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Activity Number:
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304
- Risk Applications for Disease, Toxicology, and Biomarker Modeling
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Type:
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Contributed
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Date/Time:
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Tuesday, July 30, 2019 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Risk Analysis
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Abstract #303071
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Presentation
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Title:
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Benchmark Analysis for Joint-Exposure Quantal Data in Quantitative Risk Assessment
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Author(s):
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Lucy Kerns*
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Companies:
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Youngstown State University
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Keywords:
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Benchmark dose approach;
Benchmark dose profile;
Quantal response data;
Risk assessment;
Abbott-adjusted log-logistic model;
Joint-action model
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Abstract:
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In risk assessment, it is often desired to make inferences on the minimum dose levels (benchmark doses or BMDs) at which a specific benchmark risk (BMR) is attained. The estimation and inferences of BMDs are well understood in the case of an adverse response to a single-exposure agent. However, the theory of finding BMDs and making inferences on the BMDs is much less developed for cases where the adverse effect of two hazardous agents is studied simultaneously. In this present work we apply an Abbott-adjusted log-logistic model with nonzero background response to model dose-response relationship, and we discuss the estimation of the benchmark profile (BMP) - a collection of benchmark points which induce the prespecified BMR - and propose different methods for building benchmark inferences in studies involving two hazardous agents.
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Authors who are presenting talks have a * after their name.
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