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The Next Generation of Risk Assessment Multi-Year Study-Highlights of Findings, Applications to Risk Assessment, and
Ila Cote1, Melvin E Andersen, Gerald T Ankley
1National Center for Environmental Assessment, U.S. Environmental Protection Agency (EPA), Washington, District of Columbia, USA.
The Next Generation (NexGen) of Risk Assessment initiative uses advanced biological data and methods to improve public health risk evaluation. This approach enhances chemical identification, mechanism understanding, and biomarker discovery for more efficient risk assessment.
Area of Science:
- Environmental Health Sciences
- Toxicology
- Risk Assessment
Background:
- The Next Generation (NexGen) of Risk Assessment is a collaborative effort to evaluate novel molecular, computational, and systems biology approaches.
- This initiative aims to develop more efficient methods for assessing public health risks from environmental exposures.
Purpose of the Study:
- To test if advanced biological data and methods can enhance the understanding of public health risks.
- To explore applications of new scientific approaches in regulatory and public health decision-making.
Main Methods:
- Application and evaluation of transcriptomics, genomics, and proteomics data.
- Utilized molecular epidemiology, bioinformatics, pathway analysis, in vitro/in vivo bioassays, and QSAR modeling.
- Examined biomarkers of exposure and effect, and risk characterization across various decision contexts.
Main Results:
- NexGen advanced the rapid identification of chemicals and exposures of concern.
- Improved characterization of mechanisms of action, causality, exposure-response relationships, and susceptibility.
- Elucidated new biomarkers for exposure and effects, fostering confidence in new data interpretation.
Conclusions:
- Thoughtful application of new knowledge can augment major and limited scope risk assessments.
- New approaches are valuable for prioritizing and screening chemicals with limited data.
- NexGen fostered discussion and improved confidence in applying novel data streams for risk assessment.
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