Automated Compartment Model Development Based on Data from Flow-Following Sensor Devices

Milligrams to kilograms: making microbes work at scale

If biomanufacturing can become a sustainable route for producing chemicals, it will provide a critical step in reducing greenhouse gas emissions to fight climate change. However, efforts to industrialize microbial synthesis of chemicals have met with varied success, due, in part, to challenges in translating laboratory successes to industrial scale. With a particular focus on Escherichia coli, this review examines the lessons learned when studying microbial physiology and metabolism under conditions that simulate large-scale bioreactors and methods to minimize cellular waste through reduction of maintenance energy, optimizing the stress response and minimizing culture heterogeneity. With general strategies to overcome these challenges, biomanufacturing process scale-up could be de-risked and the time and cost of bringing promising syntheses to market could be reduced.

Microbial lifelines in bioprocesses: From concept to application

Bioprocesses are scaled up for the production of large product quantities. With larger fermenter volumes, mixing becomes increasingly inefficient and environmental gradients get more prominent than in smaller scales. Environmental gradients have an impact on the microorganism's metabolism, which makes the prediction of large-scale performance difficult and can lead to scale-up failure. A promising approach for improved understanding and estimation of dynamics of microbial populations in large-scale bioprocesses is the analysis of microbial lifelines. The lifeline of a microbe in a bioprocess is the experience of environmental gradients from a cell's perspective, which can be described as a time series of position, environment and intracellular condition. Currently, lifelines are predominantly determined using models with computational fluid dynamics, but new technical developments in flow-following sensor particles and microfluidic single-cell cultivation open the door to a more interdisciplinary concept. We critically review the current concepts and challenges in lifeline determination and application of lifeline analysis, as well as strategies for the integration of these techniques into bioprocess development. Lifelines can contribute to a successful scale-up by guiding scale-down experiments and identifying strain engineering targets or bioreactor optimisations.

Special Issue on “Bioreactor System: Design, Modeling and Continuous Production Process”

Biochemical engineering deals with the processing of biological or chemical materials using enzymes or living cells as biological catalysts [...]

Mathematical Analysis of a Low Cost Mechanical Ventilator Respiratory Dynamics Enhanced by a Sensor Transducer (ST) Based in Nanostructures of Anodic Aluminium Oxide (AAO)

Mechanical ventilation systems require a device for measuring the air flow provided to a patient in order to monitor and ensure the correct quantity of air proportionated to the patient, this device is the air flow sensor. At the beginning of the COVID-19 pandemic, flow sensors were not available in Peru because of the international supply shortage. In this context, a novel air flow sensor based on an orifice plate and an intelligent transducer was developed to form an integrated device. The proposed design was focused on simple manufacturing requirements for mass production in a developing country. CAD and CAE techniques were used in the design stage, and a mathematical model of the device was proposed and calibrated experimentally for the measured data transduction. The device was tested in its real working conditions and was therefore implemented in a breathing circuit connected to a low-cost mechanical ventilation system. Results indicate that the designed air flow sensor/transducer is a low-cost complete medical device for mechanical ventilators that is able to provide all the ventilation parameters by an equivalent electrical signal to directly display the following factors: air flow, pressure and volume over time. The evaluation of the designed sensor transducer was performed according to sundry transducer parameters such as geometrical parameters, material parameters and adaptive coefficients in the main transduction algorithm; in effect, the variety of the described results were achieved by the faster response time and robustness proportionated by transducers of nanostructures based on Anodic Aluminum Oxide (AAO), which enhanced the designed sensor/transducer (ST) during operation in intricate geographic places, such as the Andes mountains of Peru.