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Related Concept Videos

Noncompartmental Analysis: Mean Residence Time01:05

Noncompartmental Analysis: Mean Residence Time

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According to statistical moment theory, mean residence time (MRT) is an important measure in pharmacokinetics. MRT can be defined as the expected mean of a probability density function distribution. It provides valuable insights into drug disposition in the body.
After the administration of a drug through intravenous bolus injection, the drug molecules are distributed throughout the body and remain there for varying periods. The MRT represents the average time these drug molecules stay in the...
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Estimating Virus Production Rates in Aquatic Systems
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Residence time distribution in continuous virus filtration.

Yu-Cheng Chen1,2, Gabriele Recanati2, Fernando De Mathia2

  • 1Key Laboratory of Biomass Chemical Engineering of Ministry of Education, Zhejiang Key Laboratory of Smart Biomaterials, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou, China.

Biotechnology and Bioengineering
|March 18, 2024
PubMed
Summary
This summary is machine-generated.

A new model predicts residence time distribution (RTD) in continuous virus filtration for biologics manufacturing. This model accounts for nonideal mixing and film resistance, improving material traceability and potentially reducing antibody consumption.

Keywords:
continuous manufacturingdownstream processingmechanistic modelmonoclonal antibodyresidence time distributionvirus filtration

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Area of Science:

  • Biologics Manufacturing
  • Chemical Engineering
  • Process Analytical Technology

Background:

  • Continuous manufacturing is increasingly adopted in biologics production.
  • Residence Time Distribution (RTD) is crucial for material traceability but poorly understood in continuous virus filtration.
  • Scale-up and fluid dynamics of continuous virus filtration require better modeling.

Purpose of the Study:

  • To develop and validate a model for predicting RTD in continuous virus filtration.
  • To incorporate nonideal mixing and film resistance into RTD predictions.
  • To enable accurate RTD modeling for improved process understanding and control.

Main Methods:

  • Developed a model considering nonideal mixing and film resistance for RTD prediction.
  • Experimentally validated the model using pulse injection of inert tracer (NaNO3).
  • Performed validation using stepwise and combined stepwise/pulse injection experiments.

Main Results:

  • Model calibration showed good agreement with experimental data (R² = 0.90).
  • Validated model accurately predicted RTD under various conditions (R² = 0.97).
  • Demonstrated model's ability to extrapolate RTD predictions for recombinant antibodies.

Conclusions:

  • The developed RTD model accurately predicts fluid dynamics in continuous virus filtration.
  • The model facilitates material traceability and can optimize downstream processes.
  • It offers potential for significant savings in biologics manufacturing, particularly antibody consumption.