The ability to measure all process variables is of great importance in the field of bioprocess monitoring and control, and continuous, real‐time measurements are highly desired. The more complete and real‐time the measurements are, the more stable, reproducible, and efficient the process can be, leading to reproducibly high‐quality products. This additional information allows the operator to better document the entire process. The process analytical technologies initiative of the US Food and Drug Administration is strongly related to the analysis and control of biopharmaceutical processes. The aim of the initiative is to create processes, generating products of ensured quality by measuring quality‐related process variables. The quality of the product is enhanced by a deep understanding of the process, which is enabled by an effective and suitable sensor system. The aim of this review is to provide an overview of current and emerging sensors for bioprocess monitoring. Sensors directly interfaced to bioreactors for measuring important variables from the gas phase, such as oxygen and carbon dioxide concentration, are discussed, as well as sensors for the monitoring of the biomass concentration and morphology and of the changing medium composition. Furthermore, sensor systems are discussed. These involve sensors (especially biosensors) that are not implemented directly inside the bioreactor but rather are used in conjunction with sample‐taking systems such as flow injection analysis. A major focus is given to spectroscopic sensors, which are noninvasive and offer interesting options for a simultaneous analysis of various compounds. Since data handling is extremely important for this kind of sensor, chemometrics are also included. Soft sensors are discussed as technology that allows a user to incorporate more process data as it become available. Finally, the current state of disposable sensor technology is presented. These sensors are needed for the growing area of disposable and continuous biomanufacturing.
The use of spectroscopic sensors for bioprocess monitoring is a powerful tool within the process analytical technology (PAT) initiative of the US Food and Drug Administration. Spectroscopic sensors enable the simultaneous real-time bioprocess monitoring of various critical process parameters including biological, chemical, and physical variables during the entire biotechnological production process. This potential can be realized through the combination of spectroscopic measurements (UV/Vis spectroscopy, IR spectroscopy, fluorescence spectroscopy, and Raman spectroscopy) with multivariate data analysis to obtain relevant process information out of an enormous amount of data. This review summarizes the newest results from science and industry after the establishment of the PAT initiative and gives a critical overview of the most common in-line spectroscopic techniques. Examples are provided of the wide range of possible applications in upstream processing and downstream processing of spectroscopic sensors for real-time monitoring to optimize productivity and ensure product quality in the pharmaceutical industry.
The best method for process control is the use of model‐based solutions, based on process analytical technology for online monitoring of critical process variables, product quality attributes, or a holistic process state estimation. Mechanistic models as well as data‐driven techniques are essential for real‐time process monitoring. Their main characteristics, advantages and disadvantages, and the link between both are discussed as well as the synergetic effects, benefits, and drawbacks resulting from their combination. Aspects and differences of the computational model life cycle management are highlighted.
Modern bioprocess monitoring demands sensors that provide on-line information about the process state. In particular, sensors for monitoring bioprocesses carried out in single-use bioreactors are needed because disposable systems are becoming increasingly important for biotechnological applications. Requirements for the sensors used in these single-use bioreactors are different than those used in classical reusable bioreactors. For example, long lifetime or resistance to steam and cleaning procedures are less crucial factors, while a requirement of sensors for disposable bioreactors is a cost that is reasonable on a per-use basis. Here, we present an overview of current and emerging sensors for single-use bioreactors, organized by the type of interface of the sensor systems to the bioreactor. A major focus is on non-invasive, in-situ sensors that are based on electromagnetic, semiconducting, optical, or ultrasonic measurements. In addition, new technologies like radio-frequency identification sensors or free-floating sensor spheres are presented. Notably, at this time there is no standard interface between single-use bioreactors and the sensors discussed here.In the future, manufacturers should address this shortcoming to promote single-use bioprocess monitoring and control.
Since the mechanism governing the partitioning behavior of biomolecules, such as proteins and enzymes, in polyethylene glycol (PEG)-salt aqueous two-phase systems (ATPS) is complex and not easily predictable, many laborious experiments have to be performed for an optimization of these systems, causing increased overall cost. However, the multivariate statistical design of experiments (DoE) methodology is representing a promising and efficient optimization technique which can overcome the limitations of traditional optimization methods. Therefore, DoE has emerged as a powerful and efficient optimization tool for PEGsalt ATPS, since it is faster, more efficient and cost-effective, allowing a simultaneous and rigorous evaluation of process/system parameters. In the present review, different DoE process steps are represented to highlight the feasibility of this approach to operate as a promising and efficient optimization tool, thus facilitating the evaluation of the partitioning behavior, recovery and purification of different proteins and enzymes in PEG-salt ATPS. In this context, several experimental designs, such as factorial and response surface designs, have been discussed and evaluated by statistical regression analysis and analysis of variance (ANOVA), as well as various applications of PEG-salt ATPS using DoE have been outlined which may further promote the optimization of these systems.
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