1. The use of mode of action information in risk assessment:quantitative key events/dose-response framework for modeling the dose-response for key events
- Author
-
Penelope A. Fenner-Crisp, J. Craig Rowlands, S. Stoney Simons, R. Julian Preston, Charlene A. McQueen, Alan R. Boobis, Nancy G. Doerrer, Samuel M. Cohen, Risk Dose-Response Subteam, Tami S. McMullin, and Ted W. Simon
- Subjects
Counterfactual thinking ,Dose-Response Relationship, Drug ,Computer science ,Adverse outcomes ,Computational biology ,Models, Theoretical ,Toxicology ,Risk Assessment ,Cholinesterase inhibition ,United States ,Species Specificity ,Key (cryptography) ,Carcinogens ,Animals ,Humans ,Relevance (information retrieval) ,United States Environmental Protection Agency ,Mode of action ,Risk assessment ,Chemical risk - Abstract
The HESI RISK21 project formed the Dose-Response/Mode-of-Action Subteam to develop strategies for using all available data (in vitro, in vivo, and in silico) to advance the next-generation of chemical risk assessments. A goal of the Subteam is to enhance the existing Mode of Action/Human Relevance Framework and Key Events/Dose Response Framework (KEDRF) to make the best use of quantitative dose-response and timing information for Key Events (KEs). The resulting Quantitative Key Events/Dose-Response Framework (Q-KEDRF) provides a structured quantitative approach for systematic examination of the dose-response and timing of KEs resulting from a dose of a bioactive agent that causes a potential adverse outcome. Two concepts are described as aids to increasing the understanding of mode of action-Associative Events and Modulating Factors. These concepts are illustrated in two case studies; 1) cholinesterase inhibition by the pesticide chlorpyrifos, which illustrates the necessity of considering quantitative dose-response information when assessing the effect of a Modulating Factor, that is, enzyme polymorphisms in humans, and 2) estrogen-induced uterotrophic responses in rodents, which demonstrate how quantitative dose-response modeling for KE, the understanding of temporal relationships between KEs and a counterfactual examination of hypothesized KEs can determine whether they are Associative Events or true KEs.
- Published
- 2014