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Related Concept Videos

Pharmacokinetic Models: Overview01:20

Pharmacokinetic Models: Overview

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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.
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Fundamental Mathematical Principles in Pharmacokinetics: Calculus and Graphs01:21

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The fundamental mathematical principles, such as calculus and graphs, play crucial roles in analyzing drug movement and determining pharmacokinetic parameters. Differential calculus examines rates of change and helps to determine the dissolution rate of drugs in biofluids, as well as how drug concentrations change over time. For instance, it can help calculate the rate of elimination of a drug from the body based on its concentration-time profile.
On the other hand, integral calculus focuses on...
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Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches01:14

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Drug disposition in the body is a complex process and can be studied using two major approaches: the model and the model-independent approaches.
The model approach uses mathematical models to describe changes in drug concentration over time. Pharmacokinetic models help characterize drug behavior in patients, predict drug concentration in the body fluids, calculate optimum dosage regimens, and evaluate the risk of toxicity. However, ensuring that the model fits the experimental data accurately...
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Pharmacokinetic Models: Comparison and Selection Criterion01:26

Pharmacokinetic Models: Comparison and Selection Criterion

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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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Model Approaches for Pharmacokinetic Data: Physiological Models01:15

Model Approaches for Pharmacokinetic Data: Physiological Models

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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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Analysis of Population Pharmacokinetic Data01:12

Analysis of Population Pharmacokinetic Data

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Analysis of population pharmacokinetic data involves studying the behavior of drugs within diverse populations to understand their pharmacokinetic parameters. Traditional pharmacokinetic methods typically involve collecting samples from a few individuals and estimating these parameters. While these methods are commonly used, they have limitations in capturing the variability in drug response among individuals or heterogeneous populations. Population pharmacokinetics is employed to address these...
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Use of Rabbit Eyes in Pharmacokinetic Studies of Intraocular Drugs
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Pharmacokinetic Tools and Applications.

Judith C Madden1, Courtney V Thompson2

  • 1School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Liverpool, UK. j.madden@ljmu.ac.uk.

Methods in Molecular Biology (Clifton, N.J.)
|February 21, 2022
PubMed
Summary
This summary is machine-generated.

Predictive software aids drug development by assessing pharmacokinetic profiles and ADME properties. These in silico tools, at three levels, help evaluate drug efficacy and toxicity early in the process.

Keywords:
ADME modelingADME webtoolsPBPK toolsQSARSAR

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Area of Science:

  • Pharmacology
  • Computational Chemistry
  • Drug Development

Background:

  • Drug efficacy and toxicity depend on reaching the target site at sufficient concentration.
  • Pharmacokinetic profiles significantly influence a drug's therapeutic activity and potential toxicity.
  • The pharmaceutical industry increasingly utilizes computational tools to predict drug properties.

Purpose of the Study:

  • To introduce in silico tools for predicting ADME-relevant properties in drug development.
  • To describe the application of these tools across three distinct predictive levels.
  • To highlight exemplar freely available resources for pharmacokinetic and ADME property prediction.

Main Methods:

  • Categorization of in silico tools into three predictive levels: physicochemical properties, individual ADME characteristics, and concentration-time profiles.
  • Utilizing exemplar freely available software for demonstrating predictive capabilities.
  • Focusing on practical applications and capabilities of the tools rather than an exhaustive review.

Main Results:

  • Level (i) tools predict fundamental physicochemical properties for screening virtual libraries.
  • Level (ii) tools predict individual absorption, distribution, metabolism, and excretion (ADME) characteristics.
  • Level (iii) tools offer sophisticated predictions of drug concentration-time profiles in specific body compartments.

Conclusions:

  • In silico tools are valuable for predicting ADME-relevant properties at various stages of drug development.
  • Freely available resources offer practical solutions for assessing drug behavior and potential effects.
  • Understanding and applying these predictive tools can optimize drug discovery and development processes.