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Related Concept Videos

Pharmacokinetic Models: Comparison and Selection Criterion01:26

Pharmacokinetic Models: Comparison and Selection Criterion

66
Physiological and compartmental models are valuable tools used in studying biological systems. These models rely on differential equations to maintain mass balance within the system, ensuring an accurate representation of the dynamic processes at play.
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.
66
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

68
Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
68
Model Approaches for Pharmacokinetic Data: Physiological Models01:15

Model Approaches for Pharmacokinetic Data: Physiological Models

41
Physiological models in pharmacokinetics are instrumental in understanding the distribution and elimination of drugs within the body. These models describe the drug concentration within target organs, influenced by factors such as drug uptake, tissue volume, and blood flow. Drug uptake is governed by the partition coefficient, which signifies the drug concentration ratio in tissue to that in the blood. The blood flow rate to a specific tissue is expressed as Qt, and the rate of change in tissue...
41
Typical Model Studies01:30

Typical Model Studies

354
Fluid mechanics model studies often utilize scaled-down systems to predict fluid behavior in full-scale environments, such as river flows, dam spillways, and structures interacting with open surfaces. Maintaining Froude number similarity in river models is crucial, as it replicates surface flow features like wave patterns and velocities.
354
Pharmacokinetic Models: Overview01:20

Pharmacokinetic Models: Overview

647
Pharmacokinetic models utilize mathematical analysis to achieve a detailed quantitative understanding of a drug's life cycle within the body. They are instrumental in simulating a drug's pharmacokinetic parameters, predicting drug concentrations over time, optimizing dosage regimens, linking concentrations with pharmacologic activity, and estimating potential toxicity.
There are three primary types of models: empirical, compartment, and physiological. Empirical models, with minimal...
647
Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches01:14

Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches

112
Drug disposition in the body is a complex process and can be studied using two major approaches: the model and the model-independent approaches.
The model approach uses mathematical models to describe changes in drug concentration over time. Pharmacokinetic models help characterize drug behavior in patients, predict drug concentration in the body fluids, calculate optimum dosage regimens, and evaluate the risk of toxicity. However, ensuring that the model fits the experimental data accurately...
112

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Related Experiment Video

Updated: Jun 22, 2025

Generic Protocol for Optimization of Heterologous Protein Production Using Automated Microbioreactor Technology
06:24

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Integration Approaches to Model Bioreactor Hydrodynamics and Cellular Kinetics for Advancing Bioprocess Optimisation.

Vishal Kumar Singh1, Ioscani Jiménez Del Val2, Jarka Glassey1,3

  • 1Process and Chemical Engineering, School of Engineering and Architecture, University College Cork, T12 K8AF Cork, Ireland.

Bioengineering (Basel, Switzerland)
|June 27, 2024
PubMed
Summary

Integrated computational fluid dynamics (CFD) and cell reaction kinetic (CRK) models improve large-scale bioprocess efficiency by simulating cellular responses to environmental gradients. This supports intelligent biomanufacturing and process optimization.

Keywords:
bioprocess modellingcell reaction kineticscomputational fluid dynamicsdigitalisationprocess optimisation

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Area of Science:

  • Biotechnology
  • Biochemical Engineering
  • Process Systems Engineering

Background:

  • Large-scale bioprocesses face challenges with decreased mixing efficiency and pronounced environmental gradients as fermenter volumes increase.
  • These gradients negatively impact cell performance, process efficiency, and overall profitability in industrial biomanufacturing.
  • Computational fluid dynamics (CFD) is crucial for simulating bioprocess performance and aiding scale-up, scale-down, and optimization.

Purpose of the Study:

  • To review the benefits of integrating CFD with dynamic Cell Reaction Kinetic (CRK) modeling for bioprocess analysis.
  • To explore various approaches for coupling CFD-based bioreactor hydrodynamic models with CRK models.
  • To assess the suitability of different coupling strategies concerning computational demands in bioprocess modeling.

Main Methods:

  • Integration of Computational Fluid Dynamics (CFD) simulations with dynamic Cell Reaction Kinetic (CRK) models.
  • Development and analysis of various coupling strategies for CFD and CRK models.
  • Evaluation of computational load associated with different integrated modeling approaches.

Main Results:

  • Coupled CFD-CRK models provide valuable insights into cellular responses to hydrodynamic variations in large-scale bioprocesses.
  • Different integration approaches offer varying levels of detail and computational efficiency for bioprocess simulation.
  • The study highlights the potential for informed decision-making in intelligent biomanufacturing through these integrated models.

Conclusions:

  • Integrated CFD-CRK modeling is a powerful tool for understanding and optimizing large-scale bioprocesses.
  • The choice of coupling approach impacts the trade-off between simulation accuracy and computational cost.
  • These advanced modeling techniques align with Industry 4.0 principles, driving digitalization and automation in biomanufacturing.