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Related Concept Videos

Pharmacokinetic Models: Overview01:20

Pharmacokinetic Models: Overview

Pharmacokinetic models utilize mathematical analysis to achieve a detailed quantitative understanding of a drug's life cycle within the body. They are instrumental in simulating a drug's pharmacokinetic parameters, predicting drug concentrations over time, optimizing dosage regimens, linking concentrations with pharmacologic activity, and estimating potential toxicity.
There are three primary types of models: empirical, compartment, and physiological. Empirical models, with minimal assumptions,...
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.
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...
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...
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...

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An All-Human Hepatic Culture System for Drug Development Applications
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MEGen: A Physiologically Based Pharmacokinetic Model Generator.

George Loizou1, Alex Hogg

  • 1Health and Safety Laboratory Buxton, UK.

Frontiers in Pharmacology
|November 16, 2011
PubMed
Summary
This summary is machine-generated.

Physiologically based pharmacokinetic (PBPK) models are complex. MEGen is a new web application designed for the rapid construction and documentation of PBPK model code, aiming to simplify their use.

Keywords:
databaseequationgeneratorpharmacokineticphysiologically based

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Area of Science:

  • Pharmacokinetics and computational modeling

Background:

  • Physiologically based pharmacokinetic (PBPK) models are increasingly utilized across various scientific domains.
  • Despite their utility, PBPK models are often perceived as complex, data-intensive, resource-heavy, and time-consuming to develop and validate.
  • The complexity of the underlying equations presents challenges for model verification and validation.

Purpose of the Study:

  • To introduce MEGen, a novel web application designed to streamline the creation and documentation of deterministic PBPK models.
  • To address the perceived complexity and resource demands associated with PBPK model development.

Main Methods:

  • Development of MEGen, a web application featuring a parameter database and a model code generator.
  • The code generator produces PBPK model code compatible with multiple commercial software packages and one freely available option.

Main Results:

  • MEGen facilitates the rapid construction of bespoke deterministic PBPK models.
  • The application supports the generation of model code for diverse software environments, enhancing accessibility and usability.
  • An overview of MEGen's current functionalities is presented.

Conclusions:

  • MEGen offers a potential solution to the challenges of PBPK model complexity and development time.
  • Future developments are planned to further enhance the capabilities and application of MEGen in pharmacokinetic modeling.
  • The tool aims to improve the accessibility and efficiency of PBPK model development and utilization.