Development of Novel Bioreactor Control Systems Based on Smart Sensors and Actuators

Wang, Baowei; Wang, Zhiwen; Chen, Tao; Zhao, Xin

doi:10.3389/fbioe.2020.00007

Cited by 46 publications

(29 citation statements)

References 111 publications

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“…The photophysiological performances, which are usually detected experimentally, result from the superposition of several highly variable aspects related to gas exchange, mixing regime, reactor geometry, and light intensity distribution ( Béchet et al, 2013 ; Huang et al, 2017 ). Direct access to the processes within the reactor environment is burdensome; therefore, simulation modeling is invaluable to shed insights into the reasons underlying the photosynthetic performances ( Wang B. et al, 2020 ). The engineering and/or operational solutions consequently devised can improve biomass photosynthetic growth efficiency and productivity.…”

Section: Discussionmentioning

confidence: 99%

Computational Analysis of Dynamic Light Exposure of Unicellular Algal Cells in a Flat-Panel Photobioreactor to Support Light-Induced CO2 Bioprocess Development

et al. 2021

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Cyanobacterial cell factories trace a vibrant pathway to climate change neutrality and sustainable development owing to their ability to turn carbon dioxide-rich waste into a broad portfolio of renewable compounds, which are deemed valuable in green chemistry cross-sectorial applications. Cell factory design requires to define the optimal operational and cultivation conditions. The paramount parameter in biomass cultivation in photobioreactors is the light intensity since it impacts cellular physiology and productivity. Our modeling framework provides a basis for the predictive control of light-limited, light-saturated, and light-inhibited growth of the Synechocystis sp. PCC 6803 model organism in a flat-panel photobioreactor. The model here presented couples computational fluid dynamics, light transmission, kinetic modeling, and the reconstruction of single cell trajectories in differently irradiated areas of the photobioreactor to relate key physiological parameters to the multi-faceted processes occurring in the cultivation environment. Furthermore, our analysis highlights the need for properly constraining the model with decisive qualitative and quantitative data related to light calibration and light measurements both at the inlet and outlet of the photobioreactor in order to boost the accuracy and extrapolation capabilities of the model.

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Section: Discussionmentioning

confidence: 99%

Computational Analysis of Dynamic Light Exposure of Unicellular Algal Cells in a Flat-Panel Photobioreactor to Support Light-Induced CO2 Bioprocess Development

et al. 2021

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“…A real-world controller design is an exercise in balancing the considerations for a speed of response, robustness, disturbance rejection, and cost of the control strategy [27,28]. A trade-off can happen at any level of industrial automation levels or at regulatory control levels depending on the importance of the product being developed in the plant.…”

Section: Trade-offs In Controller Designmentioning

confidence: 99%

Bioreactor control systems in the biopharmaceutical industry: a critical perspective

Mitra

Murthy

2021

Syst Microbiol and Biomanuf

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Industrial-scale bioprocessing underpins much of the production of pharmaceuticals, nutraceuticals, food, and beverage processing industries of the modern world. The profitability of these processes increasingly leverages the economies of scale and scope that are critically dependent on the product yields, titers, and productivity. Most of the processes are controlled using classical control approaches and represent over 90% of the industrial controls used in bioprocessing industries. However, with the advances in the production processes, especially in the biopharmaceutical and nutraceutical industries, monitoring and control of bioprocesses such as fermentations with GMO organisms, and downstream processing has become increasingly complex and the inadequacies of the classical and some of the modern control systems techniques is becoming apparent. Therefore, with increasing research complexity, nonlinearity, and digitization in process, there has been a critical need for advanced process control that is more effective, and easier process intensification and product yield (both by quality and quantity) can be achieved. In this review, industrial aspects of a process and automation along with various commercial control strategies have been extensively discussed to give an insight into the future prospects of industrial development and possible new strategies for process control and automation with a special focus on the biopharmaceutical industry.

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“…Improvements are occurring in basic sensing technologies, for example, electrochemical, capacitance, surface plasmon resonance, mass-based, optical, thermistor or piezoelectric-based. Smart sensors can convert surrogate measurements to a functional value in silico [15]. Automated sampling and distribution of culture samples is increasing in speed, precision and number of analytics supported [16].…”

Section: Improved Platforms/ Materialsmentioning

confidence: 99%

Bioprocess Intensification: Aspirations and Achievements

Whitford¹

2020

BioTechniques

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There are many drivers to intensify the manufacturing of a biological product. Advances are occurring throughout the biomanufacturing arena, from process development techniques to improved manufacturing platforms, equipment and facilities. Many employ the term 'bioprocess intensification' to refer to systems for producing more product per cell, time, volume, footprint or cost. This need is being driven by two emerging priorities: cost control and process efficiency. We are seeing great interest in the power of such disciplines as synthetic biology, process simplification, continuous bioprocessing and digital techniques in the optimization of bioprocess development and manufacturing. Other powerful disciplines here include process automation, improved monitoring and prefabricated facility modularity and podularity. Bioprocess intensificationDefining bioprocess intensification (BI) is difficult, for at least four reasons. First, the number of new biological products, from exosomes to DNA vaccines, makes even cataloging new initiatives difficult. Second are the many biomanufacturing advances, including new process development techniques and new manufacturing platforms, equipment and facilities. Third, intensification efforts include many advances in science and technology as they support diverse analytic, diagnostic and therapeutic product applications [1].The fourth difficulty relates to just what improvements in a process should be regarded as BI. Some have applied the term to most any process improvement, but many use it only when referring to getting more product from a process by producing more product per cell, time, volume, footprint or cost [2]. Used this way, BI refers to any activity that increases such common metrics as the cell-specific, volumetric or facility productivity. BI can be accomplished by such improvements as producing more product per time period upstream or retaining more quality product downstream. Defined this way, BI is a subordinate or supporting technology to the so-called nextgeneration or 'factory of the future' initiatives. BI can be enabled by such corollary technologies as continuous or digital biomanufacturing (Figure 1).Many process improvements affect values and metrics not in the original purview of BI. For example, a development initiative intended to improve product quality can also reduce failed batches and thereby increase a plant's annual productivity. Limiting the categorization of an activity to its primary, intended goals can increase clarity. We herein define BI as an activity intended to increase productivity by any metric.

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Development of Novel Bioreactor Control Systems Based on Smart Sensors and Actuators

Cited by 46 publications

References 111 publications

Computational Analysis of Dynamic Light Exposure of Unicellular Algal Cells in a Flat-Panel Photobioreactor to Support Light-Induced CO2 Bioprocess Development

Computational Analysis of Dynamic Light Exposure of Unicellular Algal Cells in a Flat-Panel Photobioreactor to Support Light-Induced CO2 Bioprocess Development

Bioreactor control systems in the biopharmaceutical industry: a critical perspective

Bioprocess Intensification: Aspirations and Achievements

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