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Related Concept Videos

Model Approaches for Pharmacokinetic Data: Physiological Models01:15

Model Approaches for Pharmacokinetic Data: Physiological Models

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...
Physiological Pharmacokinetic Models: Blood Flow-Limited Versus Diffusion-Limited Models00:57

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

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...
Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis00:59

Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis

Noncompartmental analyses offer an alternative method for describing drug pharmacokinetics without relying on a specific compartmental model. In this approach, the drug's pharmacokinetics are assumed to be linear, with the terminal phase log-linear. This assumption allows for simplified analysis and interpretation of the drug's behavior in the body.
One important characteristic of noncompartmental analyses is that drug exposure increases proportionally with increasing doses. This relationship...
One-Compartment Open Model for Extravascular Administration: Zero-Order Absorption Model01:12

One-Compartment Open Model for Extravascular Administration: Zero-Order Absorption Model

Extravascular administration, such as oral or intramuscular routes, is a non-invasive drug delivery method, often preferred for ease and patient compliance. A key factor here is absorption, which dictates how quickly and effectively the drug enters the bloodstream from the administration site. Absorption follows either zero-order or first-order kinetics.
Zero-order absorption maintains a steady rate irrespective of the amount of drug left to be absorbed, making it a constant process. In the...
Model Approaches for Pharmacokinetic Data: Compartment Models01:14

Model Approaches for Pharmacokinetic Data: Compartment Models

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...
Pharmacokinetic Models: Comparison and Selection Criterion01:26

Pharmacokinetic Models: Comparison and Selection Criterion

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.

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Related Experiment Video

Updated: Jun 6, 2026

Arteriovenous Metabolomics to Measure In Vivo Metabolite Exchange in Brown Adipose Tissue
02:55

Arteriovenous Metabolomics to Measure In Vivo Metabolite Exchange in Brown Adipose Tissue

Published on: October 6, 2023

Modeling nonsteady-state metabolism from arteriovenous data.

Erica Manesso1, Gianna M Toffolo, Rita Basu

  • 1Department of Information Engineering, University of Padova, Padova 35129, Italy. erica.manesso@thep.lu.se

IEEE Transactions on Bio-Medical Engineering
|December 8, 2010
PubMed
Summary

Accurate organ substance production measurement requires accounting for transit time, not just steady state. This new model improves accuracy for substances like insulin, especially during dynamic physiological changes.

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Continuous Blood Sampling in Small Animal Positron Emission Tomography/Computed Tomography Enables the Measurement of the Arterial Input Function
10:21

Continuous Blood Sampling in Small Animal Positron Emission Tomography/Computed Tomography Enables the Measurement of the Arterial Input Function

Published on: August 8, 2019

Related Experiment Videos

Last Updated: Jun 6, 2026

Arteriovenous Metabolomics to Measure In Vivo Metabolite Exchange in Brown Adipose Tissue
02:55

Arteriovenous Metabolomics to Measure In Vivo Metabolite Exchange in Brown Adipose Tissue

Published on: October 6, 2023

Continuous Blood Sampling in Small Animal Positron Emission Tomography/Computed Tomography Enables the Measurement of the Arterial Input Function
10:21

Continuous Blood Sampling in Small Animal Positron Emission Tomography/Computed Tomography Enables the Measurement of the Arterial Input Function

Published on: August 8, 2019

Area of Science:

  • Physiology
  • Biomedical Engineering
  • Pharmacokinetics

Background:

  • The Fick principle, using arteriovenous (AV) concentration differences, is standard for measuring organ/tissue production but is limited to steady-state conditions.
  • Non-steady-state conditions necessitate accounting for the substance's transit time through the system, as proposed by Zierler.
  • Accurate assessment of substance production in dynamic physiological states remains a challenge.

Purpose of the Study:

  • To develop and validate a novel modeling approach that incorporates parametric descriptions of production and transit time for accurate substance production estimation.
  • To assess the impact of non-negligible transit times on the estimation of pancreatic insulin secretion.
  • To compare the novel modeling approach with the simplified steady-state Fick equation.

Main Methods:

  • A parametric modeling approach was developed to estimate unknown parameters for substance production and transit time using AV data.
  • C-peptide concentrations were measured in the femoral artery and hepatic vein of 12 subjects during a meal.
  • Pancreatic insulin secretion was estimated using the novel model and compared to estimates from the steady-state Fick equation.

Main Results:

  • The proposed modeling approach successfully estimated transit time and reconstructed substance production.
  • Accounting for transit time significantly affected the estimation of pancreatic insulin secretion, particularly in the early postprandial period.
  • Even a relatively short mean transit time (3.3 ± 1.3 min) for C-peptide across the splanchnic bed impacted secretion profile accuracy.

Conclusions:

  • The study highlights the critical importance of accounting for non-negligible transit times in substance production measurements, even when transit times are relatively short.
  • The novel modeling approach provides a more accurate estimation of dynamic physiological processes, such as insulin secretion, compared to traditional steady-state methods.
  • This methodology offers a valuable tool for understanding organ/tissue function in non-steady-state conditions.