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Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

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Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
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Physiological Pharmacokinetic Models: Blood Flow-Limited Versus Diffusion-Limited Models00:57

Physiological Pharmacokinetic Models: Blood Flow-Limited Versus Diffusion-Limited Models

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Physiological pharmacokinetic models, often called flow-limited or perfusion models, typically assume a swift drug distribution between tissue and venous blood, creating a rapid drug equilibrium. This premise is based on the idea that drug diffusion is extremely fast, and the cell membrane presents no barrier to drug permeation. In this scenario, where no drug binding occurs, the drug concentration in the tissue equals that of the venous blood leaving the tissue. This greatly simplifies the...
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Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

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Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
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Mesh Analysis01:20

Mesh Analysis

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Mesh analysis is a valuable method for simplifying circuit analysis using mesh currents as key circuit variables. Unlike nodal analysis, which focuses on determining unknown voltages, mesh analysis applies Kirchhoff's voltage law (KVL) to find unknown currents within a circuit. This method is particularly convenient in reducing the number of simultaneous equations that need to be solved.
A fundamental concept in mesh analysis is the definition of meshes and mesh currents. A mesh is a closed...
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Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

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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...
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One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation

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This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
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Related Experiment Video

Updated: Nov 15, 2025

A Method for Determination and Simulation of Permeability and Diffusion in a 3D Tissue Model in a Membrane Insert System for Multi-well Plates
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A Method for Determination and Simulation of Permeability and Diffusion in a 3D Tissue Model in a Membrane Insert System for Multi-well Plates

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Adaptive mesh refinement and coarsening for diffusion-reaction epidemiological models.

Malú Grave1, Alvaro L G A Coutinho1

  • 1Department of Civil Engineering, COPPE/Federal University of Rio de Janeiro, P.O. Box 68506, Rio de Janeiro, RJ 21945-970 Brazil.

Computational Mechanics
|March 2, 2021
PubMed
Summary

This study enhances the Susceptible, Exposed, Infected, Recovered, and Deceased (SEIRD) model for COVID-19 spread. The new diffusion-reaction model captures spatio-temporal dynamics and includes travel-related introductions of the virus.

Keywords:
Adaptive mesh refinement and coarseningCOVID-19Compartmental modelsDiffusion–reactionPartial differential equations

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Area of Science:

  • Mathematical Biology
  • Epidemiology
  • Computational Science

Background:

  • The COVID-19 pandemic highlighted the need for advanced infectious disease modeling.
  • Traditional compartmental models like SEIRD often lack spatial dynamics and population movement considerations.
  • Ordinary differential equation (ODE) based SEIRD models are insufficient for capturing continuous spatio-temporal spread.

Purpose of the Study:

  • To extend the SEIRD model to a diffusion-reaction system of partial differential equations (PDEs).
  • To incorporate continuous spatio-temporal dynamics and population movement into infectious disease modeling.
  • To develop a flexible computational framework for simulating disease spread across various spatial scales.

Main Methods:

  • Formulation of a SEIRD model using PDEs to represent diffusion and reaction processes.
  • Inclusion of a source term to model virus introduction via returning travelers.
  • Implementation using the libMesh finite element library, supporting adaptive mesh refinement for multi-scale analysis.
  • Consideration of anisotropic and non-homogeneous diffusion characteristics.

Main Results:

  • The developed diffusion-reaction PDE model successfully captures spatio-temporal disease dynamics.
  • The model demonstrates enhanced capabilities compared to standard ODE-based SEIRD models.
  • Verification against standard SEIRD models confirms the model's validity and highlights new features.

Conclusions:

  • The PDE-based diffusion-reaction model provides a more comprehensive approach to modeling infectious disease spread, including spatial factors.
  • The implementation in libMesh allows for efficient and adaptive simulation across different spatial resolutions.
  • This advanced modeling framework offers new possibilities for understanding and managing pandemics like COVID-19.