In-situ imaging sensors for bioprocess monitoring: state of the art

Machine learning in bioprocess development: from promise to practice

Fostered by novel analytical techniques, digitalization, and automation, modern bioprocess development provides large amounts of heterogeneous experimental data, containing valuable process information. In this context, data-driven methods like machine learning (ML) approaches have great potential to rationally explore large design spaces while exploiting experimental facilities most efficiently. Herein we demonstrate how ML methods have been applied so far in bioprocess development, especially in strain engineering and selection, bioprocess optimization, scale-up, monitoring, and control of bioprocesses. For each topic, we will highlight successful application cases, current challenges, and point out domains that can potentially benefit from technology transfer and further progress in the field of ML.

On-line monitoring of industrial interest Bacillus fermentations, using impedance spectroscopy

Impedance spectroscopy is a technique used to characterize electrochemical systems, increasing its applicability as well to monitor cell cultures. During their growth, Bacillus species have different phases which involve the production and consumption of different metabolites, culminating in the cell differentiation process that allows the generation of bacterial spores. In order to use impedance spectroscopy as a tool to monitor industrial interest Bacillus cultures, we conducted batch fermentations of Bacillus species such as B. subtilis, B. amyloliquefaciens, and B. licheniformis coupled with this technique. Each fermentation was characterized by the scanning of 50 frequencies between 0.5 and 5 MHz every 30 min. Pearson's correlation between impedance and phase angle profiles (obtained from each frequency scanned) with the kinetic profiles of each strain allowed the selection of fixed frequencies of 0.5, 1.143, and 1.878 MHz to follow-up of the fermentations of B. subtilis, B. amyloliquefaciens and B. licheniformis, respectively. Dielectric profiles of impedance, phase angle, reactance, and resistance obtained at the fixed frequency showed consistent changes with exponential, transition, and spore release phases.

Practical monitoring technologies for cells and substrates in biomanufacturing

Precise control over bioreactor operation is desired for optimal productivity and product quality, and there is an increased drive to automation in biomanufacturing. All of these goals require sensors, not only of the basic parameters of temperature, pH, and dissolved oxygen, but of the biomass and substrate concentrations, which directly determine the outcome of the bioprocess. While there are many innovative sensing concepts for biomass and substrate concentrations, this review focuses on sensors that are in-line with the bioreactor, providing data continuously without the removal of sample from the system. The discussion emphasizes the requirements of industry for these sensors, including performance, ease of use, and cost. As the bioeconomy grows, advances in sensing technologies will be needed to achieve the automation of the future for a wider array of bioreactors.

Turbidimetry and Dielectric Spectroscopy as Process Analytical Technologies for Mammalian and Insect Cell Cultures

The production of biopharmaceuticals in cell culture involves stringent controls to ensure product safety and quality. To meet these requirements, quality by design principles must be applied during the development of cell culture processes so that quality is built into the product by understanding the manufacturing process. One key aspect is process analytical technology, in which comprehensive online monitoring is used to identify and control critical process parameters that affect critical quality attributes such as the product titer and purity. The application of industry-ready technologies such as turbidimetry and dielectric spectroscopy provides a deeper understanding of biological processes within the bioreactor and allows the physiological status of the cells to be monitored on a continuous basis. This in turn enables selective and targeted process controls to respond in an appropriate manner to process disturbances. This chapter outlines the principles of online dielectric spectroscopy and turbidimetry for the measurement of optical density as applied to mammalian and insect cells cultivated in stirred-tank bioreactors either in suspension or as adherent cells on microcarriers.

Monitoring of Microphysiological Systems: Integrating Sensors and Real-Time Data Analysis toward Autonomous Decision-Making

Microphysiological systems replicate human organ function and are promising technologies for discovery of translatable biomarkers, pharmaceuticals, and regenerative therapies. Because microphysiological systems require complex microscale anatomical structures and heterogeneous cell populations, a major challenge remains to manufacture and operate these products with reproducible and standardized function. In this Perspective, three stages of microphysiological system monitoring, including process, development, and function, are assessed. The unique features and remaining technical challenges for the required sensors are discussed. Monitoring of microphysiological systems requires nondestructive, continuous biosensors and imaging techniques. With such tools, the extent of cellular and tissue development, as well as function, can be autonomously determined and optimized by correlating physical and chemical sensor outputs with markers of physiological performance. Ultimately, data fusion and analyses across process, development, and function monitors can be implemented to adopt microphysiological systems for broad research and commercial applications.

In situ microscopy as online tool for detecting microbial contaminations in cell culture

Microbial contamination in mammalian cell cultures causing rejected batches is costly and highly unwanted. Most methods for detecting a contamination are time-consuming and require extensive off-line sampling. To circumvent these efforts and provide a more convenient alternative, we used an online in situ microscope to estimate the cell diameter of the cellular species in the culture to distinguish mammalian cells from microbial cells depending on their size. A warning system was set up to alert the operator if microbial cells were present in the culture. Hybridoma cells were cultured and infected with either Candida utilis or Pichia stipitis as contaminant. The warning system could successfully detect the introduced contamination and alert the operator. The results suggest that in situ microscopy could be used as an efficient online tool for early detection of contaminations in cell cultures.

Dielectric Spectroscopy and Optical Density Measurement for the Online Monitoring and Control of Recombinant Protein Production in Stably Transformed Drosophila melanogaster S2 Cells

The production of recombinant proteins in bioreactors requires real-time process monitoring and control to increase process efficiency and to meet the requirements for a comprehensive audit trail. The combination of optical near-infrared turbidity sensors and dielectric spectroscopy provides diverse system information because different measurement principles are exploited. We used this combination of techniques to monitor and control the growth and protein production of stably transformed Drosophila melanogaster S2 cells expressing antimicrobial proteins. The in situ monitoring system was suitable in batch, fed-batch and perfusion modes, and was particularly useful for the online determination of cell concentration, specific growth rate (µ) and cell viability. These data were used to pinpoint the optimal timing of the key transitional events (induction and harvest) during batch and fed-batch cultivation, achieving a total protein yield of ~25 mg at the 1-L scale. During cultivation in perfusion mode, the OD₈₈₀ signal was used to control the bleed line in order to maintain a constant cell concentration of 5 × 10⁷ cells/mL, thus establishing a turbidostat/permittistat culture. With this setup, a five-fold increase in productivity was achieved and 130 mg of protein was recovered after 2 days of induced perfusion. Our results demonstrate that both sensors are suitable for advanced monitoring and integration into online control strategies.

Cell confluency analysis on microcarriers by micro-flow imaging

The productivity of cell culture-derived vaccines grown in anchorage-dependent animal cells is limited by bioreactor surface area. One way to increase the available surface area is by growing cells as monolayers on small spheres called microcarriers, which are approximately 100-250 μm in diameter. In order for microcarrier-based cell culture to be a success, it is important to understand the kinetics of cell growth on the microcarriers. Micro-flow imaging (MFI) is a simple and powerful technique that captures images and analyzes samples as they are drawn through a precision flow cell. In addition to providing size distribution and defect frequency data to compare microcarrier lots, MFI was used to generate hundreds of images to determine cell coverage and confluency on microcarriers. Same-day manual classification of these images provided upstream cell culture teams with actionable data that informed in-process decision making (e.g. time of infection). Additionally, an automated cell coverage algorithm was developed to increase the speed and throughput of the analyses.

An Innovative Optical Sensor for the Online Monitoring and Control of Biomass Concentration in a Membrane Bioreactor System for Lactic Acid Production

Accurate real-time process control is necessary to increase process efficiency, and optical sensors offer a competitive solution because they provide diverse system information in a noninvasive manner. We used an innovative scattered light sensor for the online monitoring of biomass during lactic acid production in a membrane bioreactor system because biomass determines productivity in this type of process. The upper limit of the measurement range in fermentation broth containing Bacillus coagulans was ~2.2 g·L⁻¹. The specific cell growth rate (µ) during the exponential phase was calculated using data representing the linear range (cell density ≤ 0.5 g·L⁻¹). The results were consistently and reproducibly more accurate than offline measurements of optical density and cell dry weight, because more data were gathered in real-time over a shorter duration. Furthermore, µ_max was measured under different filtration conditions (transmembrane pressure 0.3–1.2 bar, crossflow velocity 0.5–1.5 m·s⁻¹), showing that energy input had no significant impact on cell growth. Cell density was monitored using the sensor during filtration and was maintained at a constant level by feeding with glucose according to the fermentation kinetics. Our novel sensor is therefore suitable for integration into control strategies for continuous fermentation in membrane bioreactor systems.

Monitoring of Microalgal Processes

Process monitoring, which can be defined as the measurement of process variables with the smallest possible delay, is combined with process models to form the basis for successful process control. Minimizing the measurement delay leads inevitably to employing online, in situ sensors where possible, preferably using noninvasive measurement methods with stable, low-cost sensors. Microalgal processes have similarities to traditional bioprocesses but also have unique monitoring requirements. In general, variables to be monitored in microalgal processes can be categorized as physical, chemical, and biological, and they are measured in gaseous, liquid, and solid (biological) phases. Physical and chemical process variables can be usually monitored online using standard industrial sensors. The monitoring of biological process variables, however, relies mostly on sensors developed and validated using laboratory-scale systems or uses offline methods because of difficulties in developing suitable online sensors. Here, we review current technologies for online, in situ monitoring of all types of process parameters of microalgal cultivations, with a focus on monitoring of biological parameters. We discuss newly introduced methods for measuring biological parameters that could be possibly adapted for routine online use, should be preferably noninvasive, and are based on approaches that have been proven in other bioprocesses. New sensor types for measuring physicochemical parameters using optical methods or ion-specific field effect transistor (ISFET) sensors are also discussed. Reviewed methods with online implementation or online potential include measurement of irradiance, biomass concentration by optical density and image analysis, cell count, chlorophyll fluorescence, growth rate, lipid concentration by infrared spectrophotometry, dielectric scattering, and nuclear magnetic resonance. Future perspectives are discussed, especially in the field of image analysis using in situ microscopy, infrared spectrophotometry, and software sensor systems.

On-line monitoring of large cultivations of microalgae and cyanobacteria

Large cultivations of microalgae will benefit from on-line monitoring to achieve process control and improved productivity. This monitoring requires reliable sensors for on-line, in situ measurement of both physicochemical and biological process variables. Although standard industrial sensors can be used for many physicochemical variables, monitoring methods for most biological quantities rely on sensors that are currently suitable only for laboratory scale or off-line use. Here, we review these methods and discuss new approaches that could be adapted. We suggest that these new methods should be noninvasive and based on approaches that have already been applied to other bioprocesses; examples discussed here are in situ microscopy, flow cytometry (FC), IR spectroscopy, and software sensors.

Automated measurement and monitoring of bioprocesses: key elements of the M(3)C strategy

The state-of-routine monitoring items established in the bioprocess industry as well as some important state-of-the-art methods are briefly described and the potential pitfalls discussed. Among those are physical and chemical variables such as temperature, pressure, weight, volume, mass and volumetric flow rates, pH, redox potential, gas partial pressures in the liquid and molar fractions in the gas phase, infrared spectral analysis of the liquid phase, and calorimetry over an entire reactor. Classical as well as new optical versions are addressed. Biomass and bio-activity monitoring (as opposed to "measurement") via turbidity, permittivity, in situ microscopy, and fluorescence are critically analyzed. Some new(er) instrumental analytical tools, interfaced to bioprocesses, are explained. Among those are chromatographic methods, mass spectrometry, flow and sequential injection analyses, field flow fractionation, capillary electrophoresis, and flow cytometry. This chapter surveys the principles of monitoring rather than compiling instruments.