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

Physiological Pharmacokinetic Models: Incorporating Hepatic Transporter-Mediated Clearance01:07

Physiological Pharmacokinetic Models: Incorporating Hepatic Transporter-Mediated Clearance

192
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,...
192
Physiological Pharmacokinetic Models: Assumption with Protein Binding01:13

Physiological Pharmacokinetic Models: Assumption with Protein Binding

162
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...
162
Pharmacokinetic Models: Comparison and Selection Criterion01:26

Pharmacokinetic Models: Comparison and Selection Criterion

258
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.
258
Model Approaches for Pharmacokinetic Data: Physiological Models01:15

Model Approaches for Pharmacokinetic Data: Physiological Models

206
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...
206
Physiological Pharmacokinetic Models: Blood Flow-Limited Versus Diffusion-Limited Models00:57

Physiological Pharmacokinetic Models: Blood Flow-Limited Versus Diffusion-Limited Models

260
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...
260
Pharmacokinetic Models: Overview01:20

Pharmacokinetic Models: Overview

1.7K
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...
1.7K

You might also read

Related Articles

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

Sort by
Same author

Relationship between toxicant transfer kinetic processes and fish oxygen consumption.

Aquatic toxicology (Amsterdam, Netherlands)·2001
Same author

Mites on birds. Comment from Harper & Randall.

Trends in ecology & evolution·2001
Same author

Dowel Fusion of the Scapho-Trapezio-Trapezoid Joint: A Description of a New Technique.

Hand surgery : an international journal devoted to hand and upper limb surgery and related research : journal of the Asia-Pacific Federation of Societies for Surgery of the Hand·2000
Same author

Calibration of the stray field gradient by a heteronuclear method and by field profiling

Journal of magnetic resonance (San Diego, Calif. : 1997)·2000
Same author

Rapid and sensitive closed-tube quantification of human interferon-gamma mRNA by reverse transcription-PCR utilizing energy-transfer labeled primers

Clinical chemistry·2000
Same author

Gerhard schwarz: scientist and colleague

Biophysical chemistry·2000

Related Experiment Videos

A physiological model to predict xenobiotic concentration in fish.

Yang1, Thurston, Neuman

  • 1Department of Zoology, University of British Columbia, 6270 University Boulevard, Vancouver, Canada

Aquatic Toxicology (Amsterdam, Netherlands)
|February 7, 2001
PubMed
Summary

A new model accurately estimates toxicant levels in fish bodies using exposure data and physiological factors. This tool enhances aquatic environmental risk assessment for non-metabolized toxicants.

Related Experiment Videos

Area of Science:

  • Environmental Toxicology
  • Aquatic Ecotoxicology
  • Physiological Modeling

Background:

  • Estimating toxicant body burden in fish is crucial for environmental risk assessment.
  • Existing models may lack accuracy for non-metabolized aquatic toxicants.
  • Physiological parameters like body weight and oxygen uptake influence toxicant accumulation.

Purpose of the Study:

  • To develop and validate a physiological model for estimating fish body toxicant load.
  • To assess the model's reliability and accuracy using a chemical exposure regime.
  • To improve predictions for aquatic environmental risk assessment.

Main Methods:

  • A physiological model was constructed incorporating exposure, fish weight, lipid content, and oxygen uptake.
  • The OXYREF oxygen database was utilized to predict fish toxicant body burden.
  • Quantitative analysis was performed to validate the model's performance.

Main Results:

  • The developed model demonstrated reliability and accuracy in estimating fish body burden.
  • The model effectively predicted toxicant loads for several non-metabolized aquatic toxicants.
  • The modified model provides more realistic predictions compared to previous approaches.

Conclusions:

  • The physiological model is a reliable and accurate tool for estimating fish toxicant body burden.
  • This model enhances the practice of aquatic environmental risk assessment.
  • The model's functional realism allows for more accurate toxicant load predictions.