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Related Concept Videos

Toxicokinetics: Overview01:21

Toxicokinetics: Overview

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Studies that assess how a drug is absorbed, distributed, metabolized, and excreted (ADME) at toxic doses are termed toxicokinetics. Understanding toxicokinetics helps predict adverse drug reactions (ADRs) and manage toxicity in humans.Toxicokinetics differs from pharmacokinetics mainly in the dose levels studied, with toxicokinetics focusing on higher toxic doses. The kinetics at these levels can be non-linear due to altered physiological processes. Toxicodynamics examines the relationship...
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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.
There are three primary types of models: empirical, compartment, and physiological. Empirical models, with minimal...
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Physiological Pharmacokinetic Models: Assumption with Protein Binding01:13

Physiological Pharmacokinetic Models: Assumption with Protein Binding

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Physiological models with protein binding in pharmacokinetics offer a sophisticated approach to understanding drug disposition. These models consider drug-protein interactions, enabling them to effectively predict drug concentrations in different organs and tissues. This precision aids in accurate drug dosing, providing a significant advantage over conventional models. A key process within these models is equilibration, which ensures that drug concentrations achieve a steady state within the...
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Physiological Pharmacokinetic Models: Incorporating Hepatic Transporter-Mediated Clearance01:07

Physiological Pharmacokinetic Models: Incorporating Hepatic Transporter-Mediated Clearance

367
Drug transporters are critical in drug absorption, distribution, and excretion processes. They should be included in physiological-based pharmacokinetic (PBPK) models, which help predict human drug disposition. However, predicting this is challenging during drug development, especially when liver transport is involved. However, with a realistic representation of body transport processes, an accurate model may be possible.
A recent model describes pravastatin's hepatobiliary excretion,...
367
Pharmacokinetic Models: Comparison and Selection Criterion01:26

Pharmacokinetic Models: Comparison and Selection Criterion

434
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.
434
Pharmacokinetic–Pharmacodynamic Relationship: Model Components01:14

Pharmacokinetic–Pharmacodynamic Relationship: Model Components

86
Pharmacokinetic-pharmacodynamic (PK–PD) modeling is essential in drug development and clinical pharmacology. It provides a quantitative framework to predict drug behavior and response over time. This approach integrates pharmacokinetics (PK), which describes the drug's absorption, distribution, metabolism, and excretion, with pharmacodynamics (PD), which characterizes the drug’s biological effects and mechanisms of action.The disposition kinetics of a drug determine its plasma...
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In Silico Modeling Method for Computational Aquatic Toxicology of Endocrine Disruptors: A Software-Based Approach Using QSAR Toolbox
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A toxicokinetic model for fish including multiphase sorption features.

Wolfgang Larisch1, Trevor N Brown1, Kai-Uwe Goss1

  • 1Department of Analytical Environmental Chemistry, Helmholtz-Centre for Environmental Research (UFZ), Leipzig, Germany.

Environmental Toxicology and Chemistry
|November 4, 2016
PubMed
Summary

This study developed a physiologically based toxicokinetic model using only physiological and physicochemical parameters, avoiding fitted data. The model accurately predicts chemical uptake, clearance, and bioaccumulation for nonpolar compounds.

Keywords:
BioaccumulationEnvironmental chemistryNonpolar chemicalsPhysiologically based toxicokinetic modelingToxicokinetic

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Area of Science:

  • Physiologically Based Toxicokinetic (PBTK) Modeling
  • Environmental Toxicology
  • Pharmacokinetics

Background:

  • Existing PBTK models vary in complexity, often relying on lumped parameters fitted to experimental data.
  • Fitted parameters limit model applicability and hinder a fundamental understanding of chemical processes.
  • A need exists for PBTK models based solely on intrinsic physiological and physicochemical properties.

Purpose of the Study:

  • To develop a PBTK model independent of fitted parameters, utilizing only well-defined physiological and physicochemical inputs.
  • To enhance the understanding of chemical uptake, distribution, and elimination processes within organisms.
  • To lay the groundwork for future model extensions, including ionic compounds and active transport.

Main Methods:

  • Development of a novel PBTK model framework.
  • Integration of fundamental physiological and physicochemical parameters.
  • Model validation using experimental data for nonpolar chemicals.

Main Results:

  • The developed PBTK model successfully predicted chemical uptake, clearance, and bioaccumulation for nonpolar compounds.
  • The model demonstrates the feasibility of a parameter-free approach in PBTK modeling.
  • Achieved accurate predictions without relying on fitted lumped parameters.

Conclusions:

  • A PBTK model based entirely on physiological and physicochemical parameters can accurately predict chemical behavior.
  • This approach offers a more robust and broadly applicable alternative to models requiring fitted parameters.
  • The study advances PBTK modeling by enabling a deeper mechanistic understanding and future extensions.