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Related Concept Videos

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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Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis00:59

Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis

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Noncompartmental analyses offer an alternative method for describing drug pharmacokinetics without relying on a specific compartmental model. In this approach, the drug's pharmacokinetics are assumed to be linear, with the terminal phase log-linear. This assumption allows for simplified analysis and interpretation of the drug's behavior in the body.
One important characteristic of noncompartmental analyses is that drug exposure increases proportionally with increasing doses. This...
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Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

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Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
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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: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

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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...
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Modeling chlordecone toxicokinetics data in growing pigs using a nonlinear mixed-effects approach.

A Fourcot1, C Feidt1, A Bousquet-Mélou2

  • 1Université de Lorraine, INRAE, USC 340, UR AFPA, 2 Avenue de la Forêt de Haye, TSA 40602, 54518, Vandœuvre-lès-Nancy, France.

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Chlordecone (CLD) pesticide pollution persists in French West Indies banana fields. This study models CLD toxicokinetics in pigs, finding average daily gain significantly impacts its variability, informing management in contaminated areas.

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ChlordeconeModelingMonolixPigsToxicokinetics

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Area of Science:

  • Environmental Science
  • Toxicology
  • Veterinary Medicine

Background:

  • Chlordecone (CLD), a persistent organic pollutant (POP), pollutes French West Indies banana fields, entering the food chain.
  • CLD is readily absorbed by animals ingesting contaminated soil, posing risks to livestock.
  • Understanding CLD toxicokinetics is crucial for managing agricultural contamination.

Purpose of the Study:

  • To model the toxicokinetics (TKs) of chlordecone (CLD) in growing pigs.
  • To utilize non-compartmental and nonlinear mixed-effects modeling (NLME) approaches.
  • To identify factors influencing CLD's absorption, distribution, metabolism, and excretion in pigs.

Main Methods:

  • Intravenous administration of CLD (1 mg/kg) to Creole and Large White growing pigs.
  • Serum CLD concentration measurement via GCMS/MS over 84 days.
  • Modeling CLD kinetics using Monolix software with NLME, evaluating covariates like breed, weight, and daily gain.

Main Results:

  • A bicompartmental model accurately described CLD serum kinetics.
  • Average daily gain was identified as the primary covariate affecting inter-individual TKs variability.
  • Key parameters: body clearance of 76.7 mL/kg/d and steady-state volume of distribution of 6 L/kg.

Conclusions:

  • This study presents the first NLME application for CLD TKs in farm animals.
  • Average daily gain is a significant factor in CLD toxicokinetics variability in pigs.
  • Findings support improved rearing management strategies in CLD-contaminated agricultural zones.