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Advances in Causal Understanding for Human Health Risk-Based Decision Makin...

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National Academy of Sciences

2101 Constitution Avenue Northwest

Washington, DC 20418

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Advances in molecular and bioinformatic approaches have enhanced our ability to understand how molecular pathways are affected by exposure, leading to a better understanding of the networks involved in disease outcomes. However, when it comes to establishing causality and performing risk assessment at the population level, these advances in understanding the molecular networks are not yet deemed as sufficient evidence for decision making. The use of animal models are still required to establish causality for regulatory decisions, despite the simultaneous push to reduce our reliance on such methods. This situation has generated a lot of questions in the field, such as: How do we determine causality using other types of data when animal data are limited or absent? Does new 21st century environmental health pathway-based thinking require new thinking about how to determine which molecular events or intermediate events should be the basis of safety concerns? To what degree do molecular events of concern (e.g., oxidative stress) need to be tied to traditional apical endpoints that regulators typically use to make decisions? What is the role of dose in predictive thinking vs. empirical observation in animals? How do we think about multicausality, where there are multiple pathways or networks determining how a disease will manifest in humans and animals?

On March 6-7, 2017, the Standing Committee on Emerging Science for Environmental Health Decisions will convene a 2-day workshop to explore these questions. This workshop will bring together environmental health experts, toxicologists, statisticians, sociologists, epidemiologists, regulators, and experts from other fields. At this workshop, participants will discuss the current thinking surrounding causal models, bring in experts from other fields that utilize different data streams for establishing causality in complex systems, and further explore methods for evaluating multi-causality and incorporating molecular data. Workshop participants will also discuss how these novel approaches and tools are relevant for environmental health and how they can be incorporated into the decision making process.

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National Academy of Sciences

2101 Constitution Avenue Northwest

Washington, DC 20418

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