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PopGen: A virtual human population generator.

Kevin McNally1, Richard Cotton2, Alex Hogg1

  • 1Health & Safety Laboratory, Buxton, Derbyshire, UK.

Toxicology
|July 24, 2013
PubMed
Summary
This summary is machine-generated.

This study introduces PopGen, a web-based tool for generating virtual human populations. PopGen aids quantitative in vitro-to-in vivo extrapolation (QIVIVE) by providing realistic physiological data for physiologically based pharmacokinetic (PBPK) models, reducing animal testing.

Keywords:
PBPKPopulation variabilityQIVIVEReverse dosimetryVirtual human population generator

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Area of Science:

  • Toxicology and Pharmacology
  • Computational Biology and Bioinformatics
  • Environmental Health

Background:

  • The field of chemical and drug risk assessment is transitioning from animal testing to in vitro methods.
  • High-throughput, mechanistic in vitro systems require robust frameworks for data integration and extrapolation to human populations.
  • Physiologically based pharmacokinetic (PBPK) models are crucial for translating in vitro findings to human exposure scenarios.

Purpose of the Study:

  • To introduce PopGen, an open-access, user-friendly web application for generating virtual human populations.
  • To demonstrate the utility of PopGen in quantitative in vitro-to-in vivo extrapolation (QIVIVE) by integrating with PBPK models.
  • To facilitate the prediction of human population variability in anatomical, physiological, and metabolic parameters.

Main Methods:

  • Development of PopGen, a web-based application for virtual population generation.
  • Utilizing PopGen to provide input data for PBPK models.
  • Reconstructing human exposure from biomonitoring data using PBPK models informed by PopGen outputs.

Main Results:

  • PopGen successfully generates realistic anatomical, physiological, and metabolic variation across diverse human populations.
  • The application provides essential input for PBPK models, enabling detailed QIVIVE.
  • Demonstrated the process of exposure reconstruction from biomonitoring data, analogous to in vitro system extrapolation.

Conclusions:

  • PopGen is a valuable tool for advancing QIVIVE and reducing reliance on animal testing in risk assessment.
  • The integration of PopGen with PBPK models supports the translation of in vitro data to human health risk.
  • This approach aids in understanding human variability and reconstructing exposure for improved risk assessment strategies.