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Related Concept Videos

Model Approaches for Pharmacokinetic Data: Compartment Models01:14

Model Approaches for Pharmacokinetic Data: Compartment Models

161
Compartmental analysis is a widely adopted approach to characterizing drug pharmacokinetics. It uses compartment models that conceptualize the body as a collection of reversibly communicating compartments, each representing a group of tissues exhibiting similar drug distribution characteristics. The movement rate of the drug between these compartments is typically described by first-order kinetics.
Two primary types of compartment models are recognized: mammillary and catenary. The more...
161
Three-Compartment Open Model01:06

Three-Compartment Open Model

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The three-compartment open model is a pharmacokinetic model used to describe the distribution and elimination of drugs following extravascular administration. It comprises a central compartment representing the plasma and two peripheral compartments. The highly perfused peripheral compartment represents organs and tissues with a rich blood supply, such as the liver, kidneys, and lungs. The scarcely perfused peripheral compartment represents tissues with lower blood supply, such as adipose...
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Compartment Models: Single-Compartment Model01:14

Compartment Models: Single-Compartment Model

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The single-compartment model serves as a simplified representation of the human body. This model assumes that the body functions as a single, well-mixed open compartment. When a drug is administered intravenously, it enters the body and quickly distributes uniformly. The drug then undergoes biotransformation and elimination, ultimately leaving the body. The volume of this compartment is referred to as the apparent volume of distribution into which the drug can uniformly distribute. In this...
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Mechanistic Models: Overview of Compartment Models01:21

Mechanistic Models: Overview of Compartment Models

131
Mechanistic models, a category encompassing both physiological and compartmental modeling, differ from empirical models' approaches to incorporating known factors about the systems being modeled. Empirical models describe data with minimal assumptions, while mechanistic models aim to provide a robust description of available data by specifying assumptions and integrating known factors about the system. Compartmental analysis is a key example of a mechanistic model in pharmacokinetics and...
131
Compartment Models: Two-Compartment Model01:20

Compartment Models: Two-Compartment Model

5.8K
The two-compartment model divides the body into central and peripheral compartments to account for varying blood perfusion rates among organs and tissues, affecting drug distribution. The central compartment includes blood and highly perfused tissues with rapid drug distribution, while the peripheral compartment contains tissues with slower drug distribution. After a single IV bolus dose, the drug concentration is high in plasma and low in tissues. The drug distribution between compartments...
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Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

71
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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Related Experiment Video

Updated: Aug 8, 2025

A Data-Driven Approach to Quantifying Immune States in Sepsis
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A Data-Driven Approach to Quantifying Immune States in Sepsis

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Kalman-based compartmental estimation for covid-19 pandemic using advanced epidemic model.

Sumanta Kumar Nanda1, Guddu Kumar1, Vimal Bhatia1,2

  • 1Department of Electrical Engineering, Indian Institute of Technology Indore, Indore, India.

Biomedical Signal Processing and Control
|March 6, 2023
PubMed
Summary

This study introduces a new SEIRPV compartmental model for COVID-19, enhancing epidemic modeling with exposed, recovered, deceased, and vaccinated states. The model, utilizing a cubature Kalman filter, offers improved quantitative insights for public health interventions.

Keywords:
Compartment-based epidemic modelCubature ruleKalman filter

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Area of Science:

  • Epidemiology
  • Mathematical Modeling
  • Public Health

Background:

  • Effective COVID-19 prevention relies on quantitative data regarding transmission factors.
  • Existing SIR models offer a basic framework but lack detailed compartments for comprehensive analysis.

Purpose of the Study:

  • Introduce a novel SEIRPV compartmental model for COVID-19.
  • Enhance the quantitative basis for administrative public health measures.
  • Stochastically model exposed, infected, and vaccinated populations within a unified framework.

Main Methods:

  • Developed a nonlinear, stochastic SEIRPV (Susceptible, Exposed, Infected, Recovered-exposed, Recovered-infected, Passed away, Vaccinated) model.
  • Employed the cubature Kalman filter (CKF) for nonlinear estimation of compartmental populations.
  • Analyzed model properties including stability, equilibrium, and reproduction rate.

Main Results:

  • The SEIRPV model provides a more detailed and stochastic representation of COVID-19 dynamics.
  • CKF demonstrated accurate estimation with manageable computational cost.
  • Model performance was validated using real-world COVID-19 outbreak data.

Conclusions:

  • The proposed SEIRPV model offers a significant advancement in COVID-19 epidemic modeling.
  • This enhanced modeling approach can strengthen the practicality and effectiveness of public health interventions.
  • The study highlights the value of integrating stochasticity and detailed compartments for disease control.