Biomass monitoring system and method for cell culture bioreactors

Abstract

A method for monitoring biomass during cell culture of cells in a bioreactor is provided, comprising culturing cells in the bioreactor using cell culture medium perfused through the bioreactor, measuring at least one of cellular nutrients and cellular by-products in the cell culture medium, determining at least one of a consumption rate of the cellular nutrients and an accumulation rate of the cellular by-products, and predicting the number of cells in the bioreactor at a specified culture time based on at least one of the consumption rate and the accumulation rate.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims the benefit of priority under 35 U.S.C. § 119 of U.S. Provisional Application No. 63 / 436,310, filed December 30, 2022, the contents of which are relied upon and incorporated herein by reference in their entirety. [Technical Field]

[0002] The present disclosure relates generally to systems and methods for monitoring cell cultures in bioreactor systems. Specifically, the present disclosure relates to methods, protocols, systems, and models for biomass monitoring of cell cultures in bioreactor systems. [Background technology]

[0003] The bioprocessing industry involves the large-scale cultivation of cells for the production of hormones, enzymes, antibodies, vaccines, therapeutic proteins, and cell therapies. The cell and gene therapy market is growing rapidly, with promising treatments advancing rapidly toward clinical trials and commercialization. However, a single cell therapy dose can require billions of cells or trillions of viruses. Therefore, the ability to deliver large quantities of cell product in a short time is critical for clinical success.

[0004] A significant portion of cells used in bioprocessing are anchorage-dependent, meaning that they require a surface to adhere to in order to grow and function. Traditionally, adherent cell culture is performed on two-dimensional (2D) cell-adherent surfaces incorporated into one of a number of vessel formats, such as T-flasks, Petri dishes, cell factories, cell stacking vessels, roller bottles, and other multi-layer vessels (e.g., HYPERStack® manufactured by Corning Inc.). These approaches can have significant drawbacks, including difficulty achieving high enough cell densities to enable large-scale production of therapeutics or cells.

[0005] Alternative methods have been suggested to increase the volumetric density of cultured cells. These methods include microcarrier cultures performed in stirred tanks, hollow fiber bioreactors, where cells can form large three-dimensional aggregates as they grow in the interstitial spaces between fibers, and packed-bed bioreactors. In packed-bed or fixed-bed bioreactors, a packed or immobilized cell substrate is used to provide a surface for attachment of adherent cells. Culture medium is perfused along the surface or through a semi-porous substrate to provide the nutrients and oxygen necessary for cell growth. For example, packed-bed bioreactor systems containing a packed bed of support or substrate systems for capturing cells have previously been disclosed in U.S. Patents 4,833,083, 5,501,971, and 5,510,262. Packed-bed substrates are typically made from porous particles, such as polymeric substrates or nonwoven microfibers.

[0006] One of the key problems with conventional fixed-bed bioreactors is the uneven distribution of cells within the bed. For example, a packed bed can function as a depth filter, with cells trapped primarily in the inlet region or other regions of relatively low flow rate and / or high substrate density, resulting in a gradient of cell distribution during the inoculation step. In addition, due to random fiber packing, the flow resistance and cell trapping efficiency across the cross section of the packed bed are not uniform. For example, medium flows more quickly through regions with low cell packing density and more slowly through regions with high resistance due to a high number of trapped cells. This creates a channeling effect, where nutrients and oxygen are pumped more efficiently to regions with lower volumetric cell densities, while regions with higher cell densities are maintained at suboptimal culture conditions.

[0007] Another significant drawback of conventional packed-bed systems disclosed in the prior art is the inability to efficiently recover intact, viable cells at the end of the culture process. Cell recovery is important when the end product is cells or when the bioreactor is used as part of a "seed train," in which a population of cells is grown in one vessel and then transferred to another vessel for further population growth. U.S. Patent No. 9,273,278 discloses a bioreactor design for improving the efficiency of cell recovery from a packed bed during the cell recovery step. This is based on loosening the packed-bed matrix and mechanically stirring or agitating the packed-bed particles to allow the porous matrix to collide and thus separate the cells. However, this approach is laborious and can cause significant cell damage, thereby reducing overall cell viability.

[0008] Additionally, due to the random placement of fibers in conventional packed-bed or fixed-bed substrates, it can be difficult for bioreactor users to predict cell culture performance due to culture-to-culture variability in substrate placement and / or packing. Monitoring the health or progress of a cell culture is also difficult. For example, the presence of the fixed bed itself limits options for effectively monitoring culture health and biomass production. Furthermore, the packed substrate of conventional fixed-bed bioreactors makes it very difficult or impossible to efficiently recover cells, as the cells are believed to be trapped by the packed bed, further hindering understanding of cell culture performance.

[0009] Regardless of the platform used, in the early stages of process development, users need information to better understand cell behavior, virus production, and culture progression. Upstream bioreactor process development requires identifying critical parameters and quality features, as well as defining and connecting these parameters to the final product. Understanding what these parameters are and how to scale them with higher density or larger systems is critical to process development and efficiency.

[0010] Upstream bioprocess production also meets Good Manufacturing Practice (GMP) regulations and requirements known as Process Analytical Technology (PAT). PAT is considered a tool for the design, analysis, and control of production processes. Final product quality can be assured through measurement of process parameters and product characteristics. This can include extensive online culture process monitoring, which provides a useful tool for process characterization and detection of process changes. Relevant parameters for packed-bed bioreactor process characterization and control are pH, temperature, dissolved oxygen or oxygen feed (DO2), and carbon dioxide (CO2). However, one of the identified drawbacks of packed-bed bioreactors is the difficulty of taking substrate samples to directly assess cell status and overall cell culture progress. Taking substrate samples risks contaminating the entire culture or, in the case of a heterogeneous platform, providing misleading or inaccurate data.

[0011] Fixed-bed bioreactors are increasingly being used for scale-up in adherent cell culture. Biomass monitoring is an important tool for designing, analyzing, and controlling pharmaceutical manufacturing processes when cell culture is involved. For suspension cell cultures, biomass monitoring can be achieved using optical or electrical approaches. However, for adherent cell cultures using fixed-bed bioreactors, no validated approaches or sensors are available for satisfactory online biomass monitoring. Historically, substrate (e.g., glucose) consumption rates have been proposed as useful for understanding the kinetics of cell growth. However, because glucose consumption rates (GCRs) are affected by many factors other than viable cell number, there are no established protocols, methods, or models for obtaining and using effective substrate consumption and metabolite accumulation rates to calculate and predict biomass.

[0012] While viral vector production for early clinical trials is possible with existing platforms, a platform capable of producing larger quantities of high-quality product is needed to reach later-stage commercial manufacturing scale. Additionally, systems and methods are needed to collect specific measurable parameters from cell cultures during bioreactor runs, allowing for better real-time control of aspects of the culture process and the detection and diagnosis of abnormal culture conditions. Summary of the Invention

[0013] According to an embodiment of the present disclosure, a method for monitoring biomass during cell culture of cells in a bioreactor is provided. The method includes culturing cells in the bioreactor using cell culture medium perfused through the bioreactor, measuring at least one of cellular nutrients and cellular by-products in the cell culture medium, determining at least one of a consumption rate of the cellular nutrients and an accumulation rate of the cellular by-products, and predicting the number of cells in the bioreactor at a specified culture time based on at least one of the consumption rate and the accumulation rate. According to one aspect of the embodiment, the bioreactor is a fixed-bed bioreactor including a substrate configured to culture cells attached to a surface of the substrate. The at least one cellular nutrient may be glucose or glutamine, and the at least one cellular by-product may be lactate or ammonia. According to one aspect of the embodiment, the cell culture medium may be a glucose- or glutamine-rich cell culture medium.

[0014] According to one aspect of the embodiment, measuring at least one of cellular nutrients and cellular by-products in a cell culture medium includes performing multiple measurements of the cellular nutrients or cellular by-products, the multiple measurements being separated by a measurement interval shorter than the doubling time of the cells in the cell culture. The measurement interval is equal to or greater than a minimum interval time, which is the time at which a change in the level of the cellular nutrients or cellular by-products exceeds the measurement tolerance for measuring the cellular nutrients or cellular by-products. In one aspect of the embodiment, the minimum interval time is about 30 minutes or more, 1 hour or more, 2 hours or more, 3 hours or more, 4 hours or more, 5 hours or more, 6 hours or more, 7 hours or more, 8 hours or more, 9 hours or more, 10 hours or more, 11 hours or more, 12 hours or more, 13 hours or more, 14 hours or more, 15 hours or more, 16 hours or more, 17 hours or more, 18 hours or more, 19 hours or more, or 20 hours or more. Measuring cellular nutrients in a cell culture medium can include measuring cellular nutrients multiple times per day of the cell culture. Measuring the cell by-products in the cell culture medium can include measuring the cell by-products multiple times per day of the cell culture.

[0015] According to one aspect of the embodiment, predicting cell number includes calculating biomass at a specified culture time using a mathematical model. Measuring can include using an in-line sensor in a cell culture medium perfusion line. Measuring can also include using offline measurements of samples of the cell culture medium.

[0016] According to one aspect of the embodiment, the method further includes, after determining the consumption rate and accumulation rate, comparing at least one of the consumption rate of a first cellular nutrient and the accumulation rate of a first cellular by-product with at least one of the consumption rate of a second cellular nutrient and the accumulation rate of a second cellular by-product. The comparison may include comparing the glucose consumption rate with the glutamine consumption rate, comparing the glucose consumption rate with the ammonia accumulation rate, comparing the lactate accumulation rate with the glutamine consumption rate, and / or comparing the lactate accumulation rate with the ammonia accumulation rate. The method may further include determining an abnormality in the cell culture based on the comparison. The method may further include seeding the cells into the bioreactor at a seeding density. The method may further include supplying fresh cell culture medium to the bioreactor, and the measurement may include a first measurement, the first measurement being performed at least one hour after supplying the fresh cell culture medium. According to one aspect of the embodiment, the cell number N t The prediction of N t =N seed e kt wherein N seed is the number of cells seeded into the bioreactor, k is the cell growth rate, and t is the time at which the cell number is predicted. [Brief explanation of the drawings]

[0017] [Figure 1] FIG. 1 is a schematic diagram of a cell culture system, according to one or more embodiments. [Figure 2]1 illustrates operations for controlling perfusion flow rate in a cell culture system according to one or more embodiments. [Figure 3] 10 is a graph of bioreactor perfusion flow rate and oxygen concentration over time during an exemplary bioreactor run using the bioreactor system according to FIG. 1 in accordance with one or more embodiments. [Figure 4A] FIG. 4 is a graph of dissolved oxygen concentration over time during the bioreactor run of FIG. 3. [Figure 4B] FIG. 4 is a graph of pH over time during the bioreactor run of FIG. 3. [Figure 4C] FIG. 4 is a graph of media conditioned temperature over time during the bioreactor run of FIG. 3. [Figure 5] 4 is a graph of oxygen consumption over time of a packed-bed cell culture during the bioreactor run of FIG. 3, including the slope α of the curve. [Figure 6] 1 is a graph of slope α versus cell seeding density for a bioreactor according to one or more embodiments. [Figure 7] 1 is a graph of slope α versus cell culture substrate surface area according to one or more embodiments. [Figure 8] 1 is a graph of cell recovery yield versus slope α, according to one or more embodiments. [Figure 9] 1 is a graph of the concentration profile of glucose in an experimental culture over a four-day period, according to an embodiment. [Figure 10] 1 is a graph of the concentration profile of lactate in an experimental culture over a four-day period, according to an embodiment. [Figure 11] 1 is a graph of the total amount of glucose consumed V(C0-Ct) as a function of time of day according to an exemplary embodiment. [Figure 12] 1 is a graph of the total daily glucose consumption rate rN0 as an exponential function over the culture period, according to an exemplary embodiment. [Figure 13] FIG. 1 is a diagram of an experimental setup, according to an embodiment. [Figure 14A] 1 is a graph of the total daily glucose consumption rate rN0 as an exponential function over the culture period, according to an embodiment. [Figure 14B] 1 is a graph of the daily total glutamine consumption rate rN0 as an exponential function over the culture period, according to an embodiment. [Figure 14C] 1 is a graph of the daily total lactate accumulation rate rN0 as an exponential function over the culture period, according to an embodiment. [Figure 14D] 1 is a graph of the total daily ammonia accumulation rate rN0 as an exponential function over the culture period, according to an embodiment. [Figure 15] 1 is a graph showing a plot of glucose consumption over time as fit to an exponential model, according to an embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0018] Various embodiments of the present disclosure will now be described in detail with reference to the drawings, where available. References to various embodiments do not limit the scope of the invention, which is limited only by the claims appended hereto. Additionally, any examples set forth herein are not limiting and merely describe some of the many possible embodiments of the claimed invention.

[0019] Embodiments of the present disclosure include systems and methods for monitoring and controlling cell cultures. The present disclosure describes systems and methods for collecting specific signal signatures during bioreactor run, having better real-time control of critical aspects, and detecting and diagnosing abnormal culture conditions. The identified signature parameters of cell cultures described in this disclosure can be used as tools for implementing process analytical techniques and online monitoring of upstream processes. As a result, optimized cell culture production processes can be established through the routine and reproducible development of signature operating parameters.

[0020] According to embodiments of the present disclosure, bioreactor systems and methods are provided for monitoring the status of a cell culture within a bioreactor system during a cell culture run. Specifically, the embodiments describe a bioreactor system having an outlet sensor at the outlet of the cell culture bioreactor or vessel, a system enabling real-time signal collection and processing from this and / or other sensors, and a method of cell culture using such a system. For example, the methods include using such sensor signals as trigger points for critical cell culture process steps or to predict the expected health or assess the current health of a cell culture for a particular bioreactor size or seeding density over time. Advantages of these systems and methods include the ability to actively monitor bioreactor status in real time without having to physically sample the packed-bed substrate for offline analysis. Continuous monitoring of bioreactor status also allows end users to proactively adjust bioprocess steps that depend on the progress of the culture process within the packed-bed bioreactor. The ability to characterize and log the progress of a bioprocess run further allows end users to monitor and record the batch-to-batch consistency of the process. This type of tracking of progress and consistency between cell culture runs can be incredibly advantageous.

[0021] Traditional large-scale cell culture bioreactors have used different types of packed-bed bioreactors. These packed beds typically contain a porous matrix to retain adherent or suspended cells and support their growth and proliferation. Because the packed-bed matrix provides a high surface area-to-volume ratio, cell densities can be higher than in other systems. However, packed beds often function as depth filters, where cells become physically trapped or entangled in the matrix fibers. Therefore, due to the linear flow of cell inoculum through the packed bed, cells are subject to uneven distribution within the packed bed, leading to variations in cell density throughout the depth or width of the packed bed. For example, cell density may be higher in the inlet region of the bioreactor and significantly lower closer to the outlet. In another example, unevenness in the packed bed creates a channeling effect, where cell culture medium preferentially flows to certain regions of the bed while being restricted from reaching other regions of the bed, again resulting in uneven cell distribution and inconsistent or inconsistent medium or nutrient distribution. This uneven distribution of cells inside the packed bed can significantly hinder the scalability and predictability of such bioreactors in bioprocess manufacturing, leading to reduced efficiency in terms of cell growth or viral vector production per unit surface area or volume of the packed bed.

[0022] Another problem encountered in packed-bed bioreactors disclosed in the prior art is the channeling effect, as discussed above. Due to the random nature of the packed nonwoven fibers, the local fiber density at any given cross-section of the packed bed is not uniform. In areas of low fiber density (high bed permeability), medium flow is fast, while in areas of high fiber density (low bed permeability), it is much slower. The resulting uneven medium perfusion across the packed bed creates a channeling effect, which manifests as gradients of important nutrients and metabolites that negatively impact overall cell culture and bioreactor performance. Cells located in areas of low medium perfusion become starved and very frequently die from nutrient deprivation or metabolic toxicity. Cell recovery is yet another problem encountered when bioreactors packed with nonwoven fibrous scaffolds are used. Due to the packed bed acting as a depth filter, cells released at the end of the cell culture process are trapped inside the packed bed, resulting in very low cell recovery rates. This significantly limits the use of such bioreactors in bioprocesses where live cells are the product. Therefore, non-uniformity leads to regions with different exposure to flow and shear, effectively reducing the usable cell culture area and causing non-uniform cultures, hindering transfer efficiency and cell release.

[0023] To address these and other issues with existing cell culture solutions, embodiments of the present disclosure provide bioreactor systems, cell growth substrates, matrices for such substrates, and methods of using such bioreactor systems and substrates that enable efficient and high-yield cell culture and production of cell products (e.g., proteins, antibodies, viral particles) for anchorage-dependent cells. Embodiments include porous cell culture substrates made from an ordered and regular array of porous substrate materials that enable uniform cell seeding and medium / nutrient perfusion, as well as efficient cell harvest. Embodiments also enable scalable cell culture solutions with substrates and bioreactors that can seed and grow cells and / or harvest cell products from process development scale to full production size scale without sacrificing the uniform performance of the embodiments. For example, in some embodiments, bioreactors can achieve equivalent viral genomes per unit surface area of ​​the substrate (VG / cm) across production scales. 2 ) can be easily scaled from process development scale to production scale. The recoverability and scalability of embodiments herein enable their use in efficient seed trains for growing cell populations at multiple scales on the same cell substrate. In addition, embodiments herein provide cell culture substrates with high surface areas that, in combination with other features described, enable high-yield cell culture solutions. In some embodiments, for example, the cell culture substrates and / or bioreactors discussed herein can be used to grow 10 cells per batch. 16 ~10 pieces 18 It is possible to produce 100 viral genomes (VG).

[0024] An embodiment of the present disclosure is a method for producing approximately 10 14 More than 10 viral genomes per batch 15 More than 10 viral genomes per batch 16 More than 10 viral genomes per batch 17 More than 10 viral genomes, or up to approximately g per batch 16A practical size viral vector platform capable of producing viral genomes on the scale of about 10 or more viral genomes can be realized. In some embodiments, production is at a rate of about 10 per batch. 15 pieces ~ about 10 18 For example, in some embodiments, the viral genome yield is about 10 15 pieces ~ about 10 16 viral genomes or batches, or approximately 10 per batch 16 pieces ~ about 10 19 viral genomes, or approximately 10 per batch 16 ~10 pieces 18 viral genomes, or approximately 10 per batch 17 pieces ~ about 10 19 viral genomes, or approximately 10 per batch 18 pieces ~ about 10 19 viral genomes, or approximately 10 per batch 18 There can be more than one viral genome.

[0025] Additionally, the embodiments disclosed herein enable not only cell attachment and growth on cell culture substrates, but also viable recovery of cultured cells. The inability to recover viable cells is a significant drawback of current platforms, leading to difficulties in establishing and maintaining sufficient numbers of cells for production capacity. According to one aspect of the disclosed embodiments, viable cells can be recovered from cell culture substrates, including 80% to 100% viable, or about 85% to about 99% viable, or about 90% to about 99% viable. For example, the recovered cells may be at least 80% viable, at least 85% viable, at least 90% viable, at least 91% viable, at least 92% viable, at least 93% viable, at least 94% viable, at least 95% viable, at least 96% viable, at least 97% viable, at least 98% viable, or at least 99% viable. Cells can be released from the cell culture substrate using, for example, trypsin, TrypLE™ (manufactured by Thermo Fisher Scientific), or Accutase® (manufactured by Innovative Cell Technologies).

[0026] According to one or more embodiments, a cell culture bioreactor can include a cell culture substrate within the bioreactor vessel. The substrate can be used in a packed-bed bioreactor configuration or other configuration within the three-dimensional culture chamber of the bioreactor vessel. Due to contamination concerns, the vessel can be a disposable vessel that can be discarded after use.

[0027] As shown in FIG. 1 , embodiments of the present disclosure include a bioreactor system 100 for culturing cells within a cell culture vessel 110. The cell culture vessel includes an inlet 112 and an outlet 114 fluidly connected to an internal reservoir 111 of the cell culture vessel 110. The internal reservoir 111 includes a space for containing and culturing cells and may also include a cell culture substrate (not shown) on which adhesive-based cells can be cultured. In some embodiments, the inlet 112 is located at one end of the cell culture vessel 110 for the introduction of medium, cells, and / or nutrients into the cell culture vessel 110, and the outlet 114 is located at the opposite end for the removal of medium, cells, and / or cell products from the cell culture vessel 110. The substrate within the internal reservoir can take many forms, some of which are discussed herein by way of example. Some embodiments may use one or both of the inlet 112 and the outlet 114 to flow medium, cells, or other contents into or out of the cell culture vessel 110. For example, inlet 112 may be used to flow medium or cells into cell culture vessel 110 during cell seeding, perfusion, and / or incubation phases, but may also be used to remove one or more of medium, cells, or cell products through inlet 112 during harvest phases. Therefore, the terms “inlet” and “outlet” are not intended to limit the function of these openings but should generally be understood to refer to ports used for fluid input and output, respectively, during the normal course of cell growth. Outlet sensor 118 is provided at outlet 114 of cell culture vessel 110. As used herein, “at outlet” can refer to a sensor that receives medium from outlet 114 and provides an in-line fluid flow path that returns the medium to another part of the system (e.g., a medium conditioning vessel), or a sensor provided within cell culture vessel 110, but preferably after a cell culture substrate, packed bed, or other cell culture zone within cell culture vessel 110. In this manner, outlet sensor 114 can detect characteristics of the medium after it has passed through a packed bed, cell culture substrate, or other cell culture zone.

[0028] The system further includes a medium conditioning vessel (MCV) 120 capable of holding and conditioning cell culture medium 122. Fluid flow paths 142, 144 deliver conditioned medium 112 from the MCV 120 to the cell culture vessel 110 and return spent medium from the cell culture vessel 110 to the MCV 120. The MCV 120 can be coupled to multiple sensors and / or regulation components 124a, 124b, 124c, 124d used to sense properties of the cell culture medium and adjust or regulate the medium as needed during cell culture. These include, but are not limited to, sensors and supplies of dissolved gases (e.g., O, air, CO, N), pH sensors, an oxygen generator / gas sparging unit, temperature probes and temperature control devices, and nutrient and base addition ports. The gas mixture supplied to the sparging unit can be controlled by gas flow controllers for N, O, and CO gases. The medium conditioning vessel 120 can also house an impeller for medium mixing.

[0029] The system may also include a medium conditioning control unit 130 operably connected to a plurality of sensors and / or regulating components 124a, 124b, 124c, 124d and configured to process signals detected from the sensors and / or control the regulating components to regulate the medium 122 within the MCV 120. The medium conditioning control unit 130 may also be operably connected to a pump 150 to control the pump 150 and, therefore, the rate of fluid flow through the fluid channels 142, 144 and perfusion through the cell culture vessel 110. Alternatively, the pump 150 and outlet sensor 118 may be directly connected or connected via a perfusion control unit separate from the medium conditioning control unit 130. In some embodiments herein, a peristaltic pump is used, although other pump types are possible. As shown in FIG. 1 , the medium conditioning vessel 120 is provided as a separate vessel from the bioreactor vessel 110. This can have advantages in that the medium can be conditioned separately from where the cells are cultured and then the conditioned medium can be supplied to the cell culture space. However, in some embodiments, the medium conditioning can occur within the bioreactor vessel 110.

[0030] In some embodiments, medium conditioning control unit 130 can be used to maintain stable or desired levels of various parameters of cell culture medium 122 within MCV 120, thus maintaining bulk medium 122 at a particular temperature, oxygen saturation level, pH, and CO2 concentration. For example, for a given cell line or stage of a cell culture process, it may be desirable for cell culture medium 122 to have a certain temperature, pH, dissolved gas content, or nutrient level for optimal cell health and / or growth. Medium 122 from medium conditioning vessel 120 is delivered to cell culture vessel 110 via inlet 112, which may also include an injection port for a cell inoculum to initiate cell seeding and cultivation. Cell culture vessel 110 may also include outlet 114, through which cell culture medium 122 exits vessel 110. Additionally, cells or cell product may be discharged through outlet 114. An outlet sensor 118 is provided to analyze the contents of the effluent from cell culture vessel 110. As described above, medium conditioning control unit 130 can receive a signal from outlet sensor 118 (e.g., an O sensor) and, based on the signal, adjust the flow of fluid through cell culture vessel 110 by sending a signal to pump 150 (e.g., a peristaltic pump) upstream of inlet 112 of cell culture vessel 110. Thus, based on one or a combination of factors measured by outlet sensor 118, pump 150 can control the flow to cell culture vessel 110 to obtain desired cell culture conditions. Because cell culture medium 122 in MCV 120 can be maintained at a desired rate, changes in flow rate can effectively address any needs of the cells in cell culture vessel 110. For example, because cell culture medium 122 leaving MCV 120 is conditioned for optimal performance, the medium entering via inlet 112 should meet optimal requirements for the medium.If outlet sensor 118 detects a less than desirable level in the cell culture medium present in cell culture vessel 110 at outlet 114, this can mean, for example, that the cells in the culture are consuming a certain amount of dissolved gases (e.g., oxygen) or cell nutrients in the medium, and that at least some cells (i.e., cells near the outlet where the medium is most depleted) are not being optimally cultured. Thus, for example, if the level of dissolved oxygen in the cell culture medium at outlet sensor 118 is lower than optimal (e.g., for a given cell type, culture stage, etc.), the perfusion flow rate can be increased to provide a higher proportion of conditioned medium, which should cause all cells (even those near the outlet) to be cultured under optimal conditions.

[0031] The medium perfusion rate is controlled by medium conditioning control unit 130, which collects and compares sensor signals from medium conditioning vessel 120 and sensors 124a-124d in MCV 120, as well as outlet sensor 118. Due to the packing flow nature of medium perfusion through the packed bed substrate in cell culture vessel 110, nutrient, pH, and oxygen gradients develop along the packed bed. The bioreactor perfusion flow rate can be automatically controlled by medium conditioning control unit 130, which is operably connected to pump 150. This control scheme is depicted in the flow diagram of FIG. 2. In sensing and control process 200 shown in FIG. 2, optimal conditions are predetermined by a round of bioreactor optimization runs at step 202. These optimal conditions include minimum pH, minimum oxygen level, and nutrients (e.g., glucose) at outlet sensor 118, as well as pH, oxygen levels, and nutrients (e.g., glucose) at MCV 120. These parameters are provided by way of example; one skilled in the art will appreciate that other parameters may be relevant to a given application (e.g., temperature). The pH and oxygen levels in the MCV 120 are independently controlled based on input from respective sensors located within the MCV 120. Nutrient (e.g., glucose) levels are maintained in the MCV 120 based in part on signals from the outlet sensor 118, such that the nutrient levels in the MCV 120 are maintained higher than the nutrient levels detected by the outlet sensor 118. During a cell culture run, steps 204 and 206 are performed in parallel. In step 204, the outlet sensor 118 is used to measure conditions (e.g., pH, O2, and glucose) at the outlet 114 of the cell culture vessel 110. In step 206, sensors 124a-124d are used to measure conditions (e.g., pH, O2, and glucose) in the MCV 120. In step 208, the perfusion pump 150 is controlled by the control unit based on input from both steps 202 and 204.In step 210, it is determined whether the pH at the outlet sensor 118 is greater than the minimum pH determined in step 202, whether the oxygen at the outlet sensor 118 is greater than the minimum oxygen level determined in step 202, and whether the nutrient level in the MCV 120 is greater than the nutrient level at the outlet sensor 118, and whether the nutrient level at the outlet sensor is greater than the minimum level determined in step 202. If all of these conditions are met, perfusion by the pump continues at the current flow rate (step 212). If these conditions are not met, step 214 queries whether the current perfusion rate is less than or equal to the maximum flow rate. If not, the system reevaluates the minimum pH, O2, and glucose at the outlet 114 or increases the nutrient levels in the MCV 120. However, if the current perfusion rate is less than the maximum flow rate, step 218 instructs the system to increase the perfusion flow rate. The sensing and control scheme 200 returns to the top of the chart in FIG. 2 for steps 204 and 206.

[0032] Thus, according to embodiments of the present disclosure, it is possible to directly measure nutrient and / or oxygen consumption of cells within a cell culture vessel and respond in a manner that maintains desirable conditions for the cells. For example, during a cell culture run, medium conditioning control unit 130 is preprogrammed to maintain a specific level of oxygen saturation in the bulk medium volume relative to atmospheric saturation, with that level in the MCV measured by sensors 124a-124d. Placement of a second sensor (outlet sensor 118) at bioreactor outlet 114 measures the oxygen saturation level in the medium as it leaves the cell culture vessel. Using these sensors and controls, a constant oxygen depletion level can be maintained within physiological conditions by automatic adjustment of the perfusion flow rate.

[0033] According to some embodiments of the present disclosure, systems and methods for improved process monitoring are provided that can accelerate process development of cell culture protocols and improve the efficiency and reproducibility of cell culture processes. The ability to characterize and log the progress of these bioprocess runs allows end users to monitor and record the batch-to-batch consistency of the process. Relevant parameters for process characterization are cell growth, cell quality, medium conditions (temperature, pH, pO2, and pCO2), and metabolite concentrations (glucose, lactate, glutamine, and ammonium). While bulk medium temperature, pH, pO2, and pCO2 are routinely controlled online in cell cultures, online monitoring of these and other process parameters in dynamic systems is not currently performed. Therefore, embodiments of the present disclosure provide systems and methods for obtaining oxygen consumption parameters in, for example, a packed-bed perfusion bioreactor and demonstrating that such parameters are characteristic of a given bioprocess and can therefore be used as signature parameters for the given bioprocess.

[0034] As discussed above, FIG. 1 shows a schematic diagram of a bioreactor system (e.g., a fixed-bed perfusion bioreactor). Cell culture medium entering the cell culture vessel 110 through the inlet 112 can have 100% atmospheric oxygen saturation. Alternatively, according to Henry's law, the concentration of a gas in the liquid phase is equal to the Henry's law constant (k) multiplied by the partial pressure of that gas in the gas phase. Therefore, oxygen saturation can be presented as the concentration of oxygen in the cell culture medium, with 100% saturation at standard atmospheric pressure equaling 204 μM. During passage of the medium through the cell culture vessel, dissolved oxygen is used by the immobilized cells, decreasing its concentration in the cell culture medium. Different cell types have different oxygen consumption rates. However, a bioreactor system with the sensing and control system of the present disclosure allows a user to run a process at a specified oxygen concentration at the bioreactor outlet measured by the outlet sensor 118, with the medium conditioning and perfusion control system operating according to the logic shown in the flow diagram of FIG. 2.

[0035] To illustrate this sensing and control of the bioreactor system, several examples are presented. Specifically, FIG. 3 shows a typical graph (302) of the percent dissolved oxygen over time during a bioreactor run, as measured by the outlet sensor 118, and a typical graph (304) of the corresponding perfusion rate (ml / min) of the medium in the system. The flow rate was automatically controlled by a peristaltic perfusion flow control unit. In this example, the bioreactor was seeded with cells at 0:00 hours, and the user set the minimum oxygen saturation level of the medium at the outlet sensor 118 to 30%. The initial medium perfusion flow rate was set to 33 ml / min. The inoculum cells were then provided into the bioreactor system, where they began to attach to the packed bed substrate and proliferate. Accordingly, oxygen consumption increased, and the saturation level of the medium at the outlet decreased to approximately 30% as of 26 hours after seeding. As a result, the control system automatically increased the perfusion flow rate to maintain that minimum 30% oxygen saturation level at the bioreactor outlet 114. At 72 hours post-inoculation, the user reduced the minimum outlet oxygen saturation level setting from 30% to 15% and allowed the cell culture to proceed in automatic mode. Note that medium conditions were independently maintained in the medium conditioning vessel by the medium conditioning control unit. Examples of medium conditioning vessel parameters are presented in Figures 4A, 4B, and 4C. Specifically, Figure 4A shows the percentage of oxygen in the medium of an MCV over time. Figure 4B shows the pH of that medium over time, and Figure 4C shows the temperature of that medium over time.

[0036] As described above, embodiments include the real-time processing of signals and control of a bioreactor system, as well as the development of a characteristic signal signature for a particular bioreactor run that can be used as an analytical tool to compare and validate independent bioreactor runs. The characteristic signal signature can therefore be used to assess the health of cells cultured inside the cell culture vessel and to make decisions regarding the next process step occurring during the bioreactor run. For example, as discussed above, FIG. 3 shows the recorded oxygen saturation concentration at the bioreactor outlet 114 over time during a cell culture process. The oxygen concentration level at the bioreactor outlet decreased from approximately 82% at the time 0 to approximately 30% during the first 26 hours of the bioreactor run. While this was occurring, the oxygen concentration at the bioreactor inlet 112 remained constant, as shown by the value detected by the MCV 120 in FIG. 4A. Using the oxygen concentrations at the inlet and outlet, the oxygen consumption rate of the cells in the culture can be determined using Equation 1.

number

[0037] This oxygen consumption rate over time (in hours) is shown in Figure 5 (expressed as % as / min). Figure 5 also shows a dotted line representing the approximate slope α of the line, which can be used as a characteristic signal signature of the bioreactor run. In other words, the value of the slope α of the data in Figure 5 directly reflects the progress of the cell culture inside the bioreactor system. This value can be used as a process analytical tool to control and describe upstream bioprocesses. The following example shows that the slope α from a graph similar to Figure 5 directly relates to the health of the cell culture and the health of the biomass inside the packed bed substrate.

[0038] To illustrate the use of the parameter α, multiple cell culture runs were performed using bioreactor systems with different sizes of cell culture substrates, bed heights, and cell seeding densities. Table 1 summarizes the parameters for the seven cell culture runs used. [Table 1]

[0039] As can be seen in Table 1, multiple bioreactors were inoculated with different cell numbers ranging from 151 to 453 million cells per bioreactor. Three identical bioreactors (Bioreactors 1, 2, and 3) had the same packed bed height (2.7 cm), were inoculated with the same number of cells (151 million cells per bioreactor), and had the same total packed bed surface area (6780 cm). 2 ) and seeding density (22,222 cells / cm 2 Three other identical bioreactors (numbers 4, 5, and 6) had the same packed bed height (5.4 cm), were inoculated with the same number of cells (302 million cells per bioreactor), and had the same total packed bed surface area (13,560 cm). 2 ) and seeding density (22,227 cells / cm 2 The final bioreactor (number 7) had a bed height (8.1 cm), total cells seeded (453 million cells), and packed bed surface area (20,340 cm). 2 ) but at a similar seeding density (22,222 cells / cm 2) during the 5-day cultivation process, bulk medium conditions (pH, DO2, temperature, and CO2) were maintained in automatic mode by a control system according to one or more embodiments described herein. The control system operated the medium conditioning vessel to maintain the medium conditions, and Figures 4A-4C represent typical measurements of the controlled medium. The medium perfusion flow rate of the bioreactor system was automatically maintained to maintain the DO2 at the bioreactor outlet at a specific saturation level. Again, the graph shown in Figure 3 is typical of the perfusion flow rate and medium outlet DO2 found during these experiments. From graphs such as Figure 3, values ​​of total oxygen consumption similar to those shown in Figure 5 were derived. The slopes of the linear curve fits of these graphs (such as α in Figure 5) were determined for each bioreactor run and are presented in the last column (slope α) of Table 1. The value of slope α determined above can be used as a process analysis tool to control and describe upstream bioprocesses and to predict biomass production inside the packed-bed substrate.

[0040] For example, Figures 6, 7, and 8 plot the α values ​​in Table 1 against seeded cell number, packed-bed surface area, and harvest density, respectively. The linearity of these graphs can be used to predict cell culture response according to various cell culture system parameters. For example, the linearity of the graph in Figure 6 indicates that the upstream process developed for small-scale bioreactors 1 and 2 in Table 1 can be scaled two- and three-fold for bioreactors 4 through 7. Therefore, constant monitoring and logging of slope α values ​​can help determine the scalability of the upstream process. An alternative method for validating process scalability is to plot slope α against bioreactor surface area, as shown in Figure 7. The orange data points in Figures 6 and 7 correspond to the failure of bioreactor 3 from Table 1 (discussed below).

[0041] Monitoring the slope α value during bioreactor run serves as a characteristic signal signature reflecting the health and expansion of the cell culture. For example, as shown in Table 1, bioreactors 1, 2, and 3 were inoculated with the same number of cells. A characteristic signal signature (slope α) was measured for all bioreactors. Figure 8 shows that real-time monitoring of slope α can be used to compare the performance of identical bioreactors and predict bioreactor productivity. From Figure 8, it can be seen that the run of bioreactor 3 was in suboptimal conditions, resulting in the lowest cell yield. Therefore, monitoring the slope α value during bioprocess run can be used as a characteristic signal signature for a given process, and any process deviations can be detected if the predetermined value is not within the range defined during process development optimization.

[0042] According to some embodiments, the medium conditioning vessel is controlled by a controller to provide the appropriate temperature, pH, O2, and nutrients. In some embodiments, the bioreactor can also be controlled by the controller, while in other embodiments, the bioreactor is provided in a separate perfusion circuit, where a pump is used to control the flow rate of the medium through the perfusion circuit based on detection of O2 at or near the outlet of the bioreactor.

[0043] The cell culture substrate can be arranged in a number of configurations within the culture chamber, depending on the desired system. For example, in one or more embodiments, the system includes one or more layers of substrate having a width that spans the width of the defined cell culture space in the culture chamber. Multiple layers of substrate can be stacked in this manner to a predetermined height. The substrate layers can be arranged such that a first side and a second side of one or more layers are perpendicular to the direction of bulk flow of culture medium through the defined culture space in the culture chamber, or the first side and a second side of one or more layers can be parallel to the direction of bulk flow. In one or more embodiments, the cell culture substrate includes one or more substrate layers in a first orientation relative to the bulk flow and one or more other layers in a second orientation different from the first orientation. For example, various layers can have first and second sides that are parallel or perpendicular to the direction of bulk flow, or at an angle therebetween.

[0044] In one or more embodiments, the cell culture system includes multiple separate pieces of cell culture substrate in a packed-bed configuration, where the length and / or width of the substrate pieces are small relative to the culture chamber. As used herein, a substrate piece is considered to have a length and / or width that is small relative to the culture chamber when the length and / or width of the substrate piece is about 50% or less of the length and / or width of the culture space. Thus, the cell culture system can include multiple substrate pieces packed into the culture space in a desired arrangement. The arrangement of the substrate pieces can be random or semi-random, or can have a predetermined order or alignment, such as pieces oriented in a substantially similar orientation (e.g., horizontally, vertically, or at an angle of 0° to 90° relative to the direction of bulk flow).

[0045] As used herein, "defined culture space" refers to the space within a culture chamber occupied by a cell culture substrate and in which cell seeding and / or culturing occurs. The defined culture space can fill substantially the entire culture chamber or may occupy a portion of the space within the culture chamber. As used herein, "bulk flow direction" is defined as the direction of bulk mass flow of fluid or culture medium through or across the cell culture substrate during cell culturing and / or during flow of culture medium into or out of the culture chamber.

[0046] In some embodiments of the present disclosure, there is only a single bulk flow direction within the defined culture space, packed bed, and / or bioreactor vessel, such that the flow of liquid or medium proceeds primarily in one direction from the bioreactor inlet through the packed bed to the bioreactor outlet. The flow of liquid or medium is uninterrupted by complex flow paths within the packed bed space and proceeds primarily in one direction through the packed bed. This avoids the complex flow paths used in some conventional bioreactors, which often use flow spacers, separators, or channels to help distribute cell culture medium through the cell culture substrate due to inherent heterogeneity in the bioreactor or cell culture substrate. However, in embodiments of the present disclosure, such complex flow paths are not required, and medium flow can be maintained in a single direction from the bioreactor inlet to the bioreactor outlet. The above is not intended to exclude the use of flow distribution plates at the inlets and outlets of the bioreactor plate, which can be used to distribute fluids and / or control pressure differentials across the width of the bioreactor vessel within the reactor, but do not otherwise affect the direction of bulk flow through the packed bed and / or within the cell culture space inside the bioreactor vessel.

[0047] The packed-bed cell culture substrate of one or more embodiments can include a substrate material constructed to have a uniform and regular porous structure. The substrate may be referred to as a "structured" substrate, meaning that the substrate has a physical structure that is not random but instead regular according to defined parameters. In one or more embodiments, the structured substrate includes a plurality of openings that define the porosity of the substrate, the plurality of openings being arranged in a regular or uniform pattern within each substrate piece or layer. In one or more embodiments, the packed-bed cell culture substrate can include a woven cell culture mesh substrate that does not include any other form of cell culture substrate disposed or present within the cell culture substrate. That is, the woven cell culture mesh substrate of the presently disclosed embodiments is an effective cell culture substrate that does not require the type of irregular, non-woven substrate used in existing solutions. This allows for simplified design and construction of cell culture systems while providing a high-density cell culture substrate with other advantages discussed herein related to flow uniformity, recovery, etc.

[0048] In one or more embodiments, the substrates, when assembled in a packed-bed or other bioreactor, have good mechanical strength and provide a structurally defined surface area for the attachment and growth of adherent cells, forming a highly uniform, multiplicity, interconnected fluidic network. In certain embodiments, mechanically stable, non-degradable woven meshes can be used as substrates to support the production of adherent cells. The cell culture substrates disclosed herein support the attachment and growth of anchorage-dependent cells in a high-volume-density format. Uniform cell seeding of such substrates and efficient recovery of cells or other bioreactor products are feasible. Additionally, embodiments of the present disclosure provide uniform cell distribution during the inoculation step, supporting cell culture to achieve confluent monolayers or multilayers of adherent cells on the disclosed substrates, avoiding the formation of large and / or uncontrollable 3D cellular aggregates with limited nutrient diffusion and increased metabolite concentrations. Therefore, the substrates eliminate diffusion limitations during bioreactor operation. Additionally, the substrates enable easy and efficient cell recovery from the bioreactor. The structurally defined substrate of one or more embodiments allows for complete and consistent cell recovery from the packed bed of the bioreactor.

[0049] The use of structurally defined culture substrates with sufficient rigidity allows for uniformity of high flow resistance across the substrate or packed bed. According to various embodiments, the substrate can be deployed in a monolayer or multilayer format. This flexibility eliminates diffusion limitations and provides uniform delivery of nutrients and oxygen to cells attached to the substrate. In addition, the open substrate lacks any cell-confining regions in a packed-bed configuration, allowing for complete cell recovery with high viability at the end of the culture. The substrate also provides uniformity of packing for packed beds, enabling direct scalability from process development units to large-scale industrial bioprocessing units. The ability to directly recover cells from packed beds eliminates the need to resuspend the substrate in a stirred or mechanically shaken vessel, which adds complexity and can impose harmful shear stress on the cells. Furthermore, the high packing density of the cell culture substrate allows for high bioprocess productivity at manageable processing volumes at an industrial scale.

[0050] In contrast to existing cell culture substrates (i.e., nonwoven substrates with random fibers) used in cell culture bioreactors, embodiments of the present disclosure include cell culture substrates with a defined and ordered structure. The defined and ordered structure enables consistent and predictable cell culture results. Additionally, the substrate has an open porous structure that prevents cell entrapment and allows uniform flow through the packed bed. This structure enables improved cell seeding, nutrient delivery, cell growth, and cell recovery. According to one or more specific embodiments, the substrate is formed of a substrate material having a thin, sheet-like structure with first and second sides separated by a relatively small thickness, such that the thickness of the sheet is small relative to the width and / or length of the first and second sides of the substrate. Additionally, multiple holes or openings are formed through the thickness of the substrate. The substrate material between the openings is of a size and geometry that allows cells to adhere to the surface of the substrate material as if it were an approximately two-dimensional (2D) surface, while also allowing adequate fluid flow around the substrate material and through the openings. In some embodiments, the substrate is a polymer-based material and can be formed as a molded polymer sheet, a polymer sheet with openings through its thickness, multiple filaments fused to a mesh-like layer, a 3D-printed substrate, or multiple filaments woven into a mesh layer. The physical structure of the substrate provides a high surface-to-volume ratio for culturing anchorage-dependent cells. According to various embodiments, the substrate can be placed or packed into a bioreactor in certain ways as discussed herein for uniform cell seeding and growth, uniform medium perfusion, and efficient cell recovery.

[0051] According to one or more embodiments, the cell culture substrate can be according to the cell culture substrate and / or substrate materials disclosed in U.S. Patent Application Nos. 16 / 781,685, 16 / 781,723, 16 / 781,764, 16 / 781,807, 16 / 781,847, 16 / 781,883, and 16 / 765,722, all of which are incorporated by reference in their entireties.

[0052] Also provided, according to some embodiments, is a method of cell culture using a bioreactor having a substrate for bioprocessing the production of a therapeutic protein, antibody, viral vaccine, or viral vector.

[0053] The provided cell culture substrates and bioreactor systems offer many advantages. For example, embodiments of the present disclosure can support the production of any of several viral vectors, such as AAV (all serotypes) and lentivirus, and can be applied for in vivo and ex vivo gene therapy applications. Uniform cell seeding and distribution maximizes viral vector yield per vessel, and the design allows for the recovery of viable cells, which can be useful for seed trains consisting of multiple expansion periods using the same platform. In addition, embodiments herein are scalable from process development scale to production scale, ultimately saving development time and costs. The methods and systems disclosed herein also enable automation and control of the cell culture process to maximize vector yield and improve reproducibility. Finally, the present disclosure allows for the scaling of viral vector production levels (e.g., 10 per batch). 16 ~10 pieces 18 The number of vessels required to reach 100 AAV volumes (µg) can be significantly reduced compared to other cell culture solutions.

[0054] Embodiments of the present disclosure relate to scalable bioreactor systems, including large-scale adherent cell culture fixed-bed bioreactors. Fixed-bed bioreactors are increasingly being used for the scaled production of cells, viral vectors, extracellular vesicles, and therapeutic proteins. Scalability is a key aspect for advancing processes from the development stage to production scale. To maintain high product quality and quantity and comply with GMP, it is highly desirable to have the ability to monitor all relevant parameters with the same measurement type at each process scale. The U.S. Food and Drug Administration (FDA) has recommended the adoption of process analytical technology (PAT) as a mechanism for designing, analyzing, and controlling pharmaceutical manufacturing processes through the measurement of critical process parameters that affect critical quality attributes.

[0055] Viable cell concentration (VCC), also known as biomass, is one of the most important key performance indicators during upstream technology in mammalian cell culture. For suspension cell culture, biomass monitoring can be achieved using optical or electrical approaches. However, for adherent cell culture using fixed-bed bioreactors, no validated approaches or sensors are available for online biomass monitoring. Indeed, for adherent cell culture, biomass is often measured by offline microscopic imaging methods after staining. Historically, substrate (e.g., glucose) consumption rates have been proposed to be useful for understanding the dynamics of cell growth. However, because substrate consumption rates are affected by many factors other than viable cell number, there are no established protocols, methods, and / or models for obtaining and using effective substrate consumption and metabolite accumulation rates to calculate and predict biomass.

[0056] However, embodiments of the present disclosure disclose methods and protocols for obtaining effective glucose consumption rates, glutamine consumption rates, lactate accumulation rates, and / or ammonia accumulation rates, and the use of at least one of these rates based on a mathematical model for biomass monitoring of adherent cell cultures in fixed-bed bioreactors. This method includes (1) using a glucose- and / or glutamine-rich medium, (2) measuring the glucose, glutamine, lactate, and / or ammonia concentrations multiple times (e.g., at least twice daily), (3) determining the glucose and glutamine consumption rates and lactate and / or ammonia accumulation rates, and (4) using a mathematical model to calculate and predict the biomass at a specific time point in the cell culture. Given the availability of online glucose sensors, this method can be used, for example, for online biomass prediction and calculation, which can be used as a guide for transfection schedules and cell harvesting. Because media samples can be collected using an offline sampling device such as a syringe, aspects of embodiments of the disclosed methods can also be performed offline using a multiplex analyzer (e.g., the Flex II Analyzer from Nova Biomedical).

[0057] Aspects of embodiments of the present disclosure describe methods for identifying any abnormalities in adherent cell cultures in fixed-bed bioreactors. Aspects of the embodiments include comparing glucose consumption or lactate accumulation rates with glutamine consumption or ammonia accumulation rates. According to certain aspects of the embodiments, any large discrepancy between the glucose / lactate rate and the glutamine / ammonia rate is an indication of a cell culture abnormality, such as cells undergoing apoptosis when they become overconfluent. In contrast, a good agreement between the glucose / lactate rate and the glutamine / ammonia rate is an indication of healthy cell growth.

[0058] According to embodiments, the medium used for cell culture preferably contains a high concentration of glucose (e.g., 2 g / L, 3 g / L, 4 g / L, 5 g / L, or even 10 g / L) and / or a high concentration of glutamine (e.g., 2 mM, 3 mM, 4 mM, 5 mM, or even 10 mM). In aspects of the embodiment, at least when the viable cell concentration is high in the latter half of the cell culture, the cell culture medium is replenished or replaced daily to prevent the glucose and / or glutamine concentrations from falling below a threshold value. This threshold value may depend on the specifics of the cell culture, but can be, for example, 0.25 g / L for glucose and 0.25 mM for glutamine. This will affect the measurement of the effective substrate consumption rate and metabolite accumulation rate, since for a given cell density at a given culture time, the glucose consumption rate will vary depending on the initial glucose concentration.

[0059] In one aspect of the embodiment, the cell seeding density is predetermined and optimized based on the cell culture setting. For example, the cell seeding density may be 20,000 cells / cm2 of surface area in a particular cell culture setting. However, this number is provided as an example only, because it should be understood that the cell seeding needs to be optimized so that the majority of cells (e.g., more than 90%) adhere to the fixed bed substrate surface.

[0060] The cell culture medium substrate and metabolites can be measured using online sensors or offline sensors or analyzers after samples are collected. The cell culture medium substrate and metabolites can be measured daily (including, for example, at least twice a day, depending on the embodiment). The two measurements can be separated by at least a specific time interval (e.g., 30 minutes, 1 hour, 2 hours, 3 hours, 4 hours, 5 hours, 6 hours, 7 hours, 8 hours, or even 20 hours). The first measurement, if any, can be taken at least 1 hour after the medium change is complete.

[0061] Depending on the bioreactor setup, use appropriate mathematical models to calculate the glucose / glutamine consumption rates, and lactate / ammonia accumulation rates, to predict and calculate the biomass at a specific cultivation period. [Example]

[0062] In experiments conducted based on embodiments of the present disclosure, the fixed bd bioreactor system described herein was used in a perfusion loop with a medium conditioning vessel (MCV) and pump. Two 1 mL syringes were attached to the perfusion loop tubing immediately upstream of the bioreactor vessel's inlet 112 and downstream of the outlet 114 (see FIG. 1). The syringes were used to collect medium samples every 30 minutes for 8 hours per day. Early each morning, half of the medium in the MCV was drained and replaced with 40 mL of excess medium back to the same volume, using fresh, warm medium to correspond to sampling from the previous day. All collected samples were analyzed offline using a Nova Biomedical Flex II Analyzer. HEK293T cells were used. The cell seeding density was 22,000 cells / cm². Cell attachment was found to be complete within 3.5 hours, with more than 95% of the cells attaching.

[0063] As shown in Figure 9, glucose concentrations decreased over time each day. Similar results were obtained for glutamine. In contrast, lactate concentrations increased over time each day, as shown in Figure 10 (similar results were obtained for ammonia). However, the differences between samples collected from upstream or downstream of the bioreactor at a particular culture time were very small, even on the final day of cell culture. This suggests that when the medium is passed through the bioreactor only once, the amount of glucose or glutamine consumed is relatively small and therefore cannot be used to obtain effective substrate consumption or metabolite accumulation rates. Therefore, according to embodiments of the present disclosure, only the substrate or metabolite concentrations from samples collected upstream of the bioreactor inlet can be used for biomass analysis.

[0064] The cell growth rate k is a function of many factors, including medium composition and concentration, temperature, and other environmental factors such as pH, dissolved oxygen, and CO. Assuming these environmental factors can be controlled so that the cell growth rate remains constant, it can be integrated over the surface area A to obtain the total cell number N(t). N(t)=N0e kt Formula (2) where N0 is the initial cell number.

[0065] According to the mass balance perfusion reactor model, as the cell culture medium passes through the bioreactor, a cell culture medium substrate concentration gradient, C in -C out is a function of the medium substrate consumption rate per cell, r, the total cell number, N, and the flow rate, Q.

number

[0066] In equation (3), C in is the concentration of cell culture medium substrate entering the bioreactor, while C out is the concentration of cell media substrate exiting the bioreactor, and Q is the flow rate. As mentioned above, in this experimental setup, the flow rate was approximately 50 mL / min, resulting in little or no change in cell media substrate concentration as the medium passed through the bioreactor. Therefore, it is difficult or impossible to directly calculate biomass using these concentration gradients. To calculate biomass using this parameter, the flow rate must be dramatically reduced or the sensor must reach a C value of 0.05 for a given analyte. in and C out It may be necessary to temporarily stop the flow (e.g., for 1 minute, 2 minutes, 10 minutes, etc.) to be able to detect significant differences between the number of cells. For example, for HEK293T cell cultures, 2 1 x 10 cells in the bioreactor (approximately 100 mL of medium is required to fill the entire bioreactor). 9For a single cell population, efficient detection of 0.1 g / L of glucose consumption requires stopping the flow for 10 min, assuming a glucose consumption rate of approximately 0.001 mg / min / million cells. Such low flow rates or stopping the flow for a certain period of time are not only difficult to achieve practically, but also result in a temporary hypoxic culture state.

[0067] According to the continuous stirred tank reactor model for MCV coupled bioreactors, the total amount of cell medium substrate consumed during a given period is a function of the cell consumption rate r and the total cell number N.

number

number

[0068] kt is sufficiently small (less than 0.5) within a maximum daily 8-hour sampling window, so that

[0069]

number

[0070] V(C0-C(t))=rN0t Equation (6)

[0071] Therefore, a plot of equation (6) fitted to a straight line ((V(C-C) vs. t) (time is shifted to the first significant sampling of each day) gives the slope of rN, where N is the total cell number at the first significant sampling of each day. Furthermore, a plot of rN vs. t, and a fit to an exponential curve, provides the following: rN0(t)=rN seed e kt Formula (7) The slope is the cell growth rate k and the intercept is r * N seed is.

[0072] FIG. 11 illustrates a graph of the total amount of glucose consumed V(C−C) as a function of time of day in accordance with an exemplary embodiment. t ) is shown. FIG. 12 shows a graph of the total glucose consumption rate rN0 for each day as an exponential function over the culture period, according to an exemplary embodiment. Using glucose consumption as an example, as shown in FIG. 11, the total amount of glucose consumed increased linearly over time within each day. However, the slope rN0 increased daily and was well fitted with an exponential function (FIG. 12), with a slope of 0.000391 min -1 cell growth rate k, intercept r of 0.212549 * N seed These results suggest that the cell doubling time is approximately 29.5 hours and the glucose consumption rate is 0.0009531 mg / min / million cells. Therefore, the harvest time t h The cell number at 5669 minutes can be predicted as follows:

number

[0073] The above number of 2046M is higher than the actual total number of cells recovered, which was found to be 1790M.

[0074] Similarly, glutamine, lactate, and ammonia profiles were obtained and used to analyze cell growth and predict cell number at harvest (Table 2). These results suggest good agreement between cell growth rate and cell number at harvest across all four analytes. Interestingly, while both glucose and lactate produced nearly identical cell growth parameters, glutamine shared similarities with ammonia. This is believed to be because lactate is a cellular metabolic product of glucose, while ammonia is a cellular metabolic product of glutamine. It is also noteworthy that glucose / lactate profiling predicted higher cell numbers than glutamine / ammonia profiling. [Table 2]

[0075] Additional experiments were performed using an alternative bioreactor system setup including a refeed bottle, as shown in Figure 13. One syringe was connected to the tubing just below the inlet of the bioreactor, where the substrate concentration was C t The second syringe is connected to the contents of the resupply bottle, where the substrate concentration is C 2,t It is called a substrate with a surface area of ​​5m 2 Two independent bioreactors were evaluated, both with a seeding density of 22,000 cells / cm. 2 HEK293T cells were cultured for 4 days using a microvessel (MCV) containing 1800 mL of medium, and the refeed loop contained 3 L of medium. 300 mL of cell solution was used for cell seeding. Results showed that the cells achieved approximately 95% adherence within 3.5 hours. At least two 2 mL samples were collected from the lower port of the reactor and the refeed bottle each day. On day 2, there was a medium change in the afternoon, and on day 3, there were two medium changes (one early in the morning and one late in the afternoon). Cells were harvested early in the morning on day 4 using an automated harvesting protocol. All collected samples were analyzed using a Nova Biomedical Flex II Analyzer.

[0076] Because this bioreactor setup includes a third re-feed bottle, a modified model is used to analyze the profiles. Let V2 and C2 be the medium volume and glucose concentration in the re-feed bottle, and Q2 is the flow rate between the MCV and the re-feed bottle. Then, for the MCV,

[0077]

number

[0078] For refill bottles,

[0079]

number

[0080] If we substitute it into the MCV formula,

[0081]

number

[0082] The solution is then:

[0083] V(C0-C(t))+V2(C 2,0 -C2(t))=rN0t

[0084] Glucose, glutamine, lactate, and ammonia profiles were also obtained and used to analyze cell growth and predict cell number at harvest. As illustrated for the first bioreactor (Figures 14A-14D), for all four analyte profiles, their corresponding consumption or accumulation rates fit well with an exponential function, consistent with the exponential growth pattern of a typical adherent cell culture. Further analysis also suggested good agreement between cell growth rates and cell numbers at harvest across all four analytes (Table 3). Again, both glucose and lactate yielded nearly identical cell growth parameters, while glutamine shared similarities with ammonia. The different cell growth parameters obtained may be related to slightly different culture conditions or cell culture variations between bioreactors (e.g., compare the results in Table 3 for the first bioreactor with those in Table 4 for the second bioreactor). In general, the cell parameters predicted using ammonia accumulation rates were lower than those for all three other analytes, likely due to the unique properties of ammonia. It is known that some of the produced ammonia escapes from the cell culture medium and enters the headspace of the MCV. [Table 3] [Table 4]

[0085] Alternatively, according to some embodiments, a metabolite kinetic model can be used. The above metabolite kinetic model is V(C0-C(t)) = rN0t or V(C0-C(t)) + V2(C 2,0 For each data set used to fit (-C2(t)) = rN0t, it is required that no medium additions or changes occur during the time span of the data set. This kinetic model has the advantage that the operator does not need to know the operating history of the entire culture, unless medium additions or changes occur during the time span of each data set collected.

[0086] However, in practice, only a limited number of samples are taken over several days, during which medium is added or replaced, and this is often done frequently. For example, in the later stages of cell culture, when cell confluency can become high, it is common to add a certain amount of medium periodically (e.g., hourly) to maintain a relatively constant medium composition, thereby improving culture productivity. In such scenarios, the following alternative approach is offered.

number

[0087] Table 5 provides an example. Assume there are seven samplings starting at t=0, one medium addition of volume Va after t2, and one medium exchange of volume Ve after t4. Δ(VC) is calculated as above, but must be adjusted for all samplings after any medium addition / exchange event. For example, for the medium addition after t2, Δ(VC) is calculated as Va for all samplings from t3 onwards. * Ca is added (Ca is the concentration of fresh medium). Similarly, for medium changes after t4, Δ(VC) is the concentration of Ve after t5. * The Ca-Ce ratio must be adjusted, where Ce is the concentration of the removed medium. To avoid the need to sample the removed medium, we suggest performing the medium change immediately after the regular sampling (in this case, immediately after t4, so that Ce = C4). [Table 5]

[0088] In the refeed bottle experiment above, there was a medium exchange from the system. Using the method proposed above, data can be prepared for the following model:

number

[0089] Figure 15 shows that total glucose consumption (correlated to total cell number) fits well to an exponential function in the model. The predicted cell growth constant, k, is 5.44e-04 min -1 (doubling time 21 hours). The predicted cell yield was 19,893 M, in close agreement with the recovery data, which was 19,175 M.

[0090] As shown, this cumulative model has the advantage of being suitable for a wide range of cell culture and metabolite data collection protocols, including fewer sampling intervals and more frequent media changes. However, this model requires tracking the entire history of the cell culture, especially any changes to the medium, such as adding, removing, or replacing the medium.

[0091] Exemplary Implementations Below are descriptions of various aspects of implementations of the disclosed subject matter. Each aspect may include one or more of various features, characteristics, or advantages of the disclosed subject matter. The embodiments are intended to illustrate some aspects of the disclosed subject matter and should not be considered a comprehensive or exhaustive description of all possible implementations.

[0092] Embodiment 1 relates to a method of monitoring biomass during cell culture of cells in a bioreactor, the method including culturing cells in the bioreactor using cell culture medium perfused through the bioreactor, measuring at least one of cellular nutrients and cellular by-products in the cell culture medium, determining at least one of a consumption rate of the cellular nutrients and an accumulation rate of the cellular by-products, and predicting the number of cells in the bioreactor at a specified culture time based on the at least one of the consumption rate and the accumulation rate.

[0093] Aspect 2 relates to a method according to aspect 1, wherein the bioreactor is a fixed-bed bioreactor comprising a substrate, the substrate being configured to culture cells attached to a surface of said substrate.

[0094] Embodiment 3 relates to a method according to embodiment 1 or 2, wherein the at least one cellular nutrient is glucose or glutamine.

[0095] Aspect 4 relates to a method according to any one of aspects 1 to 3, wherein the at least one cellular by-product is lactate or ammonia.

[0096] Aspect 5 relates to the method of any one of aspects 1 to 4, wherein the cell culture medium is a cell culture medium rich in glucose or glutamine.

[0097] Example 6 relates to the method of any one of Examples 1 to 5, wherein measuring at least one of cellular nutrients and cellular by-products in the cell culture medium comprises taking multiple measurements of the cellular nutrients or cellular by-products, wherein the multiple measurements are separated by a measurement interval that is shorter than the doubling time of the cells in the cell culture.

[0098] Embodiment 7 relates to a method according to embodiment 6, wherein the measurement interval is equal to or greater than a minimum interval time, the minimum interval time being the time during which the change in the level of the cellular nutrient or cellular by-product is greater than the measurement tolerance for measuring the cellular nutrient or cellular by-product.

[0099] Embodiment 8 relates to a method of embodiment 7, wherein the minimum interval time is about 30 minutes or more, 1 hour or more, 2 hours or more, 3 hours or more, 4 hours or more, 5 hours or more, 6 hours or more, 7 hours or more, 8 hours or more, 9 hours or more, 10 hours or more, 11 hours or more, 12 hours or more, 13 hours or more, 14 hours or more, 15 hours or more, 16 hours or more, 17 hours or more, 18 hours or more, 19 hours or more, or 20 hours or more.

[0100] Example 9 relates to the method of any one of Examples 1 to 8, wherein measuring the cellular nutrients in the cell culture medium comprises measuring the cellular nutrients multiple times per day of the cell culture.

[0101] Embodiment 10 relates to the method of any one of embodiments 1 to 9, wherein measuring the cellular by-products in the cell culture medium comprises measuring the cellular by-products multiple times per day of the cell culture.

[0102] Example 11 relates to the method of any one of Examples 1 to 10, wherein predicting the cell number comprises calculating the biomass at a specified culture time using a mathematical model.

[0103] Example 12 relates to the method of any one of Examples 1 to 11, wherein the measuring comprises using an in-line sensor in a cell culture medium perfusion line.

[0104] Embodiment 13 relates to the method of any one of embodiments 1 to 11, wherein the measuring comprises using offline measurements of a sample of the cell culture medium.

[0105] Example 14 relates to the method of any one of Examples 1-13, further comprising, after determining the consumption rate and accumulation rate, comparing at least one of the consumption rate of the first cellular nutrient and the accumulation rate of the first cellular by-product with at least one of the consumption rate of the second cellular nutrient and the accumulation rate of the second cellular by-product.

[0106] Example 15 relates to the method of Example 14, wherein the comparing comprises comparing the rate of glucose consumption with the rate of glutamine consumption.

[0107] Example 16 relates to the method of example 14 or example 15, wherein the comparing comprises comparing a rate of glucose consumption with a rate of ammonia accumulation.

[0108] Example 17 relates to the method of any one of Examples 14 to 16, wherein the comparing comprises comparing the rate of lactate accumulation with the rate of glutamine consumption.

[0109] Example 18 relates to the method of any one of Examples 14 to 17, wherein the comparing comprises comparing the rate of lactate accumulation with the rate of ammonia accumulation.

[0110] Embodiment 19 relates to the method of any one of embodiments 14 to 18, further comprising determining an abnormality in the cell culture based on the comparison.

[0111] Example 20 relates to the method of any one of Examples 1 to 19, further comprising seeding the cells into the bioreactor at a seeding density.

[0112] Example 21 relates to the method of any one of Examples 1 to 20, further comprising supplying the bioreactor with fresh cell culture medium.

[0113] Example 22 relates to a method according to example 21, wherein the measuring comprises a first measurement, and wherein the first measurement is performed at least one hour after providing fresh cell culture medium.

[0114] Aspect 23 is the cell number N t The prediction of N t =N seed e kt wherein N seed 23. The method according to any one of aspects 1 to 22, wherein k is the number of cells seeded in the bioreactor, k is the cell growth rate, and t is the time at which the number of cells is predicted. definition

[0115] "Wholely synthetic" or "fully synthetic" refers to a cell culture article, such as a microcarrier or culture vessel surface, that is composed entirely of materials of synthetic origin and does not contain any animal-derived or animal-origin materials. The disclosed whole synthetic cell culture articles eliminate the risk of xenocontamination.

[0116] The term "include," "includes," or similar terms means without limitation, that is, inclusive and not exclusive.

[0117] "User" refers to a person who uses a system, method, article, or kit disclosed herein, including a person who is culturing cells to harvest cells or cell products, or who is using cells or cell products that have been cultured and / or harvested according to embodiments herein.

[0118] When describing embodiments of the present disclosure, the term "about" as used to modify, for example, the amount, concentration, volume, process temperature, process time, yield, flow rate, pressure, viscosity, and similar values ​​and ranges of components in a composition, or the dimensions of components and similar values ​​and ranges, refers to variations in the numerical amount that may occur, for example, through typical measuring and handling procedures used to prepare a material, composition, composite, concentrate, component, article of manufacture, or formulation for use; through inadvertent errors in these procedures; through differences in the manufacture, source, or purity of starting materials or components used to carry out the method; and through similar considerations. The term "about" also encompasses variations in amounts due to aging of a composition or formulation having a particular initial concentration or mixture, and variations due to mixing or processing a composition or formulation having a particular initial concentration or mixture.

[0119] "Optional" or "optionally" means that the subsequently described event or circumstance may or may not occur, and the description includes cases where the event or circumstance occurs and cases where it does not occur.

[0120] As used herein, the indefinite article "a" or "an" and its corresponding definite article "the" mean at least one, or one or more, unless otherwise specified.

[0121] Abbreviations familiar to those skilled in the art may be used (e.g., "h" or "hrs" for hour or hours, "g" or "gm" for grams, "mL" for milliliters, and "rt" for room temperature, "nm" for nanometers, and similar abbreviations).

[0122] Specific preferred values ​​disclosed for components, ingredients, additives, dimensions, conditions, and similar aspects, as well as ranges thereof, are for illustrative purposes only and do not exclude other defined values ​​or other values ​​within the defined ranges. The systems, kits, and methods of the present disclosure can include any value or any combination of the values, specific values, more specific values, and preferred values ​​set forth herein, including any stated or implied intermediate values ​​and ranges.

[0123] Unless otherwise expressly stated, it is in no way intended that any method set forth herein be construed as requiring that its steps be performed in a particular order. Thus, unless a method claim actually recites the order in which its steps are to be followed or the claim or description specifically states that the steps are to be limited to a particular order, no particular order is intended to be inferred.

[0124] It will be apparent to those skilled in the art that various modifications and variations can be made without departing from the scope or spirit of the disclosed embodiments. Since modifications, combinations, subcombinations, and variations of the disclosed embodiments incorporating the spirit and content of the embodiments may occur to those skilled in the art, the disclosed embodiments should be construed as including all within the scope of the appended claims and their equivalents.

Claims

1. 1. A method for monitoring biomass during cell culture of cells in a bioreactor, said method comprising: Culturing the cells in the bioreactor using cell culture medium perfused through the bioreactor; measuring at least one of cellular nutrients and cellular by-products in the cell culture medium; determining at least one of a consumption rate of the cellular nutrients and an accumulation rate of the cellular by-products; and predicting the number of cells in the bioreactor at a specified culture time based on at least one of the consumption rate and the accumulation rate.

2. 10. The method of claim 1, wherein the bioreactor is a fixed-bed bioreactor comprising a substrate configured to culture cells attached to a surface of the substrate.

3. 3. The method of claim 1 or 2, wherein the at least one cellular nutrient is glucose or glutamine.

4. 4. The method of claim 1, wherein the at least one cellular by-product is lactate or ammonia.

5. 5. The method of claim 1, wherein the cell culture medium is a glucose or glutamine rich cell culture medium.

6. 6. The method of any one of claims 1-5, wherein the measuring at least one of the cellular nutrients and the cellular by-products in the cell culture medium comprises taking multiple measurements of the cellular nutrients or the cellular by-products, wherein the multiple measurements are separated by a measurement interval that is shorter than the doubling time of cells in the cell culture.

7. 7. The method of claim 6, wherein the measurement interval is equal to or greater than a minimum interval time, the minimum interval time being the time at which a change in the level of the cellular nutrient or cellular by-product is greater than a measurement tolerance for measuring the cellular nutrient or cellular by-product.

8. 8. The method of claim 7, wherein the minimum interval time is about 30 minutes or more, 1 hour or more, 2 hours or more, 3 hours or more, 4 hours or more, 5 hours or more, 6 hours or more, 7 hours or more, 8 hours or more, 9 hours or more, 10 hours or more, 11 hours or more, 12 hours or more, 13 hours or more, 14 hours or more, 15 hours or more, 16 hours or more, 17 hours or more, 18 hours or more, 19 hours or more, or 20 hours or more.

9. 9. The method of any one of claims 1 to 8, wherein said measuring said cellular nutrients in said cell culture medium comprises measuring said cellular nutrients multiple times per day of said cell culture.

10. 10. The method of any one of claims 1 to 9, wherein the measuring of the cellular by-product in the cell culture medium comprises measuring the cellular by-product multiple times per day of the cell culture.

11. 11. The method of any one of claims 1 to 10, wherein said predicting the cell number comprises calculating biomass at the specified culture time using a mathematical model.

12. The method of any one of claims 1 to 11, wherein the measuring comprises using an in-line sensor in the cell culture medium perfusion line.

13. The method of any one of claims 1 to 11, wherein said measuring comprises using offline measurements of a sample of said cell culture medium.

14. 14. The method of any one of claims 1-13, further comprising, after said determining said consumption rate and said accumulation rate, comparing at least one of a consumption rate of a first cellular nutrient and an accumulation rate of a first cellular by-product with at least one of a consumption rate of a second cellular nutrient and an accumulation rate of a second cellular by-product.

15. 15. The method of claim 14, wherein the comparison comprises comparing the rate of glucose consumption with the rate of glutamine consumption.

16. 16. The method of claim 14 or 15, wherein the comparison comprises comparing the rate of glucose consumption with the rate of ammonia accumulation.

17. 17. The method of any one of claims 14 to 16, wherein the comparison comprises comparing the rate of lactate accumulation with the rate of glutamine consumption.

18. 18. The method of any one of claims 14 to 17, wherein the comparison comprises comparing the rate of lactate accumulation with the rate of ammonia accumulation.

19. The method of any one of claims 14 to 18, further comprising determining an abnormality in the cell culture based on the comparison.

20. 20. The method of any one of claims 1 to 19, further comprising seeding cells into the bioreactor at a seeding density.

21. 21. The method of any one of claims 1 to 20, further comprising supplying the bioreactor with fresh cell culture medium.

22. 22. The method of claim 21, wherein the measuring comprises a first measurement, the first measurement being taken at least 1 hour after providing the fresh cell culture medium.

23. The number of cells N ｔ The prediction of N ｔ =N ｓｅｅｄ e ｋｔ wherein N ｓｅｅｄ 23. The method of any one of claims 1 to 22, wherein x is the number of cells seeded into the bioreactor, k is the cell growth rate, and t is the time at which the cell number is predicted.

24. 24. The method of any one of claims 1-23, wherein the measuring of at least one of the cellular nutrients and the cellular by-products in the cell culture medium comprises measuring at least one of glucose, lactate, glutamine, and ammonia concentrations at least twice per day during the cell culture for at least three days, the measurements being separated by predetermined time intervals.

25. 25. The method of claim 24, wherein the measuring comprises measuring at least two of glucose, lactate, glutamine, and ammonia concentrations.

Images