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Related Concept Videos

Pharmacokinetic Models: Overview01:20

Pharmacokinetic Models: Overview

733
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...
733
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

45
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...
45
Pharmacokinetic Models: Comparison and Selection Criterion01:26

Pharmacokinetic Models: Comparison and Selection Criterion

79
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.
79
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

74
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...
74
Analysis of Population Pharmacokinetic Data01:12

Analysis of Population Pharmacokinetic Data

267
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...
267
Multicompartment Models: Overview01:14

Multicompartment Models: Overview

151
Multicompartment models are mathematical constructs that depict how drugs are distributed and eliminated within the body. They segment the body into several compartments, symbolizing various physiological or anatomical areas connected through drug transfer processes such as absorption, metabolism, distribution, and elimination.
These models offer a more comprehensive representation of drug behavior in the body than one-compartment models. They accommodate the complexity of drug distribution,...
151

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Updated: Jul 13, 2025

Demonstration of the Sequence Alignment to Predict Across Species Susceptibility Tool for Rapid Assessment of Protein Conservation
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DEVELOPING INTEGRAL PROJECTION MODELS FOR ECOTOXICOLOGY.

N L Pollesch1,2, K M Flynn1, S M Kadlec1

  • 1USEPA Office of Research and Development, Great Lakes Toxicology and Ecology Division, 6201 Congdon Blvd, Duluth, MN, USA 55804.

Ecological Modelling
|October 18, 2023
PubMed
Summary
This summary is machine-generated.

Size-structured integral projection models (IPMs) link individual survival and reproduction to population dynamics. This approach aids ecological risk assessment for chemical exposures in data-limited aquatic environments.

Keywords:
IPMIntegral projection modelaquatic ecotoxicologyecological risk assessmentfathead minnow (Pimephales promelas)size-structured population modeltoxicity translation

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Area of Science:

  • Aquatic ecotoxicology
  • Ecological risk assessment
  • Population dynamics modeling

Background:

  • Individual size is crucial for survival and reproduction in ecosystems, particularly aquatic ones.
  • Size influences the effects of chemical exposure in aquatic ecotoxicology.
  • Ecological risk assessors need methods to estimate chemical exposure effects on wildlife populations with limited data.

Purpose of the Study:

  • To demonstrate how chemical and nonchemical effects on growth, survival, and reproduction can be linked to population-level dynamics.
  • To develop a modeling approach suitable for ecological risk assessors in data-limited environments.
  • To present the first application of integral projection models (IPMs) in ecotoxicology.

Main Methods:

  • Utilized size-structured integral projection models (IPMs) to link individual traits to population dynamics.
  • Developed modeling techniques for seasonal reproduction, density-dependent growth, and size-dependent overwinter survival.
  • Incorporated toxicokinetic-toxicodynamic models for acute survival and sub-lethal growth effects of chemical exposure into IPMs.
  • Parameterized daily time-step IPMs for the fathead minnow (Pimephales promelas) life history.

Main Results:

  • Successfully linked chemical and nonchemical effects on individual traits to population-level outcomes using IPMs.
  • Demonstrated the utility of size-structured IPMs for ecological risk assessment in data-limited scenarios.
  • Showcased the application of IPMs to seasonal reproduction, density-dependent growth, and size-dependent survival.

Conclusions:

  • Size-structured IPMs offer a flexible and promising framework for ecotoxicology.
  • This approach can synthesize ecotoxicological data and theory to assess impacts of chemical and nonchemical stressors on populations.
  • IPMs provide a valuable tool for understanding population-level consequences of environmental stressors.