ToXchange Modern Modeling Strategies to Address Uncertainty and Variability in Dose-Response Assessment
SOT Virtual CE Course: AM06
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Chair(s): Kan Shao, Indiana University; and Weihsueh A. Chiu, Texas A&M University.
Primary Endorser:
Risk Assessment Specialty Section
Other Endorser(s):
Biological Modeling Specialty Section; Regulatory and Safety Evaluation Specialty Section
Quantifying dose-response relationships to evaluate the toxicity of environmental chemicals is a key step in human health risk assessment and has evolved substantially in recent years. In addition to fundamentally developing a dose-response curve and estimating a dose level that results in a predetermined critical effect, recent advances in toxicology and modeling strategies enable dose-response assessment to more comprehensively and quantitatively address uncertainty and human variability. The purpose of this course, to be delivered by a mixed group of experts from academia, government, and industry, is to provide participants an overview of the cutting-edge modeling strategies employed in dose-response assessment to quantify uncertainty and variability. The first presentation will introduce the benchmark dose (BMD) methodology and its utilities to quantify various sources of uncertainty in dose-response modeling with a demonstration of the Bayesian BMD modeling system. The second speaker will present an overview of the principles and recent applications of probabilistic dose-response assessment approaches developed under the WHO/IPCS guidance to address uncertainty and variability in quantitative risk assessment. The third presentation will provide an overview together with case examples of Diversity Outbred (DO) mouse population-based in vitro systems to demonstrate a data-driven probabilistic approach to derive a chemical-specific uncertainty factor for inter-individual variability. The last speaker will introduce how to predict population distributions of toxicokinetic-relevant physiological quantities that NHANES does not measure based on the measured counterparts using the HTTK-Pop R package that incorporates population variability in high-throughput toxicokinetic modeling. Throughout the course, use of and applications to in vitro and high-throughput testing systems will be highlighted, including their relevance to in vitro to in vivo extrapolation (IVIVE).
- Modern Modeling Strategies to Address Uncertainty and Variability in Dose-Response Assessment
Benchmark Dose Modeling Strategies for Uncertainty Quantifications in Dose-Response Assessment.—K. Shao. Indiana University, Bloomington, IN.
Probablistic Dose-Response Assessment to Quantatively Address Uncertainty and Variability.—W. A. Chiu. Texas A&M University, College Station, TX.
Modeling Dose-Response across Populations: Quantification of Inter-Individual Variability.—A. Harrill. NIEHS, Research Triangle Park, NC.
Simulation of Population Variability in High-Throughput Toxicokinetic Modeling in Support of Dose-Response Assessment.—C. Ring. ToxStrategies, Inc., Austin, TX.
Supplemental Files
The following files are provided as supplements to Dr. Caroline Ring’s presentation. They are intended to allow you as a user to familiarize yourself with the RStudio Open Source modeling software. The following instructions, sample file, and templates are provided.
- httkpop Example Instructions
- Sample File for RStudio
- httkpop Example Output
- APROBA PLUS Template
- APROBA Data v1.0
Certificates
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