Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

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...
Molecular Models02:00

Molecular Models

Physical models representing molecular architectures of chemical compounds play essential roles in understanding chemistry. The use of molecular models makes it easier to visualize the structures and shapes of atoms and molecules.
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...
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...
Relation between Mathematical Equations and Block Diagrams01:20

Relation between Mathematical Equations and Block Diagrams

In a spring-mass-damper system, the second-order differential equation describes the dynamic behavior of the system. When transformed into the Laplace domain under zero initial conditions, this equation can be effectively analyzed and manipulated. The transformation into the Laplace domain converts differential equations into algebraic equations, simplifying the process of isolating the output.
Pharmacodynamic Models: Overview01:27

Pharmacodynamic Models: Overview

Pharmacodynamic (PD) responses describe the interaction between a drug and its biological target, culminating in a physiological effect. These responses can be classified into different types: continuous variables, such as blood glucose levels; categorical outcomes, like survival rates; and time-to-event metrics, such as disease progression. Understanding and modeling PD responses are critical for optimizing drug efficacy and safety.PD models describe the relationship between drug concentration...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

The Empirical Bayes Variational Autoencoder-A Neural ODE Approach for Population Modeling in Pharmacology.

CPT: pharmacometrics & systems pharmacology·2026
Same author

Modeling Peak Expiratory Flow in Patients With Asthma and Quantifying Treatment Effects Using a Mixed-Effects Hidden Markov Model.

CPT: pharmacometrics & systems pharmacology·2026
Same author

Postprandial glucose profiles may reflect heterogeneity in insulin secretion and sensitivity in type 2 diabetes.

Metabolism: clinical and experimental·2026
Same author

MCMC Correction of Score-Based Diffusion Models for Model Composition.

Entropy (Basel, Switzerland)·2026
Same author

Confidence-based prediction of antibiotic resistance at the patient level.

mBio·2026
Same author

Avenanthramides and avenacosides as biomarkers of oat intake: a pharmacokinetic study of solid and liquid oat consumption under single and repeated dose conditions.

Nutrition journal·2025
Same journal

Targeting the GLP-1 receptor pathways for dual management of obesity and depression.

Drug discovery today·2026
Same journal

Chemical intervention strategies targeting MYC for cancer therapy.

Drug discovery today·2026
Same journal

How many protein pairs can we chemically target?

Drug discovery today·2026
Same journal

From trial-and-error to inverse design: how AI is redefining drug delivery systems.

Drug discovery today·2026
Same journal

Critical evaluation of the key mediators causing life-threatening symptoms during human anaphylaxis.

Drug discovery today·2026
Same journal

A20 as a novel immunoregulatory target for neuroinflammation.

Drug discovery today·2026
See all related articles

Related Experiment Video

Updated: Jun 15, 2026

A Web Tool for Generating High Quality Machine-readable Biological Pathways
08:01

A Web Tool for Generating High Quality Machine-readable Biological Pathways

Published on: February 8, 2017

Biochemical modeling with Systems Biology Graphical Notation.

Andreas Jansson1, Mats Jirstrand

  • 1Fraunhofer-Chalmers Centre, Chalmers Science Park, 412 88 Göteborg, Sweden.

Drug Discovery Today
|March 10, 2010
PubMed
Summary
This summary is machine-generated.

Systems Biology Graphical Notation (SBGN) offers a standardized visual language for systems biology research. PathwayLab enables users to easily build and simulate SBGN models using a drag-and-drop interface.

More Related Videos

Modeling an Enzyme Active Site using Molecular Visualization Freeware
14:37

Modeling an Enzyme Active Site using Molecular Visualization Freeware

Published on: December 25, 2021

DeepOmicsAE: Representing Signaling Modules in Alzheimer's Disease with Deep Learning Analysis of Proteomics, Metabolomics, and Clinical Data
09:47

DeepOmicsAE: Representing Signaling Modules in Alzheimer's Disease with Deep Learning Analysis of Proteomics, Metabolomics, and Clinical Data

Published on: December 15, 2023

Related Experiment Videos

Last Updated: Jun 15, 2026

A Web Tool for Generating High Quality Machine-readable Biological Pathways
08:01

A Web Tool for Generating High Quality Machine-readable Biological Pathways

Published on: February 8, 2017

Modeling an Enzyme Active Site using Molecular Visualization Freeware
14:37

Modeling an Enzyme Active Site using Molecular Visualization Freeware

Published on: December 25, 2021

DeepOmicsAE: Representing Signaling Modules in Alzheimer's Disease with Deep Learning Analysis of Proteomics, Metabolomics, and Clinical Data
09:47

DeepOmicsAE: Representing Signaling Modules in Alzheimer's Disease with Deep Learning Analysis of Proteomics, Metabolomics, and Clinical Data

Published on: December 15, 2023

Area of Science:

  • Systems Biology
  • Bioinformatics
  • Computational Biology

Background:

  • The expanding field of systems biology requires standardized methods for knowledge representation.
  • Effective communication of complex biological systems is essential for research advancement.

Purpose of the Study:

  • To introduce the Systems Biology Graphical Notation (SBGN) as a practical standard.
  • To demonstrate the utility of PathwayLab for building and simulating SBGN models.

Main Methods:

  • Utilizing a drag-and-drop graphical user interface within PathwayLab.
  • Applying the Systems Biology Graphical Notation (SBGN) for model construction.

Main Results:

  • SBGN provides a standardized graphical language for systems biology.
  • PathwayLab facilitates the practical application of SBGN through an intuitive interface.

Conclusions:

  • SBGN is a valuable tool for enhancing communication in systems biology.
  • PathwayLab simplifies the process of creating and simulating biological models using SBGN.