Advances in Inline Monitoring for Improved Bioreactor Performance

Understanding of cell physiology, health, and metabolism during cell culture and microbial fermentation enables more efficient, cost-effective production of high-quality biologic drugs. This knowledge guides decision-making about process development and enables improvement of bioreactor designs. Both activities, therefore, impact process and bioreactor performance.

Inline monitoring provides access to process information in real time, dramatically increasing bioprocess understanding, from fundamental process behaviors to more advanced attributes such as cellular functioning. As such, it can lead to significant improvements in productivity, quality, and process stability and better performing culture runs, often resulting in savings of time, materials, and human resources.

Recognition of the importance of real-time process monitoring is resulting in the development of solutions for tracking an increasing range of process parameters and other cellular attributes. Some of these solutions leverage existing technologies in new ways, while others are novel techniques developed specifically for inline monitoring within bioreactors.

Ensuring bioreactor performance

In an ideal world, it would be possible to monitor all metabolic pathways involved in cell culture and microbial systems. That is not practically feasible, of course. Historically, according to Melissa Semple, senior product manager for automated perfusion at Cytiva, the focus has been on monitoring three areas: the controlled environment, molecular proxies for media consumption, and cell density.

The controlled environment, Semple explains, is represented by sensors on bioreactor equipment, such as mass-flow-controller gas flow rates, agitation speed, pump speeds, weigh-scale changes, vessel pressure, etc.“The data gathered with these instruments provides assurance that we have control over the equipment and can generate the desired/intended conditions,” he says.

The environment is also monitored for features that have critical impact on the cells such as pH, dissolved oxygen (DO), and when possible or the sensor is suitable, dissolved carbon dioxide (CO2), Semple comments. During microbial fermentation, the cell line may also need to be monitored for reactive oxidative species via continuous redox sensing.

These process parameters are tracked because they affect cell growth, productivity, and product quality, according to Shunsuke Shiina, R&D scientist at AGC Biologics. The data are thus used to control the airflow rate, agitation speed, media feed rate, and pH. “This multitude of sensors is required to manage the most basic life support of the culture or fermentation process, and they are treated as critical to the control of the process because they monitor critical process parameters (CPPs),” Semple adds.

Semple also notes that the importance of these sensors has led to their continuous improvement, leading to the development of true in situ or in-line sensors that are continuously in contact with the process solution. The readings obtained from these sensors are used for fast control of bioreactor devices and ultimately the culture/fermentation environment for the cells, with management of the process environment generally achieved via automated closed-loop controllers.

Molecular proxies, Semple continues, represent the carbon sources that the cells rely on commonly for growth and energy (e.g., glucose, glutamine), as well as metabolized products for these molecules (e.g., lactate, glutamate) and cell wastes, with ammonia historically the proxy molecule.“These molecules are really the most basic and minimal indicators roughly representing the supply and consumption of media components. They give process operators a partial picture of the culture/fermentation metabolism and have been workhorse readings relied on for process optimization.”

Metabolite readings have typically, however, required collection of samples for offline analysis. There is therefore a need for sensors that can measure these—and ideally a wide array of other metabolites—in situ to the culture so that immediate and more continuous readings of the culture health can be obtained, according to Semple.

Cell density is monitored closely because the density must be determined precisely to know when to perform certain key process steps, such as transfection or infection, which can have a large impact on the final yield of a process, observes Clément Dumont, product manager with Univercells Technologies.

In situ measurement of viable cell density and total cell density is ideal because the data can be used to create control loops for feeding and enable quick responses to changes in cell densities in real-time, Semple says. Unfortunately, this determination is most often made via automated microscopy analysis of off-line samples. She does note, though, that more continuous permittivity readings from in situ sensors made for bioprocessing can in most cases be correlated to viable cell density.

Tools for inline monitoring

Monitoring of common parameters such as DO, pH, temperature, sparge, agitation, and CO2 overlay predate the emergence of modern process analytical technologies (PATs) and thus, says Pramthesh Patel, vice-president of process development and manufacturing, science, and technology for Avid Bioservices, have relied on earlier analytical technologies such as dedicated probes and sensors.

In recent years, Patel notes that the emergence of innovative PATs has allowed for the real-time monitoring of a host of additional parameters, offering a clearer view into what is happening to, and in some cases inside, the cell. “This latest collection of areas of monitoring have focused on cell viability, nutrient and metabolite levels, protein quality/integrity, glycosylation, and the redox state of the cell,” he explains. The PATs that have allowed for this expanded monitoring ability include capacitance, Raman spectroscopy, fluorescence lifetime imaging (FLIM), and near-infrared (NIR) and mid-wavelength infrared (MWIR) spectroscopy.

“PAT tools are allowing process attributes that were historically measured offline into the realm of real-time monitoring,” agrees Christopher Kistler, fellow scientist, biologics product development with Catalent Biologics. He observes that capacitance technology is used to build biomass prediction models from electrical signals, and Raman/NIR spectroscopy solutions for inline monitoring of metabolites are in development. David Ede, process technology manager at Sartorius, highlights new enzymatic probes for determination of nutrient and waste metabolite levels and emphasizes that Raman spectroscopy has been adapted for the measurement of concentrations of many different analytes, including glutamine, ammonium, amino acids, and even proteins. Dumont cautions, however, that these inline solutions for metabolites have yet to be seamlessly integrated with all single-use bioreactors.

Different methods for different biomolecules

To be truly useful, inline monitoring strategies must be selected according to the needs of each specific process. “Users need to be clear on what they are trying to achieve first to select the suitable PAT systems,” states Dumont. “While the technologies used for basic cell-culture monitoring are often quite standard, the parameters monitored to determine the quality and attributes of the final product depend on the type of product, and currently no standard solutions for inline assessment of those parameters exist,” he explains.

Different biologic drug substance classes may require different methods of bioprocess monitoring, Ede agrees. Chemical synthesis processes often use chromatographic methods such as high-performance liquid chromatography, while microbial processes rely on infrared technology to measure total biomass. For protein-based therapies, which are mostly produced by fed-batch processes, the key parameters are metabolite levels and cell density. These can be measured by enzymatic and capacitance probes, as well as by Raman spectroscopy. The process volumes can also be large, so CO2 levels may need to be monitored as well.

Novel modalities have additional process-monitoring requirements. Processes for the manufacture of virus-based therapies, Ede observes, require measurement of product titer and the ratio of full to empty capsids, which can be determined offline by various technologies, such as multiangle-light scattering following a size-exclusion chromatography step. For cell-based therapies, meanwhile, the correct cellular activation or differentiation status is essential because the cells are the product. Online sensors can measure cell size, number, and aggregation, but they may not be able to detect the correct differentiation of cells. Raman spectroscopy is under investigation for this application. “Multifrequency capacitance measurements could potentially provide more advanced cell parameters in the future, but there is little evidence of their application in cell therapy yet,” Ede remarks.

The application of PAT tools alongside prediction models and the comparison of analytical techniques enables customization of inline monitoring to the drug substance, Kistler concludes. He also notes that the range of PAT tools now available can be customized within a specific class of biologic drug substance, for example, an antibody/cell line may require a specific Raman model.

Importance of sensor design

The nature of the drug substance can also influence the sensor design that is most appropriate for a specific process-monitoring application, according to Semple. “The shape and nature of the molecules being detected determine the sensor design,” she contends.She also notes that often early versions of sensor technologies are available in offline form, allowing for detection of critical molecules before the sensors are ready for use under aseptic conditions.

In fact, sensors are often redesigned to be used seamlessly in an aseptic environment, Semple says. “This means they either need to maintain accurate function after being exposed to a steam-in-place cycle used to prepare a stainless-steel bioreactor or fermenter for use or a gamma irradiation or microwave cycle used to prepare a single-use bioreactor consumable.”

Another important aspect of in situ sensor design is continuous accuracy throughout the duration of a run. Semple also notes that some sensor designs will not translate to future in situ designs for continuous monitoring, such as those in which materials used in the sensing mechanism are consumed in a reaction. “These sensors,” he says, “will only be adaptable to offline forms that will accept discrete samples pulled one at a time from a bioreactor or atline solutions where culture is continuously distributed to the sensor.”

Providing greater versatility

“The growing body of available information garnered with the latest PATs offers a wealth of benefits to drug manufacturers, both at the outset of process development when experimentation is a critical and often complex activity, and when manufacturing is taking place based on an established process,” Patel states.

One advantage is increased freedom and versatility when designing experiments for identifying optimal manufacturing processes, observes Patel. “Without real-time monitoring, each experiment would have to be carefully conducted individually and then followed by another independent experiment to build on the knowledge gained during the previous experiment. However, the power of the latest PATs shows what is happening to the cell in real-time. Together, these technologies enable continuous experimentation involving dynamic challenges to the environment within the bioreactor, driving the identification of the process development sweet spot much more rapidly and efficiently.”

In addition, PAT tools can provide various enhancements over the life cycle of a process, according to Ede. They can enable process optimization by testing different parameters, collecting data on process robustness, and leveraging computer modeling to improve performance.

Once a process is optimized and characterized, PAT technologies can enable real-time control by setting tolerance zones for each parameter and applying a control strategy to adjust them within the limits, Ede continues. For instance, using a program such as Sartorius’ SIMCA-online to monitor the process in real time can provide early warning of any anomalies that may affect product quality or yield and allow implementation of an automated control strategy that can reduce operator errors or sterility issues. “This approach leads to lower product variation and fewer process deviations,” he states.

Bioreactor design can also increase flexibility, according to Dumont. He points to fixed-bed bioreactors such as the Univercells scale-x bioreactor, which is composed of a structured fixed bed that entraps cells.“This design makes the implementation of perfusion processes easier than in stirred-tank reactor for which advanced cell retention devices need to be used,” he explains. He adds that when this feature is combined with a PAT tool for glucose measurement, perfusion processes can be run for extended periods of time with constant glucose concentrations, affording a well-controlled media environment for the cells.

Separately, Univercells is implementing a new approach for cell-density determination using a correlation model fed by glucose and lactate data, which Dumont notes highlights the important of using PAT tools for data collection in combination with advanced data analysis techniques.

Increasing confidence

Real-time data from inline tools can provide data that are linked directly or indirectly to specific process parameters. In either case, the data can be used to improve manufacturing processes, according to Shiina. “The information obtained from in-line sensor can indicate if the feed amount and timing of media addition is appropriate for the cell’s activity. In addition, sensor data can be fed back to operators and/or bioreactor devices in real time to control important process elements, such as the supply of oxygen and air, the agitation number, and pH,” he explains.In the future, Shiina believes such feedback loops may ultimately be controlled by artificial-intelligence-based software leveraging both accumulated data and inline measurements.

Semple adds that continuous sensor data allows operators to control processes in a more consistent manner, potentially improving control of the environment on a cell-specific basis so that the final process will be robust from batch-to-batch. “The end result is greater confidence in the ability to develop processes that will be reliable from a quality and yield perspective,” he observes.

Kistler notes that PAT tools also bring more data into processing decisions at the time that decisions are being made, which increases confidence in those decisions. As an example, he highlights how PAT tools facilitate the precise control of feed delivery rates and provide instant feedback on residual metabolite concentrations, allowing process performance to be evaluated more holistically. “PAT tools could enable a future state where having access to product quality data in real-time will allow for evaluation of process and product data together; potentially improving quality, while minimizing the number of experiments required. Decisions can be made with more information and in an appropriate timeframe for course correction if necessary. Most importantly,” Kisstler emphasizes, “processing errors can be detected as they happen, and mitigated before they have the opportunity to become catastrophic.”

Contributing to improved bioreactor designs

Data collected with inline sensors have applications beyond process improvement and control. They can also be used, Patel observes, to inform strategies for enhancing the design, structure, or functionality of bioreactors. As an example, he notes that existing data can reveal additional data that would be good to collect, which in some cases may create opportunities to incorporate new probes/technologies directly into bioreactor designs rather than have them supplied as add-ons.

In fact, Semple notes that some of the most important improvements in bioreactor design in the course of history have come from the industry identifying the most critical molecules or cell features to the health and control of a cell-driven process.

“Making single-use interfaces available in bioreactor bag designs is key to fully utilizing the benefit these sensors can bring for a process while also reducing the risk of contamination in the long run,” Ede agrees.

There is at least one caveat, however, according to Shiina. “Using this information for long-term bioreactor design is dependent on a few factors, including the scale and shape of the bioreactor and the optimal locations and numbers of inline sensors being continuously improved.”

Semple expands on that thought: “As the biology of cell metabolism becomes better understood, more indicators of culture performance are becoming critical indicators for improved consistency in cell-culture and fermentation outcomes. The importance of a molecule to the health or productivity of the target cell type will determine where the biopharma industry will focus.The ability of the sensor to survive the environment of a bioreactor or fermenter will determine the placement of the sensor as a bench-top or in situ sensing device.If continuous culture sampling can be provided that works with the atline sensor solution, the continuous sampling feature becomes important for certain cell-culture or fermentation processes. These solutions will be created when the new sensed value is critical to the function or consistency of the process controlled.”

Not necessarily new technologies

PAT tools designed for real-time monitoring can be based on novel technologies, but often they leverage existing analytical techniques adapted to perform in an inline, continuous manner. “It is not always necessary to develop new technology, as existing technology can sometimes be leveraged to address these new applications, with the application of Raman spectroscopy for real-time monitoring of product quality attributes being one such example,” Kistler says.

Capacitance and FlIM are two other primary PATs recently introduced that do not represent fundamentally new technologies, adds Patel.“They are each long-established technologies based on the fundamentals of physics. However, it is only recently that these approaches have been applied to advancing the monitoring capabilities within biopharmaceutical processes,” he notes.

Real-time monitoring of cell physiology

As biopharmaceutical solutions have expanded past protein-based therapies to include gene and cell therapies, customers are looking to quantifying more molecular species, cell species, and cell forms (live/dead) in their pursuit of a controlled production process. Fourier-transform infrared spectroscopy (FTIR) and field-effect transistor (FET) biosensor solutions are two technologies attracting interest for inline, real-time monitoring as a result, according to Semple.

Potential for inline sterility monitoring

One important aspect of bioprocess testing that has not yet benefited from inline techniques is sterility monitoring. Kistler notes that several working groups across the industry are investigating rapid microbial testing capabilities. “Once the testing is fast and accurate enough, the next step would be to move the testing away from an offline paradigm.”

“If successful,” Kistler notes, “such inline sterility testing would have the potential to reduce the existing significant turnaround time between the end of a manufacturing batch and the return of sterility test results, not only reducing release times but affording manufacturers the opportunity to terminate problematic batches prior to committing additional valuable, human, material, or other resources.”

New solutions needed for novel modalities

As more molecule types are created through cell-culture and fermentation processes, Semple expects the drive to monitor various molecules (e.g., proteins, viruses, DNA, and RNA) and be able to distinguish between various forms of those molecules (e.g., glycosylation states of target proteins, plasmid DNA, messenger RNA, and so on) will create a need for additional real-time monitoring solutions.

Indeed, both cell and gene therapies require relevant inline monitoring solutions that are currently lacking, according to Ede. “For cell therapies, sensors are needed that can measure cell density, aggregation, activity, and differentiation to guide cells into a favorable state. For gene therapies, sensors that can quantify product titer in real time are needed to accelerate process development and reduce the risk of GMP [good manufacturing practice] production,” he says.

Use of fixed-bed bioreactors for adherent cell culture of viral vectors and other virus-based therapies is, according to Dumont, creating the need for new real-time monitoring solutions as well. Univercells has several projects underway, including one that is focused on using inline glucose and lactate measurement combined with an advanced correlation model for biomass prediction in the bioreactor.

“The adoption of soft sensors for cell density monitoring provides some key benefits, especially when used in fixed-bed bioreactors,” Dumont says. He adds that the model being developed by Univercells provides data that are representative of the entire fixed bed, while some other measurement methods provide a more local measurement and can be less representative of the whole cell culture. The model is also, according to Dumont, particularly beneficial when used with a range of bioreactors that enable direct scalability, because the models created at small scale can be applied directly at larger scale.

Technical, validation, and other challenges

While inline sensing for real-time monitoring of bioprocesses is leading to improved bioreactor and process performance, the development of these solutions is not a simple task. Introduction of new sensors and PAT tools within single-use systems, in particular, is challenging with respect to optimizing sensor location, resistance to sterilization procedures (e.g., gamma or x-ray irradiation), and aseptic installation, notes Shiina. He adds that confirmation and validation of the comparability of new inline sensors with offline equipment is important, particularly if offline assays must initially be used as new technologies are implemented.

Patel points out that many of the latest sensors/PAT tools have the potential to be vulnerable to light interference. This attribute creates a challenge because plastic single-use bioreactors are not particularly well-protected from light. Another issue, he says, is the fact that disposable bioreactors can only accommodate so many probes, potentially limiting how many PATs are utilized.

Validation of the performance of new sensors/PAT tools within the matrix environment of the bioreactor must also be considered, according to Patel. “The latest tools are developed and tested within relatively pristine environments allowing for specific focus on the target being analyzed. However, the bioreactor is populated with a diverse mixture of materials, any of which may impact the performance of a sensor or probe. Understanding this challenge and having processes by which to ensure these devices are performing accurately is of upmost importance,” he explains.

In addition, Dumont stresses the need for PAT systems to be integrated seamlessly in the customer environment. “A single process often combines different equipment from different providers. Standardization in the new PAT system being introduced will be of critical importance,” he observes. New systems must also provide proper measurement in a wide range of conditions so they can be used in different processes and combined with different equipment in a flexible manner.

Other issues include the need for scalability and management of sensor life and calibration. In single-use systems, Kistler points out that there is no way to manipulate a sensor as an end user. “The industry is moving towards the integration of sensors with bag film, enabling sensors to be calibrated at the point of assembly, only. Sensors then need to be stable through the product lifecycle, from sterilization through packaging, shipment, and ultimately, use in a production batch,” he says.

Compliance needs can create obstacles as well. As an example, Semple comments that in situ sensor design must consider regulatory requirements around impact on viable cells, chemical compatibility, particle generation, and leachable/extractable profiles when in contact with process liquids, even if those liquids are to be later purified. Ede adds that single-use sensors are part of regulated products and GMP processes, that require rigorous testing and qualification before each launch, which can extend development timelines.

Data management and analysis

PAT tools must be supported by appropriate data management and analysis solutions to ensure maximum benefit of the collected data. “For all of the information from a PAT tool to be useful, the infrastructure must be in place to analyze and handle the dataset, and this consideration is often overlooked,” notes Kistler.

Ede agrees, “To make the most of the data generated, you need to feed it back into the process.” That includes tools that allow performance of multivariate data analysis (MVDA), model creation, and detection of process anomalies through real-time batch monitoring. Control software is also needed that connects various sources of process knowledge, sets process strategies, and then links those strategies to the necessary actuators, such as pumps, stirrer motors, and valves,” he adds.

Other factors that are required to turn the data into useful information, Kistler says, include the ability to access information from the PAT tools, integrating the process and PAT data together, the networking required to move data off the production floor, and the skill sets required to develop models.

AGC Biologics, in fact, has placed high importance on developing a process information system to collect data from inline monitoring and link it to process control. The company is also, according to Shiina, looking to deploy MVDA of wavelengths originating from many substances in the culture media obtained by Raman spectroscopy sensors. “In particular, we anticipate that the information obtained from MVDA will be used to control key components,” he says.

Accessing previously unknown information

The entire goal of real-time monitoring within biopharmaceutical processes, stresses Patel, is to unlock what has previously been a black box to scientists—what is happening to cells and the environment inside a bioreactor in real-time. “While we have made great strides in building windows into the black box, blind spots still remain. In order to address those remaining blind spots, we need to create additional windows (probes/PATs) that offer even more precision and sensitivity,” he contends.

For Patel, “the most important advance we can make is enabling the real-time monitoring and analysis of the physiology of a cell inside the bioreactor, as well as getting a pretty good handle on product quality real time. This will allow us to peek inside of the cell and view transcription/translation activities, as well as its overall energy state of the cell. Ultimately, this will help us understand the conditions that best make the cell ‘happy’ and allow us to recreate those conditions to optimize biopharmaceutical processing.”

“The stronger our understanding of the biological and molecular processes during the development of biopharmaceuticals, the stronger our control of our processes and the greater the process consistency. Ultimately our understanding of biological processes will reduce lost batches, slim the number of runs needed to develop new processes based on past experimentation, and lead to a more responsive and sustainable industry. Such achievements can only come through a strong understanding of the cause-effect nature of the biological processes under control,” Semple concludes.

About the author

Cynthia A. Challener is a contributing editor to BioPharm International®.

Article details

BioPharm International
Vol. 36, No. 9
September 2023
Pages: 22–28, 38

Citation

When referring to this article, please cite it as Challener, C.A. Advances in Inline Monitoring for Improved Bioreactor Performance. BioPharm International 2023 36 (9).