Society For Risk Analysis Annual Meeting 2017
Session Schedule & Abstracts
* Disclaimer: All presentations represent the views of the authors, and not the organizations that support their research. Please apply the standard disclaimer that any opinions, findings, and conclusions or recommendations in abstracts, posters, and presentations at the meeting are those of the authors and do not necessarily reflect the views of any other organization or agency. Meeting attendees and authors should be aware that this disclaimer is intended to apply to all abstracts contained in this document. Authors who wish to emphasize this disclaimer should do so in their presentation or poster. In an effort to make the abstracts as concise as possible and easy for meeting participants to read, the abstracts have been formatted such that they exclude references to papers, affiliations, and/or funding sources. Authors who wish to provide attendees with this information should do so in their presentation or poster.
|Chair(s): Ingrid Druwe, J. Allen Davis email@example.com
Sponsored by Dose-Response, Exposure Assessment, Decision Analysis and Risk, and Ecological Risk Assessment Specialty Groups
|The challenges facing the risk assessment community in the 21st century, especially the need to screen large databases of toxicological information in order to provide relevant and timely human health risk assessments to interested stakeholders, represent a unique opportunity to advance the field given the advent of multiple technologies and the evolution of systematic review methods. When conducting assessments on chemicals with large databases, it can be difficult to efficiently screen tens of thousands of references to identify the most relevant, high quality studies to use. And once those references are identified, effectively and transparently managing the data to support hazard identification and dose-response analyses can prove to be a formidable task. In response to this challenge, the U.S. EPAâ€™s National Center for Environmental Assessment (NCEA) is leading efforts to develop and apply advancements in data science, machine learning, automation of systematic review, data integration, and dose response modeling in order to efficiently produce human health risk assessments in a timely fashion that meet the needs of our stakeholders. The objective of this Roundtable is to bring together a diverse group of experts at the forefront of risk assessment science and provide a platform for discussing strategies for making systematic review feasible in human health assessments, including the concept of fit-for-purpose evaluations and use of specialized software (SWIFT, HAWC) to increase productivity and improve data-content management. These tools and methods will improve data sharing with stakeholders, other Federal and State agencies and promote the integration of new approach methods (NAM) into human health risk assessment.|
Disclaimer: The views expressed in this abstract are those of the authors and do not necessarily represent the views or policies of the U.S. Environmental Protection Agency
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