Scientific tools and capabilities to examine relationships between environmental exposure and health outcomes have advanced and will continue to evolve. Researchers are using various tools, technologies, frameworks, and approaches to enhance our understanding of how data from the latest molecular and bioinformatic approaches can support causal frameworks for regulatory decisions. For this reason, on March 6-7, 2017, the National Academies' Standing Committee on Emerging Science for Environmental Health Decisions, held a 2-day workshop to explore advances in causal understanding for human health risk-based decision-making. The workshop aimed to explore different causal inference models, how they were conceived and are applied, new frameworks and tools for determining causality, and ultimately discussed gaps, challenges, and opportunities for integrating new data streams for determining causality. This workshop brought together environmental health researchers, toxicologists, statisticians, social scientists, epidemiologists, business and consumer representatives, science policy experts, and professionals from other fields who utilize different data streams for establishing causality in complex systems to discuss the topics outlined above. This Proceedings of a Workshop-in Brief summarizes the discussions that took place at the workshop.
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