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Bioreactor Design and Operational System01:29

Bioreactor Design and Operational System

Bioreactors are engineered vessels designed to cultivate microorganisms under controlled conditions for industrial bioprocessing. They maintain sterility and allow precise regulation of pH, temperature, oxygen, and nutrient levels to optimize microbial growth and metabolite production. Bioreactors range from small laboratory units of 1 liter to industrial systems holding up to 500,000 liters, though only about 75% of their volume is actively used for fermentation. The remaining headspace...
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Strain improvement is a foundational strategy in industrial microbiology aimed at maximizing microbial productivity, particularly because natural isolates typically yield commercially valuable products in very low concentrations. Although optimizing the culture medium and environmental conditions can improve yields, these adjustments are inherently limited by the organism’s genetic potential. As a result, the focus shifts toward genetic modifications to enhance biosynthetic capacity. The...
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Pharmacodynamic (PD) responses describe the interaction between a drug and its biological target, culminating in a physiological effect. These responses can be classified into different types: continuous variables, such as blood glucose levels; categorical outcomes, like survival rates; and time-to-event metrics, such as disease progression. Understanding and modeling PD responses are critical for optimizing drug efficacy and safety.PD models describe the relationship between drug concentration...
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A multi-paradigm modeling framework to simulate dynamic reciprocity in a bioreactor.

Himanshu Kaul1, Zhanfeng Cui, Yiannis Ventikos

  • 1Institute of Biomedical Engineering and Department of Engineering Science, University of Oxford, Oxford, United Kingdom.

Plos One
|April 5, 2013
PubMed
Summary
This summary is machine-generated.

This study introduces a new computational platform that models bioreactor dynamics and cell behavior. It simulates how microenvironment changes affect cell growth and how cells influence their surroundings, optimizing bioreactor design.

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Area of Science:

  • Biotechnology and Biomedical Engineering
  • Computational Biology
  • Cellular Engineering

Background:

  • Bioreactors are often treated as black boxes, limiting optimization through trial and error.
  • Existing computational models struggle to capture the complex interplay between bioreactor dynamics and cellular behavior.
  • A comprehensive approach is needed to understand and predict cell growth within bioreactors.

Purpose of the Study:

  • To present a novel multi-paradigm modeling platform for simulating bioreactor systems.
  • To investigate the bidirectional relationship between cellular activities and the microenvironment.
  • To demonstrate the platform's utility in optimizing bioreactor design and understanding cell behavior.

Main Methods:

  • Coupling an agent-based modeling platform with a computational fluid dynamics framework.
  • Simulating virtual bioreactors with agent-based cells exhibiting proliferation, migration, chemotaxis, and apoptosis.
  • Incorporating mass transport phenomena and cell-specific probabilistic parameters into the model.

Main Results:

  • The platform successfully captured the impact of bioreactor transport processes on cellular behavior.
  • It also demonstrated how cellular activities influence local mass transport and overall cell growth.
  • Validation through simulation of cellular chemotaxis in a direct visualization chamber showed agreement with experimental data.

Conclusions:

  • The developed multi-paradigm platform offers a comprehensive perspective on bioreactor system dynamics.
  • It can predict the effects of bioreactor parameters on cell populations and vice versa.
  • This tool can serve as a concept selection tool for optimizing bioreactor design specifications.