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From: "Secretary, ACS Division of Chemical Health and Safety" <secretary**At_Symbol_Here**DCHAS.ORG>
Subject: [DCHAS-L] EPA Science: Examining the Links Between Chemical Exposures and Health
Date: Tue, 6 Jun 2017 15:22:56 -0400
Reply-To: ACS Division of Chemical Health and Safety <DCHAS-L**At_Symbol_Here**PRINCETON.EDU>
Message-ID: 46F1ECDC-F2CB-42FA-A3DB-D2E59385E6E5**At_Symbol_Here**dchas.org
Examining the Links Between Chemical Exposures and Health
EPA scientists are filling in missing pieces of the puzzle on chemical exposure. One approach is the development of Adverse Outcome Pathways (AOPs). AOPs are a way of assembling all the existing knowledge about small biological changes - to a cell, tissue, or organ=E2=80" resulting from exposure to a chemical, and their connection to more serious harmful health effects detected in people and ecosystems. These powerful organizational tools use available biological data and information to predict potential effects caused by exposure to chemicals that have limited available safety data.
Findings from newly developed AOPs are exciting. However, like all science, they must be tested to determine how they can best assist regulators in their efforts to protect people and the environment from unhealthy exposures to toxic chemicals.
In a new paper published in Environmental Science & Technology, EPA scientists developed a computer model of an AOP, called a quantitative AOP (qAOP). They tested whether the qAOP, working with the data they had about a specific estrogen disruption triggered in the fathead minnow after exposure to a chemical at a certain dose, over a specific period of time, could be used to predict a decrease in the minnow population over time.
The paper shows that the qAOP is, in-fact, able to provide regulatory decision-makers with data-based information about the amount of the chemical the fish would need to be exposed to over a specified period of time in order to eventually see the population decrease. This is an important step in providing regulators with the tools and data they need to justify regulations when traditional safety data is limited.
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