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Quantal Risk Assessment Database: A Database for Exploring Patterns in Quantal Dose-Response Data in Risk Assessment

Matthew W Wheeler1, Walter W Piegorsch2, Albert John Bailer3

  • 1Risk Evaluation Branch, National Institute for Occupational Safety and Health, Cincinnati, OH, USA.

Risk Analysis : an Official Publication of the Society for Risk Analysis
|October 29, 2018
PubMed
Summary
This summary is machine-generated.

This study introduces a historical database of 733 quantal dose-response datasets for chemical risk assessment. Using this database in Bayesian analyses stabilizes risk estimates and improves potency predictions.

Keywords:
BMDS softwareBayesian prior elicitationR softwarecarcinogenicitydata miningknowledge basequantal dose-response datastatistical methodstoxicology

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Area of Science:

  • Toxicology
  • Risk Assessment
  • Biostatistics

Background:

  • Quantitative risk assessments for various agents depend on scientific studies.
  • Limited observations in studies lead to significant uncertainty in risk models.
  • A diverse set of experimental studies is crucial for developing and assessing new risk assessment methods.

Purpose of the Study:

  • To construct a historical database of quantal dose-response data for chemical risk assessment.
  • To utilize this database for developing priors in Bayesian analyses.
  • To demonstrate the application of the database in stabilizing risk assessment estimates.

Main Methods:

  • Assembled a database of 733 quantal dose-response datasets from existing toxicological sources.
  • Employed the database to develop prior distributions for Bayesian dose-response model parameters.
  • Applied Bayesian analyses to illustrate the impact of historical data on risk estimates.

Main Results:

  • Incorporating prior information from the curated historical database stabilized point estimates in quantitative risk assessments.
  • Dose-response functions became more stable and precisely estimated.
  • Potency estimates also benefited from increased stability and precision.

Conclusions:

  • The developed historical database is a valuable resource for quantitative risk assessment.
  • Utilizing curated historical data in Bayesian analyses enhances the reliability of risk and potency estimates.
  • The database offers potential for further exploration in various risk assessment applications.