Over the past decade, single-use bioreactors have evolved from simple, small-volume rocking platforms with minimal measurement and control, to sophisticated systems. The single-use paradigm allows for many capabilities and simplifications in deployment that are not possible with existing glass and steel vessels.
by Dr Barbara A. Paldus and Mark D. Selker
Bacterial, mammalian, avian and insect cells are currently the main cell types used to produce therapeutic products. Each cell type used for this purpose has unique benefits as well as limitations, which determine the type of lab-scale bioreactor used. Applications of lab-scale bioreactors include research (understanding the process and cell physiology), scale-up process development (determining critical and optimal process parameters), and scale-down troubleshooting (solving problems encountered in large-scale production).
Lab-scale bioreactors typically have a working volume that varies from about 0.2L to 20 L. It is therefore important that both the bench-top bioreactors and their associated controllers can be relied upon to accurately mimic and/or scale laboratory and pilot process conditions. It is important as this ability allows growth kinetics and factors that affect product expression – often optimised only at lab-scale volumes – to be understood and accounted for, thereby allowing accurate, quantitative scale-up or -down.
Single-use lab-scale bioreactors
Lab-scale bioreactors vessels can utilise different construction materials, such as glass, stainless steel or even plastic (in single-use configurations). The vessels can be single-wall or jacketed, can use different types and numbers of impellers (e.g., Rushton for fermentation versus marine-type for cell culture) and spargers (e.g., open pipe versus frit or bubble columns), and provide for real-time (e.g., pH, dissolved oxygen, temperature, cell density) or off-line (e.g., metabolic parameters such as glucose) measurements. Lab-scale bioreactors can be operated in several different modes, such as batch, fed-batch, continuous and continuous perfusion. Each of these modes requires further configuration of the bioreactor control system.
As manual labour is expensive, availability of trained operators and research efficiency become dominant factors in ever-increasing drug development costs; even the cost of using bench-scale bioreactors is expected to drive faster adoption of single-use systems. Over the past decade, single-use bioreactors have evolved from simple small-volume rocking platforms with minimal measurement and control, to sophisticated systems [Figure 1] whose capabilities rival, if not exceed, glass and stainless steel vessels. As we will discuss, the single-use paradigm allows for many capabilities and simplifications in deployment that are not possible with the existing glass and steel vessels.
The potential of such media-filled, pre-configured single-use bioreactors with integrated single-use sensors for primary process parameters is significant, provided that they are not limited by an inflexible control system that is difficult to use.
Pre-calibrated, integrated sensors
A new opportunity to fully automate the lab-scale process and minimise operator error, even for a bench full of 1L bioreactor vessels, is emerging in research and process development labs. Currently only fundamental process parameters such as pH, dissolved oxygen and temperature are measured in-line and in real-time with any confidence; even these parameters are subject to systematic and random error generated by the operator. Other process variables such as cell count, cell viability and metabolic parameters (e.g., glucose, glutamine) are measured off-line, using mostly manual methods. However, all of these measurements still rely on manual calibration. The current paradigm with “dumb” control systems and traditional sensors is very labour-intensive and therefore very costly and time consuming.
Sensors that are pre-calibrated and can directly communicate with the control system's database to store calibration parameters can eliminate further errors and reduce operator time significantly [1]. Technology currently exists that allows “smart” chips or tags to be integrated into the single-use component such that the calibration and validation data can be automatically read into the system [2].
Intelligent lab-scale control systems
Process data are often still recorded in laboratory notebooks, excel spreadsheets, or are manually entered into the automation system. Naturally such manual procedures can generate significant human errors, both in the measurement and recording of the data. In addition, the current scenario is labour-intensive, which does not realise the goal of minimising operator time, and does not provide additional data for process control.
Improvements in bioreactor operating software that allow automated sampling, measurement and data entry with minimal human intervention will not only minimise errors, but allow the data to be used for process optimisation. In both cases, the deployment of electronic records for storing both calibration and measurement information, as well as tracking serial numbers of the physical components used to produce a batch, will provide significant labour savings while improving the quality/accuracy of the data and the reproducibility of the process. Being easily able to automate parallel runs of multiple bioreactors for design of experiment (DOE) approaches further enhances the value of the automation system.
The availability of calibration and off-line data can be further extended to include the management of the entire process configuration. Specifically, modern computer systems have sufficient computational and storage capability to allow a user to store a process “recipe” (i.e., the settings of all sensors and actuators for a given process), to make logical decisions and to drive a process in phases, as well as to store and process large amounts of process data [3].
Furthermore, by leveraging the real-time capability of modern operating systems such as Windows or Linux, sophisticated real-time computation can be performed and used to enable novel control algorithms, or “virtual” process parameters (e.g., “software sensors” that calculate a parameter indirectly from physically measured values). These advances in process control have the potential to further improve process yield beyond the gains achieved through biological (genetic) optimisation of cell line robustness and productivity.
The advent of modern high-bandwidth telecommunications can also be leveraged in bio-processing, as in almost every other industry. Standardisation of communication protocols (such as OPC and USB) allows plug-and-play integration of on-line and off-line analytical instruments into the process control system, thereby increasing the number of measured process parameters and the overall knowledge of the process state [Figure 2]. The rapid piping of data into and out of the control system will allow more sophisticated and dynamic control and optimisation of the process. By deploying secure networks, remote monitoring and control of processes will increase productivity of international research teams. Finally, the ability to store and transmit process configurations electronically will enable technology transfer and facilitate outsourcing to other countries.
TruBio PC: a powerful, user-friendly laboratory control system
Using the “Wintel” combination, the T300 system from Finesse, comprising TruViu hardware and TruBio μC software, is a smart lab-scale bioreactor automation solution. The use of a hardened industrial Intel micro-processor board and a mature operating system allow the user to change process settings, strategies and values without re-compiling, and enable a GUI style [Figure 3] that has become familiar to the “PC generation”.
TruBio μC software uses these tools to create a real-time, user-friendly environment and amplifies the advantages of smart single-use sensors. For example, mining and monitoring of material data were discussed, but the effect of sensor performance on control and loop performance was not. Factors like sensor response time and sampling rates can be part of the basic data set that is automatically read. These data can be used to automatically populate or modify fields in control loops enabling transparency for the operator.
It is also possible to provide automated sequences and programming, which automatically map out vessel mass transfer coefficients (e.g., Kla). In an era where new disposable vessels are created yearly (e.g., Millipore’s Mobius, New Brunswick’s CelliGen and Artellis’ iCELLis), these features save time and allow a focus on the process and not the equipment. These loops can be run to determine first order optimal values for PID loops controlling temperature, pH and dissolved oxygen.
Other problems that can be alleviated are the issues with scale-up and scale-down of processes [3]. Even if the vessels are well characterised, the control loop strategy and time response must also be understood. If the control strategies are different and the loop time responses poorly understood, much of the work spent understanding the bioreactor becomes meaningless. Again, with a smart controller some of these details can be made easier as a file can be used to store many of the parameters required to run a bioprocess; the many vessel-dependent parameters can be stored in the system. This information can be used when the vessel is changed to start the scale-up process.
Conclusions
In order to fully enable the lab-scale single-use paradigm and process optimisation on a global scale, the automation software, hardware and single-use sensors must share the following common characteristics:
- Single-use sensors must either replace traditional sensors or enable new analytical capability. Ideal “smart” sensors would be intoduced into the bioprocess container pre-calibrated and gamma-irradiated with the container, so that the entire system arrives sterile, thereby minimising operator time during process setup.
- Automation hardware systems must be flexible and movable, in order to adapt to different sizes and types of laboratory vessels. Hardware must be user-friendly and plug-and-play, with a wide variety of external equipment, such as pumps, MFCs, scales and off-line analysers. The control system must also allow fast and easy re-configuration for different processes (i.e., batch, fed-batch, or perfusion) or cell types.
- Automation software should allow rapid scalability of a process through advanced process models and smart algorithms, as well as easy data collection and analysis. The software should allow easy process re-configuration through drop-down menus without any programming, and allow the user to save and load process recipes for accelerated process scale-up or transfer.
Coupled with the capability of running multiple parallel single-use bioreactors for DOE studies, this enhanced flexibility in research, process development and production should not only improve the overall efficiency of the biotech industry, but also allow both large and small international players to maximise the use of limited resources, and diversify their product pipeline.
References
1. Selker MD, Paldus BA.Single-Use Systems: Optical Sensors and Bioreactors. BTi Magazine. 2008; Sept: 16-18.
2. Selker MD, Paldus BA. Single-Use Solutions for Scale-Up and Technology Transfer. Innovations in Pharmaceutical Technology 2009; March: 57-59.
3. Wilson JD. Method and Apparatus for Control of Biochemical Processes 1975; U.S. Patent 9,926,738.
The authors
Barbara A. Paldus and Mark D. Selker
Finesse Solutions, LLC,
San Jose, CA, USA
www.finesse.com
