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Related Concept Videos

Analysis of Population Pharmacokinetic Data01:12

Analysis of Population Pharmacokinetic Data

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...
What is Population Genetics?01:25

What is Population Genetics?

A population is composed of members of the same species that simultaneously live and interact in the same area. When individuals in a population breed, they pass down their genes to their offspring. Many of these genes are polymorphic, meaning that they occur in multiple variants. Such variations of a gene are referred to as alleles. The collective set of all the alleles within a population is known as the gene pool.
What are Populations and Communities?00:30

What are Populations and Communities?

Overview
Hardy-Weinberg Principle01:49

Hardy-Weinberg Principle

Diploid organisms have two alleles of each gene, one from each parent, in their somatic cells. Therefore, each individual contributes two alleles to the gene pool of the population. The gene pool of a population is the sum of every allele of all genes within that population and has some degree of variation. Genetic variation is typically expressed as a relative frequency, which is the percentage of the total population that has a given allele, genotype or phenotype.
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

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 squares (OLS)...
Population Growth00:57

Population Growth

Population size is dynamic, increasing with birth rates and immigration, and decreasing with death rates and emigration. In ideal conditions with unlimited resources, populations can increase exponentially, which plots as a J-shaped growth rate curve of population size against time. This type of curve is characteristic of newly-introduced invasive species, or populations that have suffered catastrophic declines and are rebounding.

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Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
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What do we learn from repeated population analyses?

Stephen B Duffull1, Daniel F B Wright

  • 1School of Pharmacy, University of Otago, PO Box 56, Dunedin, New Zealand.

British Journal of Clinical Pharmacology
|September 17, 2013
PubMed
Summary
This summary is machine-generated.

Repeated population analyses refine understanding of drug effects over time and individual variability. This review explores their added value for researchers and clinicians in drug development and dosing.

Keywords:
enoxaparinpopulation PK

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Area of Science:

  • Pharmacometrics and Drug Development
  • Clinical Pharmacology
  • Pharmacokinetic/Pharmacodynamic Modeling

Background:

  • Population analyses are crucial for understanding drug concentration-effect relationships and inter-individual variability.
  • Multiple population analyses for certain drugs exist, necessitating a review of their cumulative contributions.
  • Assessing the added value of repeated analyses is important for guiding future research and clinical application.

Purpose of the Study:

  • To explore the knowledge gained from repeated population analyses of drugs.
  • To provide a framework for evaluating the value-added contributions of successive population analyses.
  • To guide authors and readers in critically reviewing population pharmacokinetic/pharmacodynamic studies.

Main Methods:

  • Literature review of published population analyses for selected drugs.
  • Synthesis of findings from repeated population analyses.
  • Qualitative assessment of the incremental value provided by subsequent studies.

Main Results:

  • Repeated analyses refine estimates of population pharmacokinetic parameters and covariate effects.
  • Subsequent studies often identify novel covariates or explore specific subpopulations.
  • The cumulative evidence from repeated analyses enhances understanding of drug behavior and optimizes dosing strategies.

Conclusions:

  • Repeated population analyses offer significant value by progressively refining drug models and informing clinical practice.
  • A critical appraisal of the added value of each new analysis is essential for efficient drug development.
  • Understanding the evolution of knowledge from repeated analyses aids in evidence-based decision-making for drug dosing and regulatory submissions.