Beyond Science and Decisions: From Issue Identification to Dose-Response Assessment
Workshop I Date: March 16-18, 2010
Location: Texas Commission on Environmental Quality; Austin, Texas

 

Case Study Proposals Recommend for Further Development

Breakout groups discussed the proposed case studies, suggested enhancements and modifications, and recommended whether a full case study based on the proposal should be brought to the second workshop. Breakout groups also had the opportunity to propose additional case studies. The report of the breakout group discussions is at http://www.allianceforrisk.org/Workshop/Workshop1MeetingReport.doc. The following list groups the case study proposals by topic, but within topic, the numbering reflects the original numbering of the case study proposals. Although chemicals are named, the focus is on the principles of methodology illustrated by the case. Topics covered include the following; note that some case studies addressed multiple topics:

1.      Consideration of the impact of inter-individual variability in cancer susceptibility;

• Case Study #2 – Inter-individual variability in cancer susceptibility – 4-aminobiphenyl from the Silver Book

• Case Study #8 - Conceptual models for individual/population dose response - TCDD

2.      Evaluation of a data-rich chemical using approaches of increasing sophistication, and data intensity, from default through BBDR, potentially including sensitivity analyses to address relative uncertainty;

• Case Study #4 – Consideration of known pathophysiology and human variability – Ethanol (maybe – lower priority, no team assigned)

See also Case Study #5, below

3.      Consideration of background and endogenous processes;

• Case Study #3 - Consideration of Endogenous processes: 1,4-Dioxane from the Silver Book

4.      Methods for screening-level assessments;

• Case Study #6 – Sustainable futures screening

• Case Study #25 – Tiered screening for acute exposure- Pentene

5.      Determining the risk consequences of intermittent exceedances of short-term exposure screening levels;

• New Case Study – Determine risk consequences of short, intermittent exceedances of 1-hour short term screening levels.

6.      A variety of methods for calculating risk at exposures exceeding or in the range of the RfD/RfC;

• Case Study # 9 – Extending the dose-response curve using biomarkers of effect – TiO₂

• Case Study #11 – Estimate risk above the reference dose using the published uncertainty factor distributions of Swartout et al. (1998), applied to 10 RfDs and RfCs from EPA IRIS.

• Case Study #17 – Calculate the probability of adverse effects at any dose at or above a threshold of one molecule, assuming a threshold of one molecule and applying linear extrapolation to zero; applied to 10 RfDs and RfCs from EPA IRIS.

• Case Study # 18 – Calculate the risk above the RfD using categorical regression.

• Case Study #21 – Use of biomarkers in the benchmark dose method to define risk for exposures above the RfD

• New Case Study - A comparative toxicological reference values analysis by carrying out low dose linear extrapolations.

7.      Acute exposure limits of varying severity using the AEGL methodology;

• Case Study #13 - Apply AEGL Methodology to Develop Acute Exposure Limit for Ethyl Benzene

8.      Applying MOA information with PBPK and BBDR modeling to quantify cancer risk, including consideration of endogenous/background exposure and background processes, as well as uncertainty, variability, and alternative modeling approaches;

• Case Study #5 – Applying MOA information with PBPK and BBDR modeling to quantify cancer risk, including consideration of endogenous/background exposure and background processes, as well as uncertainty, variability, and alternative modeling approaches (Formaldehyde).

• Case Study #10 – Considering uncertainty in cancer dose-response assessment – develop a method or framework for conducting comparable uncertainty analyses on both default/statistical-modeling methods and BBDR-based methods. (recommended be combined with #5)

• Case Study #16 – Using a flexible dose-response model for describing the dose-response for a MOA that includes multiple pathways – Acrylamide

• Case Study #26 - Consideration of nonlinearities in genotoxic modes of action – acrylamide (recommended to combine with #16)

• New Case Study Proposal - DNA damage by intracellular generated formaldehyde has been proposed as a carcinogenic mode of action for several chemicals (e.g., methanol, MTBE).

9.      Decision tree/framework on criteria for using increasingly data-informed approaches;

• Case Study #1A – Sufficiency of data to evaluate human relevance – Thyroid follicular tumors (maybe – no team identified)

10.  Review of data fusion methodologies to integrate data from different organizational levels;

• Case Study #19 - Apply data fusion methodologies for toxicological dataset analysis to resolve data quality issues in predictive toxicology

11.  Incorporation of data on inter- and intra-species variability in kinetics for noncancer endpoints;

• Case Study #23 – Incorporation of interspecies kinetic variability in metabolism – ovarian atrophy and 1,3-butadiene

• New Case Study –Use of human data in cancer risk assessment – 1,3-butadiene and leukemia (recommend to combine with #23)

• Case Study #24 – Consideration of human kinetic variability – Trichloroethylene

12.  Dose-response for liver tumors in rats involving receptor-mediated modes of action

• Case Study #20 - Three nuclear receptors, AHR, CAR/PXR and PPARα, as examples for how their biology is linked to key events and dose response for liver tumors in rodents

• Case Study #8 - Conceptual models for individual/population dose response - TCDD

13.  Dose-response for liver tumors in rats involving receptor-mediated modes of action

• Case Study #20 - Three nuclear receptors, AHR, CAR/PXR and PPARα, as examples for how their biology is linked to key events and dose-response for liver tumors in rodents

• Case Study #8 - Conceptual models for individual/population dose response - TCDD

14.  Other

• Case Study #12 - IUEBK model prediction incorporating exposure distribution and background exposure (IUEBK/Lead).

For more information, please contact Oliver Kroner.