Bioprocessing Optimization
Bioprocessing Optimization - Related Videos
07:42
Overview of Bioprocess Engineering
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2023
Bioprocessing is a method that uses living organisms to produce a desired target product. Often, bioprocessing refers to the use of bioreactors to produce protein products from genetically engineered organisms. This field is responsible for the large-scale manufacture of biotherapeutics; drugs that have become essential to improving the quality of life for many with complex diseases like cancer, autoimmune diseases and HIV/AIDS. This video will introduce the engineering approach to designing a...
07:26
In Situ Microscopy for Real-time Determination of Single-cell Morphology in Bioprocesses
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Cited by 5 •
2019
A photo-optical in situ microscopy device was developed to monitor the size of single cells directly in the cell suspension. The real-time measurement is conducted by coupling the photo-optical sterilizable probe to an automated image analysis. Morphological changes appear with dependence on the growth state and cultivation conditions.
06:24
Generic Protocol for Optimization of Heterologous Protein Production Using Automated Microbioreactor Technology
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Cited by 9 •
2017
This manuscript describes a generic approach for tailor-made design of microbial cultivation media. This is enabled by an iterative workflow combining Kriging-based experimental design and microbioreactor technology for sufficient cultivation throughput, which is supported by lab robotics to increase reliability and speed in liquid handling media preparation.
03:37
Optimal Foraging - Concepts
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2019
Optimal Foraging Organisms must acquire and use resources in their environment to survive. While food is one of the primary resources organisms must search for, individuals also need to seek habitats, shelter, and mates. This process of searching for resources is known as foraging, which involves a series of costs and benefits. More specifically, acquiring a resource provides the organism with a benefit, however, searching and capturing the resource requires expenditure of time and energy.
00:48
Optimal Foraging
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2019
How animals obtain and eat their food is called foraging behavior. Foraging can include searching for plants and hunting for prey and depends on the species and environment. Optimal foraging theory states that natural selection favors foraging strategies that balance the benefits of a particular food, such as energy and nutrients, with the costs of obtaining it, such as energy expenditure and the risk of predation. Optimal foraging maximizes benefits while minimizing costs. For the Crows
FAQs
Researchers compare process data with outcomes such as cell growth, product quality, consistency, and yield. Controlled experiments then vary parameters including temperature, pH, nutrient delivery, agitation, aeration, and dissolved oxygen. This approach helps distinguish influential conditions from less important ones, allowing teams to target the factors that most strongly restrict production performance.
Cells and microorganisms respond to a combination of environmental and nutritional conditions, so changing one parameter can alter the effectiveness of others. Monitoring these variables together helps maintain a favorable production state instead of optimizing a single measurement in isolation. This coordinated control supports more stable growth, product formation, and batch-to-batch consistency.
Data analysis reveals relationships between critical process parameters and biological outcomes, while process modeling provides a structured way to interpret those relationships. Together, they help identify limiting factors, evaluate controlled experiments, and guide adjustments based on evidence rather than trial and error. These tools also support more reliable movement from laboratory systems toward industrial bioreactors.
A typical workflow begins by selecting measurable process parameters and monitoring them during cell culture or microbial fermentation. Researchers then conduct controlled experiments, analyze the resulting growth and production data, and use the findings to adjust operating conditions. Repeated evaluation focuses on improving yield, consistency, and product quality while preserving conditions that support biological activity.
Important variables include temperature, pH, nutrient delivery, agitation, aeration, and dissolved oxygen. These measurements describe whether the biological system remains within conditions favorable for growth and production. Monitoring them provides the information needed to detect unfavorable changes, compare experimental conditions, and make controlled adjustments in laboratory cultures or larger bioreactor systems.
The approach supports cell cultures, microbial fermentations, recombinant protein production, vaccine development, enzyme production, and other bioproducts. Its value extends beyond improving a single laboratory result: optimization helps reduce variability and establish more reliable manufacturing as processes move toward larger bioreactors. The same principles therefore connect biological research with production-scale development.