Research Triangle Institute

Data Standards to Support Integrated Source to Outcome Modeling - Project Summary/abstract as a Field, Environmental Health Science (EHS) Spans a Diverse Set of Disciplines and Subdomains That Evaluate Environmental Fate and Transport, Human Exposures, Dosimetry, Biochemical Interactions, Biological Effects, and Adverse Health Outcomes. Although Each of These Research Areas Provides Insight Into the Impacts of Chemicals That Are in the Environment, Integration Across These Areas Is Needed to Improve Interoperability Across the Source to Outcome Continuum (S2O). the S2O Tracks Chemicals From Their Release Into the Environment to Determine Human Exposure Levels and Then Uses Knowledge of Toxicity Mechanisms to Predict Potential Adverse Outcomes Resulting From These Exposures. This Project Will Build More-precise Semantic Descriptions of Physical and Biological Processes That Make Up the S2O to Facilitate Communication Among Humans and Computer Models Across Ehs Subdomains and Support for Public Health Decisions. to Accomplish This Goal, We Will Engage Data Generators, Computational Modelers, Public Health Decision Makers, and Developers of Data and Metadata Standards and Terminologies (S&T). Based on the Input From These Communities, We Will Expand S&T to Better Distinguish Biomarker Measurements From the Biological Events Those Biomarkers Represent and to Better Link Environmental Exposures to Upstream Chemical Sources and to Downstream Adverse Outcomes. These Efforts Will Be Guided by a Functional Workflow That Implements the S&T Improvements and Tests Their Impact on Human Health Outcome Predictions. the Resulting S&T Enhancements Will Provide Long-term Benefits to the Ehs Community by Enabling Analyses That Span the S2O, Thereby Improving Our Understanding of Environmental Impacts on Human Health. in Aim 1, We Will Engage the Ehs Community to Define the S&T Requirements for Data Exchange Between Neighboring Subdomains. This Aim Will Include the Identification of Opportunities and Needs for S&T Through a Series of Workgroup Meetings Held With Scientific Domain Experts, Stakeholders, and S&T Developers. Aim 2 Will Focus Directly on the Expansion of S&T to Better Describe Exposure and Biological Processes. the Biolink Model, Which Currently Underpins Projects Such as the Ncats Biomedical Data Translator, Will Be Used to Integrate S&T Across the S2O. S&T Expansion in This Aim Will Be Guided by Our Community Engagement Activities. Aim 3 Will Develop a Functional Workflow for S2O Analyses That Will (1) Identify Gaps in Existing S&T to Guide Community Engagement and S&T Development, (2) Provide a Test System to Evaluate the Impacts of S&T Improvements, and (3) Demonstrate How More Precise Language Across Ehs Subdomains Can Enable Analyses That Better Inform Public Health Decisions.