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Mechanistic data in hazard assessment

Academic and industry scientists debate whether use of mechanistic data in regulatory hazard assessment of chemicals should be decisive or supportive only, discuss study selection process for systematic reviews

In an article published on August 29, 2018, by regulatory news provider Chemical Watch, editor Andrew Turley informs about the outcomes of a consultation held by the U.S. Environmental Protection Agency (EPA) on the application of systematic review in Toxic Substances Control Act (TSCA) risk evaluations, which closed on August 16, 2018.

One point of disagreement between the industry and academic scientists turned out to be “the role of mechanistic data in the regulatory hazard assessment of chemicals.” Mechanistic data are generated for example by in vitro experiments or in silico predictions, such as cell-based assays or quantitative structure-activity relationship (QSAR) models, respectively.

The industry association American Chemistry Council (ACC) urged EPA “to add discussion to the approach that emphasizes the importance of incorporating mechanistic data in problem formulation.” Turley explains that, while traditionally “regulatory hazard assessments were dominated by data from toxicity studies of animals as model organisms and large-scale epidemiological studies of humans,” in recent years “mechanistic data has become central . . . for several long-running assessments.” For example, mechanistic data are being used by ACC to “claim that formaldehyde does not cause leukemia.”

On the contrary, academic scientists demanded clarifying “that mechanistic data, if available, can only be used to increase, not decrease, confidence in a body of evidence.” This “means that if the other data indicates a certain hazard, it is inappropriate to use conflicting mechanistic data to reduce confidence in that findings,” Turley explains. For example, a 2017 report by the U.S. National Academies of Sciences (NAS), focused on systematic review of endocrine disrupting chemicals (FPF reported), concluded “that the foundation of the hazard classification in a systematic review is the animal and human data, with the mechanistic data playing a supporting role.”

Industry and academia also “differed greatly over the proposed process for evaluating the quality of studies,” Turley observes. While the ACC generally supported the use of a quantitative study scoring systems as being “highly transparent and consistent,” academic scientists maintained that “quantitative scores are, in general, arbitrary and not scientific.” They further emphasized that the extent of study reporting should not be conflated with the study quality and expressed concerns that the EPA’s proposed scoring system “excludes otherwise quality research based on single reporting or methodological limitations.”

On December 10-11, 2018, in Washington D.C., U.S., the U.S. National Academies of Sciences will hold a workshop titled “Strategies and tools for conducting systematic reviews of mechanistic data to support chemicals assessments.”

Read more

Andrew Turley (August 29, 2018). “EPA’s systematic review approach exposes mechanistic debate.Chemical Watch

The National Academies of Sciences (2017). “Application of systematic review methods in an overall strategy for evaluating low-dose toxicity from endocrine active chemicals.

Board on Environmental Studies and Toxicology (2018). “Strategies and tools for conducting systematic reviews of mechanistic data to support chemical assessments.The National Academies of Sciences

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