EEPROM), flash memory, etc. and electromechanical memory such as magnetic disk drives, tape drives, optical drives, etc., which may use built-in interface drives (IDE) or variations or extensions thereof, such as enhanced IDE (EIDE) or ultra-direct memory access ( UDMA), or Small Computer System Interface (SCSI) based interface, or a variant or enhancement thereof such as fast-SCSI, wide-SCSI, fast-wide-SCSI, etc., or serial storage interface (SATA), or a variation or enhancement thereof, or an Arbitrary Logic Fiber Channel (FC-AL) drop interface.

The memory 508 may include a recurring controller 512, a data controller 514, and an operating system 520. The recurring controller 512 may include a recurring software product to operate one or more controllers. The data controller 514 may include data required by the regular operations controller 512 to perform processing. In one implementation, the regular operations controller 512 may include multivariate software for performing multivariate analysis, such as. DNA regression model. In this aspect, the regular operations controller 512 may include SLMCA-QPp (MKS Data Analytic Solutions, Umea, Sweden) to perform DNA chemometric modeling. In another implementation, the schedule controller 512 may also include software to perform denoising on the data set. In this aspect, the regular operation controller 512 may include a MATLAB Runtime (The Mathworks Inc., Natick, MA) to execute denoising filter models. In addition, the regular operation controller 512 may include software, such as MATLAB Runtime, to work with an automatic feedback controller, such as a PID controller. The control software for the automatic feedback controller must be able to calculate the difference between the preset value and the measured process variable (eg measured nutrient concentration) and automatically apply a fine correction. Accordingly, the computer system 500 may also be operatively connected to the feed pump 400 so that a corrective amount of nutrient may be pumped into the bioreactor 300.

The disclosed systems may control and monitor process variables in a single bioreactor or multiple bioreactors. In one embodiment, the system may control and monitor process variables in at least two bioreactors. In another embodiment, the system may control and monitor process variables in at least three bioreactors or at least four bioreactors. For example, the system can control up to four bioreactors per hour.

Examples

The following non-limiting examples demonstrate methods for controlling one or more process variables in a cell culture bioreactor in accordance with the present invention. The examples are merely illustrative of the preferred embodiments of the present invention and should not be construed as limiting the invention, the scope of which is defined by the appended claims.

Example 1

Materials and methods.

The mammalian cell culture process used a Chinese Hamster Ovary (CHO) cell line grown in a chemically defined basal medium. Production was carried out in an experimental 60 L stainless steel bioreactor with RSLogix 5000 software (Rockwell Automation, Inc. Milwaukee, WI).

Data acquisition for the model included spectral data from Kaiser RamanRXN2 and RamanRXN4 analyzers (Kaiser Optical Systems, Inc. Ann Arbor, MI) using BIO-PRO optics (Kaiser Optical Systems, Inc. Ann Arbor, MI). The operating parameters of the RamanRXN2 and RamanRXN4 analyzers were set to a scan time of 10 s for 75 acquisitions. OPC Reader/Writer for RSLinx OPC Server was used for data transfer.

SIMCA 13 (MKS Data Analytic Solutions, Umea, Sweden) was used to correlate peaks in spectral data with offline glucose measurements. Subsequent spectral filtering was performed on the raw spectral data: 1st derivative with smoothing of the 21 cm ⁻¹ point to remove changing baselines and standard normal variation (SNV) normalization to correct for changes in laser power and exposure time.

A partial least squares regression model was generated with corresponding offline measurements performed on the Nova Bioprofile Flex (Nova Biomedical, Waltham, MA). In table. 1A below are the details of the chemometric regression model of fractional least squares nutrient concentration values.

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Table 1A

Detailed data of the chemometric regression model using the method of fractional least squares of nutrient concentration values

DNA Model Nutrient Concentration Variable Meaning Observations 223 Wavelength range (cm-1) 350-3100 Nutrient concentration range (g/l) 0.65-8.63 RMSEE (Root Mean Square Estimate Error) 0.430 RSMECV (Root Mean Squared Error of Cross Validation) 0.662 ^R2X 0.982 ^Q2 0.869

Signal processing techniques have also been performed, in particular noise reduction filtering. The denoising technique combined the raw measurement with a model-based estimate of what the measurement should give according to the model. Using an iterative approach, it allows you to update the filtered dimension based on the previous dimension and the current process conditions.

An inverse proportional-integral-derivative (PID) control was used, having an algorithm programmed separately in MATLAB Runtime (The Mathworks Inc., Natick, MA). All PID controller variables, such as tuning constants, can be changed in real time from the platform interface.

Results.

Fig. 3 shows the predicted value of the nutrition process, confirmed by offline nutrient samples. As can be seen from FIG. 3, the Raman analyzer and the chemometric model predicted nutrient concentration values within the variability of the offline analytical method. This demonstrates that in situ Raman spectroscopy and chemometric modeling according to the methods of the present invention provide accurate measurements of nutrient concentration values.

Fig. 4 shows the filtered endpoints of the nutrient supply process after the signal processing method. As can be seen from FIG. 4, the signal processing method reduces the noise of the original power process predictions. Filtering predicted nutrient values with noise reduction improves the reliability of the entire feedback control system.

Fig. 5 shows the predicted nutrient process values and the filtered nutrient process endpoints after a shift in a predetermined setpoint nutrient concentration in a feed-back batch with controlled feedback. As can be seen from the adjustment of the values of the filtered process of nutrient supply, a successful response from the feedback controller is observed when there is a shift in the value of the concentration of nutrients. Indeed, the PID controller was able to quickly respond to a setpoint change by operating on the filtered value of the process nutrient noise.

Based on the results shown in FIG. 3-5, the methods of the present invention provide real-time data that provides automatic feedback control for continuous and constant nutrient addition.

Example 2

Materials and methods.

Production was carried out in separate bioreactors with a volume of 250 liters. A regression model was created using the fractional least squares method. In table. 1B below are the details of the chemometric regression model of fractional least squares nutrient concentrations.

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Table 1B

Detailed data of the chemometric regression model using the method of fractional least squares of nutrient concentration values

DNA Model Nutrient Concentration Variable Meaning Observations 147 Wavelength range (cm-1) 350-3100 Nutrient concentration range (g/l) 0.6-3.61 RMSEE (Root Mean Square Estimate Error) 0.352 RSMECV (Root Mean Squared Error of Cross Validation) 0.520 ^R2X 0.769 ^Q2 0.617

No noise reduction techniques were used in this example.

Results.

Fig. 6 shows the effect of glucose concentration on post-translational modifications. As can be seen from FIG. 6, the higher the glucose concentration, the higher the percentage of PTM. The data in FIG. 6 for normalized % post-translational modifications (PTM) and glucose concentration on the day of the study series are shown in Table. 2 below.

table 2

Normalized % PTM and glucose concentration data for FIG. 6

Time watch) % PTM Concentration glucose Normalized % PTM Glucose concentration (g/l) 192 18.7 4.83 0.623333333 4.83 192 20.4 9.75 0.68 9.75 195 20.6 8.4 0.686666667 8.4 198 20.2 8.3 0.673333333 8.3 200 16.2 7.68 0.54 7.68 214 16.6 3.96 0.553333333 3.96 214 17.7 9.34 0.59 9.34 220 17.4 9.09 0.58 9.09 223 17.5 8.03 0.583333333 8.03 225 20.9 7.68 0.696666667 7.68 238 21.5 4.56 0.716666667 4.56 238 22.3 8.22 0.743333333 8.22 243 21.8 7.78 0.726666667 7.78 246 23.1 7.19 0.77 7.19 248 18.6 7.08 0.62 7.08 267 17 4.11 0.566666667 4.11 291 19.1 3.3 0.636666667 3.3 310 19.4 4.62 0.646666667 4.62 315 19 4.55 0.633333333 4.55 318 24 4.23 0.8 4.23 320 24.7 4 0.823333333 4 334 26 2.53 0.866666667 2.53 340 25.3 2.15 0.843333333 2.15 343 25.9 1.86 0.863333333 1.86 345 20.7 1.67 0.69 1.67 357 19.7 0.59 0.656666667 0.59 358 20.2 11.18 0.673333333 11.18 362 20.6 10.34 0.686666667 10.34 366 20.5 10.31 0.683333333 10.31 381 25.9 7.74 0.863333333 7.74

Fig. 7 is a graph showing the predicted in situ Raman spectroscopy values of glucose concentration under continuous feed with controlled feedback in accordance with the present invention and under bolus feed with nutrients. The black thick line in Fig. 7 represents a predetermined setpoint. The predetermined setpoint (331) was initially set at 3 g/l (331) and has been increased to 5 g/l (332). As can be seen from FIG. 7, the glucose concentrations predicted by Raman spectroscopy are accurately corrected during the shift at predetermined values. The observational data in Fig. 7 for Raman values of glucose concentration on the day of the study series are shown in table. 3 below.

- 10 042735

Table 3

Glucose concentration data predicted by Raman for FIG. 7

Time (glucose feedback control) (elapsed days) Ramanovskaya closed-loop glucose concentration (g/l) Time (bolus glucose feed) (past days) Ramanovskaya bolus concentration (g/l) 2 5.27449 2 #n/a 2.023263889 6.057528 2.023263889 #n/a 2.044097222 6.093102 2.044097222 #n/a 2.064930556 6.030814 2.064930556 #n/a 2.085763889 5.928053 2.085763889 #n/a 2.106597222 6.112341 2.106597222 #n/a 2.127430556 5.877689 2.127430556 #n/c 2.148263889 5.881066 2.148263889 #n/a 2.169097222 5.929256 2.169097222 #n/a 2.189930556 5.928593 2.189930556 #n/a 2.210763889 5.929407 2.210763889 #n/a 2.231597222 5.672209 2.231597222 #n/a 2.252430556 5.796999 2.252430556 #n/a 2.273263889 5.572541 2.273263889 #n/a 2.294097222 5.771776 2.294097222 #n/a 2.31494213 5.521614 2.31494213 #n/a 2.335775463 5.630873 2.335775463 #n/a 2.356608796 5.53435 2.356608796 #n/a 2.37744213 5.628556 2.37744213 #n/a 2.398275463 5.575116 2.398275463 #n/a 2.419108796 5.675688 2.419108796 #n/a 2.43994213 5.356216 2.43994213 #n/a 2.460775463 5.019809 2.460775463 #n/a 2.481608796 5.571718 2.481608796 #n/a 2.50244213 5.424471 2.50244213 #n/a 2.523275463 4.974746 2.523275463 #n/a 2.544108796 5.105621 2.544108796 #n/a 2.56494213 4.882367 2.56494213 #n/a 2.585775463 5.156937 2.585775463 #n/a 2.606608796 4.882068 2.606608796 #n/a 2.62744213 5.054303 2.62744213 #n/a 2.648275463 5.034556 2.648275463 6.109157 2.669108796 4.835382 2.669108796 5.83853 2.689953704 5.057273 2.689953704 6.071649 2.710787037 4.504433 2.710787037 6.257731 2.73162037 4.725886 2.73162037 5.978051 2.752453704 4.707865 2.752453704 5.687498 2.773275463 4.474821 2.773275463 5.510823 2.794108796 4.595435 2.794108796 5.745687 2.814953704 4.846455 2.814953704 5.493782 2.835787037 4.349487 2.835787037 5.420269 2.85662037 4.623514 2.85662037 5.677184 2.877453704 4.35981 2.877453704 5.499728 2.898287037 4.580013 2.898287037 5.273839 2.91912037 4.233418 2.91912037 5.523314 2.939953704 4.033472 2.939953704 5.601781 2.960787037 3.875247 2.960787037 5.556786 3.0009375 4.083802 3.0009375 5.661055 3.023287037 3.564172 3.023287037 5.20255 3.04412037 3.788096 3.04412037 5.251106 3.064953704 3.721753 3.064953704 5.24757 3.12525463 3.615655 3.12525463 5.073968 3.166898148 3.759606 3.166898148 5.125836 3.208564815 3.402011 3.208564815 5.700113 3.250231481 3.312303 3.250231481 5.346854

- 11 042735

3.291898148 3.384652 3.291898148 5.366998 3.333553241 2.754262 3.333553241 5.469024 3.416898148 2.657981 3.416898148 4.906005 3.458564815 2.661131 3.458564815 4.953602 3.500231481 2.683549 3.500231481 5.018805 3.541909722 2.315241 3.541909722 5.040889 3.583564815 2.470533 3.583564815 4.669607 3.625243056 2.895316 3.625243056 4.677879 3.666909722 3.167133 3.666909722 4.748203 3.708564815 2.959319 3.708564815 4.306628 3.750243056 3.334286 3.750243056 4.003834 3.791898148 3.10766 3.791898148 4.363513 3.833587963 3.058263 3.833587963 4.014596 3.875243056 2.723771 3.875243056 4.028898 3.916909722 2.612081 3.916909722 4.080404 3.958576389 2.666911 3.958576389 3.442322 4.00025463 2.121485 4.00025463 3.755342 4.040208333 2.498356 4.040208333 3.691836 4.063460648 2.796938 4.063460648 3.801793 4.084293981 3.222628 4.084293981 3.397573 4.105127315 3.059871 4.105127315 3.198539 4.125960648 3.144483 4.125960648 6.444279 4.146793981 2.912629 4.146793981 6.634366 4.167627315 2.798553 4.167627315 6.147713 4.188460648 2.657885 4.188460648 6.247666 4.209305556 2.724152 4.209305556 6.187882 4.230127315 2.72257 4.230127315 6.114422 4.250960648 2.797554 4.250960648 5.93613 4.271793981 3.035758 4.271793981 5.516821 4.332094907 2.726879 4.332094907 5.486897 4.373726852 2.984358 4.373726852 5.457622 4.415405093 2.487146 4.415405093 5.381355 4.457060185 2.364557 4.457060185 5.195489 4.498738426 2.894607 4.498738426 4.731695 4.540393519 3.171245 4.540393519 4.725901 4.623738426 3.579278 4.623738426 4.398326 4.665405093 3.227408 4.665405093 4.601714 4.707071759 2.769516 4.707071759 3.739007 4.74875 3.303736 4.74875 4.125107 4.810706019 2.604359 4.810706019 3.918031 4.833958333 2.666446 4.833958333 3.87917 4.854791667 2.436089 4.854791667 3.812785 4.875625 2.365274 4.875625 #n/a 4.896458333 3.052339 4.896458333 #n/a 4.917291667 3.356655 4.917291667 #n/a 4.938125 3.536857 4.938125 #n/a 4.958958333 3.254377 4.958958333 8.184118 4.979803241 2.647855 4.979803241 7.679708 5.000625 2.479576 5.000625 7.4381 5.021458333 3.108576 5.021458333 6.956085 5.042291667 2.733165 5.042291667 6.785896 5.063136574 2.161332 5.063136574 6.765765 5.083958333 2.115124 5.083958333 6.793903 5.104803241 2.617033 5.104803241 6.765692 5.125636574 2.554023 5.125636574 6.222265 5.146458333 2.480167 5.146458333 6.749342 5.167291667 2.715101 5.167291667 5.725123 5.188136574 2.735876 5.188136574 5.549073 5.208969907 2.725627 5.208969907 5.06423 5.229803241 2.575811 5.229803241 5.338056 5.250636574 2.212894 5.250636574 5.471513 5.271458333 2.233998 5.271458333 5.151946 5.292303241 2.213399 5.292303241 5.546629 5.313136574 2.766555 5.313136574 5.259173 5.333969907 2.52938 5.333969907 4.601235 5.354803241 2.933614 5.354803241 4.772757 5.375636574 3.028033 5.375636574 4.52338 5.396469907 3.41555 5.396469907 4.513873

- 12 042735

5.417303241 3.193063 5.417303241 4.173473 5.438136574 3.138092 5.438136574 3.831865 5.458981481 2.893515 5.458981481 3.9247 5.479814815 3.43812 5.479814815 3.336164 5.500636574 3.013834 5.500636574 3.628655 5.521469907 3.132246 5.521469907 3.92468 5.542314815 3.046817 5.542314815 7.176596 5.563148148 3.078321 5.563148148 6.633468 5.583981481 2.615919 5.583981481 6.08785 5.604803241 2.751108 5.604803241 6.244726 5.625636574 2.824868 5.625636574 5.927638 5.646469907 2.517154 5.646469907 7.42588 5.667314815 1.988747 5.667314815 6.687646 5.688148148 2.344756 5.688148148 7.307424 5.708969907 3.218347 5.708969907 6.437283 5.729814815 2.85646 5.729814815 5.960429 5.750648148 2.43488 5.750648148 6.032461 5.771493056 2.792278 5.771493056 6.137525 5.811608796 2.982295 5.811608796 6.469258 5.833981481 2.991141 5.833981481 6.484286 5.854814815 3.201134 5.854814815 5.838443 5.875659722 2.563264 5.875659722 5.693282 5.896481481 2.42295 5.896481481 6.134384 5.917314815 2.673206 5.917314815 5.663696 5.938148148 2.654685 5.938148148 5.459308 5.958981481 2.747516 5.958981481 5.10138 5.979814815 2.548837 5.979814815 5.754516 6.019282407 2.525679 6.019282407 4.844961 6.060914352 2.808173 6.060914352 5.415936 6.102592593 2.547346 6.102592593 5.179432 6.144259259 2.485466 6.144259259 4.849273 6.185925926 2.707999 6.185925926 4.904904 6.227592593 3.150225 6.227592593 4.450798 6.269259259 2.60164 6.269259259 4.495592 6.310925926 2.741736 6.310925926 3.395906 6.352592593 2.407971 6.352592593 4.206471 6.394259259 1.757518 6.394259259 3.473652 6.435925926 2.549188 6.435925926 3.669552 6.477604167 3.543268 6.477604167 8.226236 6.519270833 3.739929 6.519270833 8.798409 6.5609375 3.384398 6.5609375 8.077047 6.602604167 3.33986 6.602604167 7.873461 6.644270833 2.969001 6.644270833 7.76911 6.6859375 2.726888 6.6859375 7.415218 6.727604167 2.846601 6.727604167 6.526413 6.769270833 2.275316 6.769270833 6.82022 6.8109375 2.198233 6.8109375 6.822738 6.852615741 3.320418 6.852615741 6.629892 6.894282407 3.746778 6.894282407 6.207532 6.935949074 3.943445 6.935949074 6.731417 6.977615741 3.363937 6.977615741 5.485258 7.019282407 2.890475 7.019282407 6.309702 7.060949074 3.262214 7.060949074 5.860365 7.102615741 2.954454 7.102615741 5.880978 7.144282407 2.153391 7.144282407 5.84526 7.185960648 2.378666 7.185960648 5.735903 7.227662037 2.9512 7.227662037 5.541218 7.269293981 3.551366 7.269293981 5.192567 7.310960648 3.218829 7.310960648 9.177272 7.352627315 3.12968 7.352627315 8.703374 7.394293981 2.593928 7.394293981 8.983128 7.435960648 2.394028 7.435960648 8.965026 7.477627315 2.21824 7.477627315 8.120359 7.519293981 3.134434 7.519293981 8.137175 7.560960648 2.766007 7.560960648 8.314145 7.602627315 2.512249 7.602627315 8.698809 7.644305556 2.630357 7.644305556 8.641541 7.685972222 2.416168 7.685972222 8.071362

- 13 042735

7.727638889 2.661644 7.727638889 8.489848 7.769305556 2.79807 7.769305556 8.062885 7.810960648 2.972875 7.810960648 7.448528 7.852638889 2.41065 7.852638889 8.106278 7.894305556 2.495323 7.894305556 7.770178 7.935972222 2.934737 7.935972222 8.291804 7.977638889 2.847816 7.977638889 7.42387 8.01931713 3.15902 8.01931713 8.205845 8.060983796 3.667069 8.060983796 7.910364 8.102638889 3.282952 8.102638889 7.724277 8.14431713 2.793275 8.14431713 7.616001 8.185983796 2.452958 8.185983796 7.379514 8.227650463 2.630365 8.227650463 7.477386 8.26931713 2.729709 8.26931713 6.807137 8.310983796 2.807003 8.310983796 6.842168 8.352650463 2.620657 8.352650463 9.308379 8.39431713 3.13093 8.39431713 8.968605 8.436030093 2.627208 8.436030093 9.14572 8.477662037 2.251114 8.477662037 8.747909 8.51931713 2.646687 8.51931713 8.726134 8.56099537 3.079137 8.56099537 8.391006 8.602662037 2.563705 8.602662037 8.450653 8.644328704 3.087527 8.644328704 7.990832 8.68599537 2.590317 8.68599537 8.18066 8.727662037 2.968817 8.727662037 7.942457 8.769340278 3.12238 8.769340278 7.713663 8.811006944 3.547524 8.811006944 8.415674 8.852673611 4.297379 8.852673611 7.626019 8.894340278 4.161104 8.894340278 8.069413 8.936018519 5.030762 8.936018519 8.045293 8.977673611 5.637126 8.977673611 8.527124 9.019351852 5.298599 9.019351852 7.610373 9.061006944 4.932112 9.061006944 7.099549 9.102685185 5.059932 9.102685185 7.573514 9.144351852 4.555223 9.144351852 7.538042 9.186018519 4.263374 9.186018519 7.441958 9.227685185 4.428963 9.227685185 7.639114 9.269351852 4.978399 9.269351852 6.761559 9.311018519 5.80515 9.311018519 7.284119 9.352685185 5.421699 9.352685185 7.794689 9.394351852 5.041867 9.394351852 9.245949 9.436018519 4.245652 9.436018519 10.85137 9.477685185 4.627719 9.477685185 10.59078 9.519363426 5.043918 9.519363426 10.01031 9.561030093 5.134606 9.561030093 9.805758 9.602696759 4.84806 9.602696759 10.12079 9.644398148 3.838338 9.644398148 10.16871 9.686030093 4.53542 9.686030093 9.679668 9.727696759 4.92595 9.727696759 9.62599 9.769351852 4.769973 9.769351852 9.378336 9.811030093 5.17225 9.811030093 10.05829 9.852696759 4.80986 9.852696759 8.640112 9.894363426 5.148977 9.894363426 9.457369 9.936030093 4.672589 9.936030093 9.403243 9.977708333 4.188494 9.977708333 9.422581 10.019375 4.707168 10.019375 9.496971 10.06104167 4.721385 10.06104167 8.947212 10.10269676 4.783384 10.10269676 8.878696 10.144375 4.512029 10.144375 9.005632 10.18604167 4.258463 10.18604167 8.788143 10.22770833 4.029292 10.22770833 8.814812 10.269375 4.322887 10.269375 8.966389 10.31104167 4.08165 10.31104167 8.892519 10.35265046 4.958148 10.35265046 9.361223 10.394375 5.847916 10.394375 8.628824 10.43604167 6.32333 10.43604167 8.199861 10.47770833 6.265306 10.47770833 7.797361 10.51938657 5.801625 10.51938657 8.34846

- 14 042735

10.56104167 5.735916 10.56104167 9.992476 10.60271991 5.45328 10.60271991 10.55201 10.64438657 5.33565 10.64438657 10.78163 10.68605324 5.542859 10.68605324 10.40103 10.72771991 5.033404 10.72771991 9.900923 10.76938657 4.913043 10.76938657 9.858058 10.81105324 5.076824 10.81105324 10.93733 10.85275463 4.666098 10.85275463 10.56453 10.89439815 4.554989 10.89439815 10.63292 10.93605324 4.729548 10.93605324 10.1317 10.97771991 4.089445 10.97771991 10.15173 11.01938657 3.973743 11.01938657 10.03745 11.06105324 4.564354 11.06105324 9.908442 11.10273148 4.511001 11.10273148 9.87036 11.14439815 5.108614 11.14439815 10.1959 11.18606481 4.441917 11.18606481 9.519185 11.22773148 4.69673 11.22773148 9.621466 11.26939815 4.755281 11.26939815 10.03958 11.31106481 4.227083 11.31106481 8.765776 11.35273148 4.190309 11.39439815 4.416976 11.43606481 4.467027 11.47773148 5.739811 11.51939815 5.667678 11.56107639 5.399963 11.60273148 5.114323 11.64440972 5.493369 11.68607639 4.566129 11.72774306 4.238223 11.76940972 4.256388 11.81107639 3.624721 11.85274306 4.105767 11.89440972 5.08095 11.93607639 5.102737 11.97775463 5.012239

Fig. 8 shows the antibody titer during continuous feed with controlled feedback and during bolus feed with nutrients. As seen in FIG. 8, antibody production is not affected by any of the methods. In the tables below. 4 and 5 show bolus fed antibody titer and feedback control antibody titer data, respectively, for FIG. 8.

Table 4

The bolus feed antibody titer data for FIG. 8

Bolus Refill Time (Past Days) Titer AB at bolus feed (mg/l) Titer of normalized AB during bolus feeding 0 0.866 0.000721667 0.831180556 2.362 0.001968333 1.668321759 #N/A #n/a 2.614583333 32.606 0.027171667 3.625787037 89.425 0.074520833 4.531863426 148.02 0.12335 5.726122685 301.873 0.251560833 6.67775463 421.186 0.350988333 7.65849537 519.165 0.4326375 8.641284722 670.959 0.5591325 9.714537037 #n/a #N/A 10.66090278 #n/a #N/A 11.64418981 #n/a #N/A 12.62819444 1158.82 0.965683333

Table 5

The fed-back antibody titer data for FIG. 8

Make-up time with closed-loop control Titer AB at feeding with feedback (mg/l) Titer of normalized AB with feed-back 0 #n/a #n/a 0.753171296 2.556 0.00213 1.749884259 15.36 0.0128 2.757048611 48.048 0.04004 3.710439815 105.017 0.087514167 4.757465278 205.669 0.171390833 5.814016204 #n/a #n/a

- 15 042735

Fig. 9 shows the normalized percentage of PTM as a result of glucose concentration. As can be seen from FIG. 9, a decrease in PMT is observed as the glucose concentration decreases from about 6-8 g/L (setpoint (33) for bolus feed collection) to 5g/L (setpoint 2) to 3g/L (setpoint 1). In other words, a decrease in nutrient exposure leads to a decrease in PTM.

The data in FIG. 9 for the normalized percentage of PTM are shown in table. 6 below.

6.735243056 423.018 0.352515 7.729918981 543.108 0.45259 8.767893519 683.645 0.569704167 9.742418981 795.66 0.66305 10.70917824 913.834 0.761528333 11.73123843 1034.809 0.862340833 12.79594907 1134.383 0.945319167

Table 6

The normalized % PTM data for FIG. 9

Condition % Post-translational modifications Normalized % post-translational modifications Day -1 Increases 33 12.03 0.401 Day 0 Increases 33 11.79 0.393 Day 1 Increases 33 14.88 0.496 Day 2 Increases 33 16.48 0.549333333 Day 3 Increases 33 17.58 0.586 Day 4 Increases 33 20.63 0.687666667 Collection on bolus refill 27.2 0.906666667

Fig. 10 is a graph showing glucose concentrations during continuous, controlled-feedback nutrient feeding according to the present invention and during bolus nutrient feeding. As can be seen from FIG. 10, the methods of the present invention are capable of providing reduced, stable glucose concentrations. The data in FIG. 10 for glucose concentrations are shown in table. 7 below.

Table 7

The glucose concentration data for FIG. 10

Time (hour) Feedback control Feedback control of glucose concentration (g/l) Time (h) Bolus Refill Glucose concentration during bolus feeding (g/l) 0 5.29985 0 3.9606 0.443888889 3.95717 0.443888889 3.92564 0.888055556 3.87786 0.888055556 3.82241 1.331944444 3.94245 1.554444444 3.84826 1.554444444 3.88536 1.998333333 3.78432 1.998333333 3.88327 2.442222222 3.81402 2.442222222 3.84436 4.382222222 3.83029 2.886111111 3.7485 5.334444444 3.75084 3.589444444 6.98909 6.226666667 3.80185 4.157777778 3.83584 7.119166667 3.72134 5.11 3.78798 8.011388889 3.68723 6.0025 3.7856 8.900833333 3.71741 6.894722222 3.73533 20.45444444 3.40678 7.787222222 3.68673 30.1175 4.74804 8.679444444 3.66978 31.01027778 4.80446 20.23388889 3.40307 31.90277778 4.76064 21.12222222 3.40884 32.79527778 4.69968 21.56944444 3.37754 33.68777778 4.7881 29.72194444 3.11293 43.51138889 4.50823 30.78583333 3.15921 44.40333333 4.44888 31.67833333 3.08833 45.295 4.56108 32.57111111 2.95089 46.18777778 4.44496 33.46333333 3.04687 47.07722222 4.43893 34.35305556 2.90941 56.46 4.27974 43.2875 2.92864 57.35194444 4.30659 44.17888889 2.81226 58.24444444 4.29294 45.07138889 2.85354 59.13638889 4.18843 45.96333333 2.83553 60.02611111 4.13743 46.85583333 2.79272 69.4075 4.95997 56.23555556 2.67934 71.02194444 4.9194 57.12805556 2.67136 71.46583333 4.41552 58.02 2.57063 71.90972222 4.38365 58.91194444 2.54624 72.35361111 4.42239

- 16 042735

59.80472222 2.50303 73.02027778 4.31899 69.18361111 2.97555 73.46416667 4.37885 70.07583333 3.77294 73.90805556 4.3449 70.80111111 4.34847 74.35194444 4.23448 71.46583333 4.08935 75.01861111 4.24824 71.90972222 4.00212 75.4625 4.14202 72.35361111 3.99123 75.90638889 4.14761 72.7975 4.01331 76.35027778 4.07654 73.02027778 3.99191 77.01694444 4.04303 73.46416667 3.91424 77.46083333 4.10848 73.90805556 3.85688 77.90472222 4.02519 74.35194444 3.84475 78.34861111 3.97673 74.79583333 3.67941 79.01527778 3.97045 75.01861111 3.64752 79.45916667 3.99019 75.4625 3.66484 79.90305556 3.90772 75.90638889 3.6525 80.34694444 4.13212 76.35027778 3.55085 81.01361111 3.94071 76.79416667 3.45215 81.4575 3.93964 77.01694444 3.42771 81.90138889 3.93305 77.46083333 3.5292 82.34527778 3.90002 77.90472222 3.47243 83.01194444 3.78135 78.34861111 3.48275 83.45583333 3.80974 78.7925 3.44748 83.89972222 3.72092 79.01527778 3.51503 84.34361111 3.54584 79.45916667 3.40908 85.01055556 3.79766 79.90305556 3.4091 85.45472222 3.73607 80.34694444 3.40949 85.89861111 3.6327 80.79083333 3.37424 86.34277778 3.60241 81.01361111 3.66927 87.01 3.64506 81.4575 3.40708 87.45416667 3.4821 81.90138889 3.29053 87.89805556 3.49399 82.34527778 3.33054 88.34194444 3.50496 82.78916667 3.3244 89.00888889 3.53164 83.01194444 3.2331 89.45305556 3.31505 83.45583333 3.24332 89.89722222 3.27601 83.89972222 3.39759 90.34111111 3.33213 84.34361111 3.15861 91.00805556 3.43951 84.78777778 3.22317 91.45222222 3.38503 85.01055556 3.24632 91.89611111 3.1468 85.45472222 3.31019 92.34027778 3.4265 85.89861111 3.17534 93.00694444 3.24971 86.34277778 3.14291 93.45083333 3.19635 86.78694444 3.11793 93.895 3.27543 87.01 3.16349 94.33888889 3.09075 87.45388889 3.0751 95.24694444 2.49991 87.89805556 2.9869 95.69111111 2.57693 88.34194444 3.00619 96.135 2.5465 88.78583333 2.95103 96.57916667 4.02104 89.00888889 3.05399 97.02305556 3.98664 89.45305556 2.81784 97.46722222 3.95544 89.89694444 2.94564 97.91138889 3.86852 90.34111111 2.82913 98.35527778 3.66631 90.785 2.83378 99.0225 3.62051 91.00805556 2.91134 99.46638889 3.76868 91.45222222 3.09505 99.91027778 3.69577 91.89611111 2.86231 100.3544444 3.74638 92.34027778 2.95479 101.0216667 3.61072 92.78416667 2.84231 101.4655556 3.65232 93.00694444 2.81938 101.9094444 3.65673 93.45083333 2.79815 102.3536111 3.50981 93.895 2.83839 103.0205556 3.59905 94.33888889 2.93334 103.4647222 3.50056 95.02611111 2.94485 103.9086111 3.58028 95.69083333 3.01962 104.3525 3.51239 96.135 3.08518 105.0194444 3.35906 96.57888889 2.90996 105.4636111 3.46452 97.02305556 2.822 105.9077778 3.4217 97.46722222 2.60949 106.3516667 3.52777

- 17042735

97.91111111 2.98458 107.0186111 3.37968 98.35527778 2.99921 107.4627778 3.24786 98.79944444 2.89195 107.9066667 3.17432 99.02222222 2.88476 108.3508333 3.26832 99.46638889 2.80296 109.0180556 3.09402 99.91027778 2.81875 109.4619444 3.19621 100.3544444 2.88799 109.9061111 3.15208 100.7986111 2.7446 110.3502778 3.08408 101.0213889 2.71513 111.0169444 3.12704 101.4655556 2.62124 111.4611111 3.09169 101.9094444 2.7469 111.905 3.13017 102.3536111 2.6358 112.3488889 3.10825 102.7977778 2.64662 113.0161111 3.05118 103.0205556 2.64383 113.4602778 2.96148 103.4644444 2.48012 113.9041667 3.13752 103.9086111 2.56149 114.3483333 3.07076 104.3525 2.61773 115.0152778 2.97416 104.7966667 2.58291 115.4594444 3.11854 105.0194444 2.49816 115.9033333 3.01764 105.4636111 2.46984 117.2877778 6.00949 105.9075 2.5008 117.7316667 5.96736 106.3516667 2.47808 118.1758333 5.92612 106.7955556 2.24744 118.6194444 5.64293 107.0186111 2.57076 119.2863889 5.49402 107.4625 2.47027 119.7302778 5.43498 107.9066667 2.43396 120.1741667 5.47254 108.3508333 2.43259 120.6180556 5.28723 108.7947222 2.4977 121.2847222 5.26741 109.0177778 2.38829 121.7286111 5.17114 109.4619444 2.34725 122.1725 5.22748 109.9058333 2.22657 122.6163889 5.18455 110.35 2.27469 123.2830556 5.05853 110.7941667 2.3519 123.7269444 5.09368 111.0169444 2.28667 124.1708333 5.06618 111.4608333 2.29553 124.6147222 4.92785 111.905 2.30401 125.2813889 4.95126 112.3488889 2.1131 125.7252778 5.12272 112.7930556 2.05542 126.1694444 5.04657 113.0158333 2.15201 126.6133333 4.89878 113.46 2.15773 127.28 4.89227 113.9041667 2.1462 127.7236111 4.83168 114.3480556 2.0095 128.1675 4.73809 114.7922222 2.00685 128.6113889 4.62723 115.015 2.08611 129.2783333 4.56662 115.4591667 2.23016 129.7222222 4.5413 115.9033333 1.89489 130.1661111 4.39996 116.3475 2.03546 130.61 4.36069 117.0672222 2.11907 131.2766667 4.47573 117.7316667 2.10383 131.7205556 4.19303 118.1755556 1.91726 132.1644444 4.17655 118.6194444 1.93228 132.6083333 4.24852 119.0636111 1.78201 133.275 4.07631 119.2863889 1.90199 133.7188889 4.01898 119.7302778 1.76972 134.1627778 3.97811 120.1741667 1.81882 134.6066667 3.7236 120.6180556 1.90338 135.2736111 3.78111 121.0619444 1.86254 135.7177778 3.82847 121.2847222 1.89595 136.1613889 3.56015 121.7286111 1.95022 136.6052778 3.56488 122.1725 2.03028 137.2722222 3.59907 122.6163889 2.02368 137.7158333 3.53736 123.0602778 1.80358 138.1597222 3.51143 123.2830556 1.86305 138.6036111 3.48144 123.7269444 1.68852 139.2705556 3.69714 124.1708333 2.16485 139.7144444 3.53598 124.6147222 2.68219 140.1583333 3.56975 125.0586111 3.84445 140.6022222 3.46682 125.2813889 3.75849 141.5097222 3.27107

- 18 042735

125.7252778 3.05046 141.9536111 3.37317 126.1691667 1.60889 142.3975 3.19992 126.6133333 1.55251 142.8413889 3.29018 127.0569444 1.49635 143.285 5.29681 127.28 1.4625 143.7288889 5.42912 127.7238889 1.5599 144.1730556 5.31815 128.1675 1.411 144.6169444 5.49514 128.6113889 1.59737 145.2836111 5.31922 129.0555556 1.49927 145.7275 5.50698 129.2783333 1.55528 146.1713889 5.40168 129.7222222 1.68831 146.6152778 5.21572 130.1661111 1.65586 147.2819444 5.22277 130.61 1.69803 147.7258333 5.32597 131.0538889 1.51503 148.1697222 5.25509 131.2766667 1.62337 148.6133333 5.18307 131.7205556 1.56305 149.0683333 5.08164 132.1644444 1.53581 149.3183333 4.88397 132.6083333 1.39492 149.5683333 5.06794 133.0522222 1.35263 149.8183333 5.01549 133.275 1.2922 150.0686111 4.91031 133.7188889 1.21502 150.3186111 4.92284 134.1627778 1.38027 150.5686111 4.88071 134.6066667 1.30947 150.8186111 4.90576 135.0505556 1.3538 151.0686111 4.7337 135.2736111 1.36581 151.3186111 4.98071 135.7175 1.19768 151.5686111 4.66753 136.1613889 1.41395 151.8186111 4.73602 136.6052778 1.08014 152.2625 4.67663 137.0494444 1.32496 152.7066667 4.66436 137.2719444 1.34268 153.1505556 4.79716 137.7158333 1.45098 153.5947222 4.70976 138.16 1.3088 154.0388889 4.68658 138.6038889 1.39873 154.4827778 4.45627 139.0475 1.36488 154.9269444 4.69575 139.2705556 1.19001 155.3711111 4.61841 139.7144444 1.40293 156.0380556 4.58039 140.1583333 1.41103 156.4822222 4.6775 140.6022222 1.5462 156.9263889 4.4771 141.2888889 2.01927 157.3702778 4.35384 141.9536111 2.42777 158.0372222 4.4401 142.3975 2.63074 158.4811111 4.56737 142.8413889 2.83209 158.9252778 4.42704 143.285 2.72224 159.3691667 4.07445 143.7288889 2.63608 160.0361111 4.36575 144.1730556 2.69195 160.4802778 4.13995 144.6169444 2.71345 160.9241667 4.22379 145.0608333 2.50984 161.3680556 4.17469 145.2836111 2.6369 162.035 4.28975 145.7275 2.60541 162.4788889 4.13539 146.1713889 2.67274 162.9230556 3.87281 146.6152778 2.69351 163.3672222 4.87836 147.0591667 2.50699 164.0338889 5.2242 147.2819444 2.68272 164.4780556 5.24807 147.7258333 2.80848 165.165 5.03418 148.1697222 2.71963 165.8297222 4.81739 148.6133333 3.27574 166.2736111 4.73886 152.2625 1.84522 166.7177778 4.87246 152.7066667 2.02054 167.1616667 4.77461 153.1505556 1.89572 167.6058333 4.68469 153.5947222 1.7493 168.2725 4.5802 154.0386111 1.82994 168.7166667 4.5102 154.4827778 2.03299 169.1608333 4.70917 154.9269444 1.84201 169.6047222 4.54906 155.3708333 2.33961 170.2716667 4.58545 155.815 2.17287 170.7155556 4.46504 156.0380556 2.09251 171.1597222 4.47254 156.4822222 2.00326 171.6036111 4.42642 156.9263889 2.00972 172.2705556 4.48492

- 19042735

157.3702778 1.95632 172.7147222 4.27087 157.8144444 1.85693 173.1586111 4.16092 158.0372222 1.87511 173.6027778 4.23464 158.4811111 2.25587 174.2697222 4.18793 158.9252778 2.41394 174.7138889 4.17626 159.3691667 2.27275 175.1580556 4.12183 159.8133333 2.33431 175.6022222 4.31591 160.0361111 2.11631 176.2691667 3.96654 160.48 2.15315 176.7130556 3.86951 160.9241667 2.21482 177.1572222 4.05681 161.3680556 2.10691 177.6013889 3.80757 161.8119444 1.9879 178.2683333 3.88444 162.0347222 2.07513 178.7122222 3.7184 162.4788889 2.09918 179.1563889 3.76801 162.9230556 2.045 179.6002778 3.65193 163.3669444 2.0579 180.2672222 3.8665 163.8111111 1.9786 180.7113889 3.60753 164.0338889 2.04415 181.1552778 3.56228 164.4780556 2.11519 181.5994444 3.51562 164.9219444 2.04256 182.2663889 3.53538 165.8297222 1.92716 182.7105556 3.58554 166.2736111 1.74054 183.1544444 3.52299 166.7177778 2.17775 183.5986111 3.50055 167.1616667 2.21902 184.2655556 3.35449 167.6055556 2.23581 184.7097222 3.15678 168.0497222 2.1295 185.1536111 3.49221 168.2725 2.06408 185.5977778 3.31856 168.7166667 1.95822 186.2644444 3.1794 169.1608333 1.87785 186.7086111 3.261 169.6047222 2.38464 187.1525 3.26585 170.0486111 2.52549 187.5963889 3.11678 170.2716667 2.48755 188.0405556 3.29677 170.7155556 2.39386 188.4847222 3.13789 171.1594444 2.26082 188.9288889 3.04174 171.6036111 2.10124 189.8586111 2.84437 172.0477778 2.04631 190.7886111 2.97215 172.2705556 1.96783 191.7183333 2.74657 172.7144444 2.03789 192.6480556 2.85061 173.1586111 1.96485 193.5780556 2.71859 173.6025 1.75977 194.5077778 2.64369 174.0466667 2.13635 195.4377778 2.23807 174.2697222 2.35361 196.3675 2.16861 174.7138889 2.19967 197.2975 2.18502 175.1577778 2.2276 198.2275 2.02487 175.6019444 2.26713 199.1572222 2.00279 176.0461111 2.27076 200.0861111 2.05927 176.2688889 2.08234 201.0158333 1.77877 176.7130556 2.05613 201.9455556 3.21063 177.1569444 1.98094 202.8752778 5.70505 177.6011111 2.09971 203.8047222 5.55309 178.0452778 2.13739 204.7341667 5.62934 178.2683333 1.81014 205.6636111 5.40796 178.7122222 2.33795 206.5933333 5.26706 179.1561111 2.27909 207.5230556 5.24844 179.6002778 2.13411 208.4522222 5.04861 180.0441667 2.28842 208.8961111 4.9106 180.2672222 2.3228 209.3402778 4.83827 180.7113889 2.20826 209.7844444 5.05838 181.1552778 2.1662 210.2286111 4.83412 181.5991667 1.97546 210.6725 4.76257 182.0433333 2.11621 211.1166667 4.64707 182.2661111 2.07917 211.7836111 4.80408 182.7102778 1.95 212.2275 4.53231 183.1544444 2.00555 212.6716667 4.68255 183.5983333 2.1972 213.1155556 4.661 184.0425 1.99805 213.7827778 4.53894 184.2652778 1.90735 214.2266667 4.38914 184.7094444 2.07147 214.6705556 4.51892

-20042735

185.1536111 2.30457 215.1147222 4.35161 185.5975 1.94533 215.7816667 4.2933 186.0416667 2.04383 216.2255556 4.2022 186.2644444 2.02201 216.6697222 4.14232 186.7086111 2.00486 217.1136111 4.19824 187.1525 1.87491 217.7808333 3.98641 187.5963889 1.71041 218.225 4.17967 188.0405556 2.27353 218.6688889 4.12755 188.4844444 2.27361 219.1130556 3.98162 188.9286111 2.21939 219.7797222 4.18885 189.6158333 2.32112 220.2238889 3.99614 190.5455556 2.23684 220.6680556 3.88445 191.4752778 2.00438 221.1122222 4.00875 192.4052778 2.08773 221.7794444 4.02466 193.335 1.98721 222.2233333 4.92433 194.2647222 2.34499 222.6675 5.31792 195.1947222 2.07045 223.1116667 5.10258 196.1247222 1.87379 223.7786111 5.18651 197.9844444 2.44455 224.2227778 5.33129 198.9144444 1.43529 224.6669444 5.31647 199.8438889 2.10835 225.1111111 5.22186 200.7730556 2.16165 225.7780556 5.09756 201.7027778 2.03911 226.2219444 5.0919 202.6325 2.02224 226.6661111 5.09598 203.5619444 2.04709 227.1102778 5.20148 204.4916667 1.74866 227.7775 5.27139 205.4205556 2.42807 228.2213889 5.17647 206.3502778 2.3646 228.6655556 4.97104 207.28 2.29919 229.1097222 4.95102 208.2313889 2.37703 229.7766667 5.02617 208.8961111 2.39499 230.2208333 4.89217 209.3402778 1.97051 230.6647222 5.06075 209.7841667 2.24512 231.1088889 4.91127 210.2283333 2.25347 231.7758333 4.75924 210.6725 2.08371 232.6836111 4.86344 211.1166667 2.15365 233.1275 4.66869 211.5605556 2.29691 233.5713889 4.77352 211.7833333 2.03092 234.0155556 4.63601 212.2275 1.97129 234.4597222 4.71014 212.6716667 1.9721 234.9038889 4.69685 213.1155556 2.07924 235.3477778 4.83778 213.5597222 1.93054 235.7919444 4.73268 213.7825 2.09871 236.2358333 4.72232 214.2266667 2.01653 236.6797222 4.70191 214.6705556 1.97157 237.1238889 4.61924 215.1147222 2.08205 237.7908333 5.82279 215.5586111 2.20945 238.2347222 5.95289 215.7816667 1.90401 238.6788889 5.7376 216.2255556 2.25764 239.1227778 5.39835 216.6697222 2.20062 239.7897222 5.55047 217.1136111 2.38191 240.2336111 5.45566 217.5577778 2.30704 240.6777778 5.56575 217.7808333 2.3666 241.1219444 5.37954 218.225 2.21814 241.7888889 5.28663 218.6688889 2.22546 242.2330556 5.22091 219.1130556 2.29399 242.6769444 5.31419 219.5569444 2.35247 243.1211111 5.269 219.7797222 2.36244 243.7880556 5.33359 220.2238889 2.42202 244.2322222 5.20919 220.6677778 3.90842 244.6763889 5.16646 221.1119444 3.226 245.1202778 4.87647 221.5561111 3.24104 245.7872222 5.19865 221.7791667 3.44121 246.2313889 5.26332 222.2233333 2.10021 246.6755556 5.27455 222.6675 1.65588 247.1194444 4.9051 223.1116667 2.00054 247.7863889 4.96193 223.5555556 2.2584 248.2302778 4.95473 223.7786111 2.18337 248.6744444 4.87265

- 21 042735

224.2227778 2.22002 249.1186111 4.88933 224.6666667 2.02996 249.7855556 4.95339 225.1108333 2.11005 250.2297222 4.91535 225.555 1.98403 250.6738889 4.8415 225.7780556 1.97535 251.1180556 4.73406 226.2219444 2.1047 251.785 4.75863 226.6661111 2.14528 252.2291667 4.83177 227.1102778 2.11167 252.6733333 4.73776 227.5541667 1.96546 253.1175 4.80804 227.7772222 2.1583 253.7841667 4.47607 228.2213889 2.09114 254.2283333 4.44379 228.6655556 2.03119 254.6722222 4.61578 229.1097222 2.03169 255.1163889 4.35294 229.5536111 1.805 255.7833333 4.35565 229.7766667 1.75306 256.4702778 4.63822 230.2208333 2.03753 257.4 4.1795 230.6647222 1.98862 258.3291667 4.3277 231.1088889 1.85836 259.2588889 4.10085 231.5530556 1.81241 260.1886111 4.15495 231.7758333 1.83977 261.1183333 3.90911 232.4627778 1.76471 262.0477778 3.81073 233.1275 1.63967 262.9772222 3.87842 233.5713889 1.79819 263.9061111 5.04643 234.0155556 1.74429 264.8347222 4.97527 234.4594444 1.77757 265.7641667 4.93942 234.9036111 1.82093 266.6936111 4.81825 235.3477778 1.75825 267.6225 4.80283 235.7919444 1.71644 268.2875 4.75164 236.2358333 1.64919 268.7313889 4.93642 236.6797222 1.65067 269.1755556 4.75401 237.1238889 1.59211 269.6197222 4.51092 237.5677778 2.09602 270.2866667 4.5984 237.7905556 2.0281 270.7308333 4.54899 238.2347222 2.0728 271.1747222 4.70999 238.6786111 1.96003 271.6188889 4.4307 239.1227778 2.13435 272.2858333 4.3134 239.5666667 2.14529 272.7297222 4.46242 239.7897222 2.12039 273.1738889 4.44403 240.2336111 2.1226 273.6177778 4.31874 240.6777778 2.17822 274.2847222 4.43482 241.1216667 2.09458 274.7286111 4.22428 241.5658333 1.93963 275.1727778 4.50794 241.7888889 1.78058 275.6166667 4.37905 242.2327778 1.92457 276.2836111 4.28183 242.6769444 2.54728 276.7277778 4.36293 243.1208333 2.7696 277.1716667 4.06209 243.565 2.96879 277.6155556 4.27271 243.7880556 3.0983 278.2825 4.05231 244.2322222 2.44977 278.7266667 4.19835 244.6761111 3.0513 279.1705556 4.10201 245.1202778 4.46037 279.6147222 4.0479 245.5641667 3.64992 280.2816667 4.14879 245.7872222 2.63717 280.7258333 4.01384 246.2311111 2.23246 281.1697222 3.94503 246.6752778 1.96177 281.6138889 3.82963 247.1194444 1.9733 282.2808333 4.01967 247.5633333 1.92291 282.725 4.08182 247.7863889 1.9421 283.1688889 3.83589 248.2302778 2.29655 283.6130556 3.8807 248.6744444 2.15675 284.28 3.60671 249.1186111 2.06017 284.7238889 3.74206 249.5625 1.83718 285.1680556 3.61191 249.7855556 2.26354 285.6119444 3.64284 250.2297222 2.15135 286.2788889 3.49373 250.6736111 2.13613 286.7227778 3.75384 251.1177778 2.01012 287.1666667 5.50193 251.5619444 1.91997 287.6108333 5.36619 251.785 2.04497 288.2777778 5.44722

- 22 042735

252.2288889 1.76215 288.7219444 5.23718 252.6730556 1.91976 289.1661111 5.48611 253.1172222 2.17963 289.61 5.29237 253.5613889 2.49015 290.2769444 5.09807 253.7841667 2.31233 290.7211111 5.27902 254.2280556 2.25077 291.165 5.21127 254.6722222 2.41304 291.8522222 4.93468 255.1161111 2.32947 292.5169444 5.3445 255.5602778 2.27885 292.9611111 4.9385 255.7833333 1.94173 293.4052778 5.0282 256.2272222 2.39855 293.8491667 4.92491 257.1572222 1.97358 294.2933333 4.94234 258.0863889 2.13599 294.7375 5.14301 259.0161111 2.20439 295.1813889 5.09006 259.9458333 2.07312 295.6252778 4.97926 260.8752778 2.35689 296.2922222 4.79825 261.8052778 2.16814 296.7363889 4.98856 262.7347222 2.00509 297.1802778 4.64638 263.6638889 2.06753 297.6241667 4.83557 264.5925 1.85036 298.2913889 4.66544 265.5213889 2.46909 298.7352778 4.46933 266.4508333 2.44871 299.1794444 4.42644 267.3797222 2.44656 299.6233333 4.40905 268.2872222 2.48505 300.2902778 4.48562 268.7313889 2.63435 300.7344444 4.29635 269.1755556 3.24711 301.1786111 4.21742 269.6194444 2.23888 301.6227778 4.5645 270.0636111 2.07904 302.2894444 4.37116 270.2863889 2.21563 302.7333333 4.30076 270.7305556 1.91896 303.1775 4.357 271.1747222 2.09629 303.6216667 4.19275 271.6188889 2.04491 304.2888889 4.3476 272.0627778 1.96894 304.7327778 4.12702 272.2858333 2.10447 305.1766667 4.22847 272.7297222 1.98481 305.6208333 4.14018 273.1736111 1.88517 306.2877778 3.91622 273.6177778 2.02339 306.7319444 4.0101 274.0616667 2.1536 307.1758333 4.08905 274.2844444 1.94488 307.62 3.69736 274.7286111 2.09537 308.2866667 3.89877 275.1725 1.94546 308.7308333 3.91969 275.6166667 1.97124 309.1747222 3.95032 276.0605556 2.10351 309.6188889 3.83547 276.2833333 2.15169 310.2858333 5.15943 276.7275 2.06851 310.73 4.85061 277.1713889 1.95511 311.1738889 4.90129 277.6155556 2.17411 311.6177778 4.69627 278.0594444 1.91116 312.2847222 4.98669 278.2825 1.89503 312.7286111 4.99629 278.7263889 2.13133 313.1727778 4.92192 279.1705556 2.23375 313.6166667 4.91592 279.6147222 2.07922 314.2838889 4.79179 280.0588889 2.15941 314.7277778 4.82191 280.2816667 2.10306 315.1719444 4.62895 280.7258333 2.09977 315.6158333 4.68028 281.1697222 1.90922 316.5236111 4.39498 281.6138889 1.97935 316.9675 4.51145 282.0577778 1.98323 317.4116667 4.64399 282.2808333 2.13178 317.8558333 4.35246 282.725 2.05535 318.5230556 4.39085 283.1688889 2.17687 318.9669444 4.51255 283.6130556 2.10914 319.4111111 4.26767 284.0569444 1.88863 319.855 4.41338 284.28 1.90439 320.5225 4.04934 284.7238889 2.27687 320.9663889 4.54584 285.1680556 2.27819 321.4105556 4.21321 285.6119444 1.97363 321.8547222 4.26114 286.0561111 2.474 322.5219444 4.16462

- 23 042735

286.2788889 2.08995 322.9658333 4.03369 286.7227778 2.25392 323.41 4.07753 287.1666667 2.16887 323.8541667 4.06638 287.6108333 2.53164 324.5213889 4.03094 288.0547222 2.19634 324.9652778 4.01644 288.2777778 2.18478 325.4094444 4.21972 288.7219444 2.05544 325.8536111 4.08692 289.1661111 2.28481 326.5205556 3.84686 289.61 2.18665 326.9644444 4.04213 290.0538889 2.44092 327.4086111 3.77223 290.2769444 2.30768 327.8527778 3.9225 290.7208333 2.09997 328.52 3.99757 291.165 2.13653 328.9638889 3.76221 291.6091667 2.29461 329.4080556 3.68814 292.5166667 1.89174 329.8522222 3.89506 293.405 3.35168 330.5194444 3.79475 293.8491667 3.81949 330.9636111 3.69956 294.2933333 1.83112 331.4075 3.64703 294.7372222 1.8642 331.8516667 3.57235 295.1813889 2.16381 295.6252778 2.17022 296.0691667 1.98928 296.2919444 1.90433 296.7361111 2.24558 297.1802778 2.07294 297.6241667 2.00742 298.0680556 2.04407 298.2911111 1.82856 298.7352778 2.18444 299.1791667 2.38328 299.6233333 1.94764 300.0675 2.35273 300.2902778 2.10771 300.7344444 2.18582 301.1783333 2.28062 301.6225 2.18726 302.0666667 2.01366 302.2894444 2.08052 302.7333333 2.115 303.1775 2.1862 303.6213889 2.23513 304.0655556 1.88516 304.2886111 2.01393 304.7327778 2.13416 305.1766667 1.95372 305.6205556 2.34303 306.0647222 2.20315 306.2877778 2.26925 306.7316667 2.10713 307.1758333 2.12814 307.62 2.36701 308.0636111 2.16943 308.2866667 1.82948 308.7308333 2.26683 309.1747222 2.1141 309.6188889 2.49 310.0630556 2.27842 310.2858333 2.20096 310.73 2.17509 311.1738889 2.15439 311.6177778 2.33172 312.0616667 2.19789 312.2847222 2.15463 312.7286111 2.27852 313.1725 1.99785 313.6166667 1.96589 314.0608333 2.49224 314.2836111 2.40053

- 24 042735

314.7277778 2.37773 315.1716667 2.46324 315.6158333 2.55963 316.3027778 2.42319 317.4113889 3.20763 317.8558333 4.52655 318.2997222 2.16813 318.5227778 1.901 318.9669444 1.79215 319.4111111 2.46673 319.855 2.19232 320.2991667 2.22674 320.5222222 2.16041 320.9663889 2.30146 321.4102778 2.35759 321.8544444 2.06147 322.2986111 2.2465 322.5216667 1.90065 322.9658333 2.42279 323.41 2.29138 323.8541667 2.21841 324.2980556 2.42145 324.5211111 2.35336 324.9652778 2.25286 325.4094444 2.25769 325.8536111 2.31652 326.2975 2.24343 326.5205556 2.28121 326.9644444 2.32713 327.4086111 2.38217 327.8527778 2.14074 328.2966667 2.30334 328.5197222 2.2444 328.9638889 2.10546 329.4080556 2.16617 329.8522222 2.30982 330.2961111 2.12672 330.5191667 2.19646 330.9633333 1.81375 331.4075 2.20783

Example 2: Comparison of feedback control and bolus feeding strategy.

Materials and methods.

Cells were cultured under feedback control and using the bolus feed strategy as described above.

Results.

In FIG. 11 shows the differences in PTMs in cells cultured using feedback and a bolus feeding strategy. Each pair of columns corresponds to the day of the series study. In each pair of columns, the left column corresponds to feedback control data and the right column corresponds to bolus feed data. It was confirmed that the feedback control strategy (left column in each column pair) reduced the % PTM level in the subsequent experiment compared to the bolus feed strategy (right column in each column pair). By controlling the nutrient concentration set point at a constant level, the % PTM was reliably maintained during production. The % PTM also decreased relative to the bolus feed strategy, thus demonstrating the ability to control the quality of the antibody due to feedback control by Raman spectroscopy.

The feedback-controlled culture systems and methods described provide for multicomponent analysis without sample removal. Real-time data enables automatic feedback control for continuous nutrient addition. The reduced steady-state concentrations of active nutrients in the bioreactor result in an antibody PTM level 50% lower than with a standard bolus feed, thus improving product quality and consistency.

Although the present invention has been described in the foregoing description with reference to certain embodiments thereof, and many details are used for illustrative purposes, it will be apparent to a person skilled in the art that the invention provides for additional embodiments, and that some of the details presented in the present description may vary significantly without deviating from the basic principles of the present invention.

All references cited in the present description are incorporated herein in their entirety. The present invention may be embodied in other specific forms without departing from its spirit or essential features, and accordingly, reference should be made to the appended claims, and not to the foregoing description, as an indication of the scope of the invention.

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Claims (35)

CLAIM 1. A method for monitoring cell culture environment conditions, comprising quantifying one or more analytes in the cell culture medium using in situ Raman spectroscopy to determine concentrations of one or more analytes; and regulation, using continuous feeding with controlled feedback during the work cycle, of the concentrations of one or more analytes in the cell culture medium to ensure a stable addition of a dose of nutrients over a time around or at the rate at which nutrients are taken up or consumed by cells in culture medium, where at least one of the predetermined analyte concentrations supports post-translational modifications of bioproducts in the cell culture medium up to 1.0-30%, where post-translational modifications include more than one post-translational modification selected from the group consisting of glycation, glycosylation, acetylation, phosphorylation, amidation, derivatization with a protecting/blocking group, proteolytic cleavage, and modification by a non-naturally occurring amino acid. 2. The method according to claim 1, characterized in that the post-translational modification includes glycation. 3. The method according to claim 1, characterized in that the bioproduct is an antibody or its antigen-binding fragment. 4. The method according to claim 1, characterized in that the bioproduct is a fusion protein. 5. The method of claim 1, wherein the cell culture medium contains mammalian cells. 6. The method of claim 5, wherein the mammalian cells comprise Chinese hamster ovary cells. 7. The method according to claim 1, characterized in that the analyte is glucose. 8. The method according to claim 7, characterized in that the predetermined glucose concentration is from 0.5 to 8.0 g/l. 9. The method according to claim 7, characterized in that the glucose concentration is from 1.0 to 3.0 g/l. 10. The method according to claim 7, characterized in that the glucose concentration is 2.0 g/l. 11. The method according to claim 7, characterized in that the glucose concentration is 1.0 g/l. 12. The method of claim 1, wherein the predetermined analyte concentrations support post-translational modifications of proteins in the cell culture medium up to 1.020%. 13. The method of claim 1, wherein the predetermined analyte concentrations support post-translational modifications of proteins in the cell culture medium up to 5.010%. 14. The method according to claim 1, characterized in that the quantitative determination of analytes is carried out continuously. 15. The method according to claim 1, characterized in that the quantitative determination of analytes is carried out periodically. 16. The method according to claim 1, characterized in that the quantitative determination of analytes is carried out at intervals. 17. The method according to claim 1, characterized in that the quantitative determination of analytes is carried out at 5-minute intervals. 18. The method according to claim 1, characterized in that the quantitative determination of analytes is carried out at 10-minute intervals. 19. The method according to claim 1, characterized in that the quantitative determination of analytes is carried out at 15-minute intervals. 20. The method according to claim 1, characterized in that the quantitative determination of analytes is carried out hourly. 21. The method according to claim 1, characterized in that the quantitative determination of analytes is carried out at least daily. 22. The method according to claim 1, characterized in that the regulation of analyte concentrations is carried out automatically. 23. The method of claim 1, wherein at least two different analytes are quantified. 24. The method of claim 1, wherein at least three different analytes are quantified. 25. The method of claim 1, wherein at least four different analytes are quantified. - 26 042735 26. A method for reducing post-translational modifications of a secreted bioproduct, comprising culturing cells secreting the bioproduct in a cell culture medium containing 0.5-8.0 g/l of glucose; gradual determination of the glucose concentration in the cell culture medium during cell culture using in situ Raman spectroscopy using continuous feed-back controlled nutrient feeding during the work cycle to ensure a steady supply of nutrients over a time period around or at the rate at which nutrients are taken up or consumed by the cells in the culture medium; regulation of glucose concentration to maintain glucose concentration up to 0.5-8.0 g / l by automatically supplying several doses of glucose per 1 hour to maintain post-translational modifications of the secreted bioproduct up to 1.0-30.0%, where post-translational modifications include more than one post-translational modification a modification selected from the group consisting of glycation, glycosylation, acetylation, phosphorylation, amidation, derivatization with a protecting/blocking group, proteolytic cleavage, and modification by a non-naturally occurring amino acid. 27. The method according to claim 26, characterized in that the glucose concentration is from 1.0 to 3.0 g/l. 28. A system for monitoring conditions of a cell culture medium, comprising one or more processors in cooperation with a computer-readable medium storing program code for execution by one or more processors to cause the system to receive data containing the concentration of one or more analytes in the cell culture medium, with using an in situ Raman spectrometer; and regulation, using continuous feeding with controlled feedback during the work cycle, of the concentrations of one or more analytes in the cell culture medium to ensure a stable addition of a nutrient dose over a time around or at the rate at which nutrients are taken up or consumed by cells in culture medium, where at least one of the predetermined concentrations of the analyte supports post-translational modifications of the bioproduct in the cell culture medium up to 1.0-30%, where the post-translational modifications include more than one post-translational modification selected from the group consisting of glycation, glycosylation, acetylation, phosphorylation, amidation, derivatization with a protecting/blocking group, proteolytic cleavage, and modification by a non-naturally occurring amino acid. 29. The system of claim 28, wherein the program code is further configured to cause the system to perform a chemometric analysis of the data. 30. The system of claim 29, wherein the chemometric analysis includes fractional least squares regression modeling. 31. The system of claim 28, wherein the program code is further configured to cause the system to perform one or more signal processing methods. 32. The system according to claim 31, characterized in that the signal processing method comprises a noise reduction method. 33. A system for reducing post-translational modifications of a secreted bioproduct, comprising one or more processors in cooperation with a computer-readable medium storing a program code for execution by one or more processors to cause the system to gradually acquire spectral data, including the concentration of glucose in the cell culture medium during cell culture protein-secreting cells from an in situ Raman analyzer using continuous feed-back controlled nutrient feeding during the work cycle to ensure a steady addition of nutrient dose over time around or at the rate at which nutrients are taken up or consumed by cells in the culture medium ; and regulating the glucose concentration to maintain the glucose concentration to a level of 0.5-8.0 g/l by automatically supplying several doses of glucose per 1 hour to maintain post-translational modifications of the secreted bioproduct up to 1.0-30.0%, where post-translational modifications include more one post-translational modification selected from the group consisting of glycation, glycosylation, acetylation, phosphorylation, amidation, derivatization with a protecting/blocking group, proteolytic cleavage, and modification by a non-naturally occurring amino acid. 34. The system of claim 33, wherein the software code is further configured such that the system correlates peaks in the spectral data with glucose concentrations. 35. The system of claim 33, wherein the program code is further configured to perform fractional least squares spectral data regression modeling. -