Mechanistic integration of exposure and effects: Advances to apply systems toxicology in support of regulatory decision making

Abstract Modernizing risk assessment methods that underly risk management decisions developed to protect public and environmental health will require interdisciplinary dialogue and communication. Alignment of exposures across traditional data streams such as data from in vivo laboratory animal and epidemiological or clinical studies, as well as integration of novel data types from emerging testing technologies and new methods of analysis, will improve causal inference. We propose a mechanistic scaffold that supports a source-to-outcome structure and an associated workflow pipeline which facilitates needed data curation and transparency regarding operational assumptions. The scaffold and workflow components enhance the utility and repurposing of data with the flexibility to support regulatory decision making in a fit-for-purpose fashion. Efficient use of data based on this scaffold across various modeling approaches will promote “one health” characterization to improve, promote, and protect the health of all species and the environment. Associated data standards to facilitate leveraging and sharing of data will increase communication and collaboration across different disciplines to enable that end.