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Related Concept Videos

Mechanistic Models: Overview of Compartment Models01:21

Mechanistic Models: Overview of Compartment Models

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...
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 Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

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...
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.
Pharmacodynamic Models: Link Model and Systems Pharmacodynamic Model01:14

Pharmacodynamic Models: Link Model and Systems Pharmacodynamic Model

The link model is a fundamental pharmacokinetic-pharmacodynamic (PK–PD) approach to account for delayed drug responses when the observed effect does not immediately correlate with the drug's plasma concentration peak. This delay is mathematically addressed by introducing an effect compartment concentration, Ce, which is kinetically linked to the plasma concentration, Cp, via a first-order rate constant, ke0. The linkage allows for a more accurate prediction of drug effects over time. A higher...

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Related Experiment Video

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Endothelialized Microfluidics for Studying Microvascular Interactions in Hematologic Diseases
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Vascular microphysiological systems (MPS): biologically relevant and potent models.

Lucas Breuil1, Atsuya Kitada1, Sachin Yadav1

  • 1Department of Micro Engineering, Kyoto University, Kyoto Daigaku-katsura, Nishikyo-ku, Kyoto 615-8540, Japan. yokokawa.ryuji.8c@kyoto-u.ac.jp.

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Vascular microphysiological systems (MPS) offer advanced 3D models for studying blood vessel biology. These organ-on-a-chip systems overcome limitations of traditional models for vascular research and drug development.

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Area of Science:

  • Biomedical Engineering
  • Vascular Biology
  • Microfluidics

Background:

  • Traditional in vitro models lack the complexity of native vasculature.
  • In vivo models present ethical and physiological relevance challenges.
  • Advanced models are needed to study vascular biology and pathology.

Purpose of the Study:

  • To review the relevance and capabilities of vascular microphysiological systems (MPS).
  • To highlight how MPS overcome limitations of traditional research models.
  • To discuss applications of MPS in disease modeling and drug development.

Main Methods:

  • Utilizing microfluidic channels and 3D structures to create vascular MPS.
  • Incorporating diverse cellular and acellular components.
  • Mimicking the physiological microenvironment of blood vessels.

Main Results:

  • Vascular MPS replicate 3D architecture and multi-component interactions.
  • These systems enable investigation of vascular responses to physiological cues.
  • MPS facilitate complex biological processes relevant to vascular health and disease.

Conclusions:

  • Vascular MPS represent a powerful in vitro tool for advancing vascular biology.
  • Organ-on-a-chip technology provides physiologically relevant models.
  • Vascular MPS are crucial for disease modeling and accelerating drug discovery.