Workshop Proceedings Addresses Advances in Health Risk-based Decision Making
The proceedings of a March 2017 workshop on causal understanding for human health risk-based decision making is now available from the National Academies of Sciences, Engineering, and Medicine. The workshop explored advances in this area and examined different causal interference models and new frameworks for determining causality. As described in the proceedings, new molecular and bioinformatic approaches have improved understanding of the effects of chemical exposures on molecular pathways and which molecular networks are involved in disease. However, the ability of these emerging approaches to establish causality for public health risk assessment is unclear, which leaves regulators largely reliant on traditional endpoints—those observed in animal studies, for example—to assess risk. Environmental health researchers, toxicologists, statisticians, epidemiologists, regulators, and others gathered at the two-day workshop to discuss these new approaches and to identify gaps, challenges, and opportunities for integrating new data streams to determine causality in complex systems. The workshop covered the regulatory perspective on new data streams and ways to leverage epidemiology to help organize, evaluate, and categorize data on human carcinogens. The group also discussed the use of statistical modeling and computational tools to determine causality in situations with many variables. A PDF of the workshop proceedings can be downloaded from the National Academies website.