Developing Computational Models to Understand and Predict Adverse Human Health Effects Associated with Exposure to Environmental Chemicals

National Institute Of Environmental Health Sciences

Investigators

Abstract

The mission of NIEHS is to discover how the environment affects people in order to promote healthier lives. The Division of Translational Toxicology (DTT) contributes to that mission by leading the transformation of toxicology through the development and application of innovative, human-relevant tools and strategies to characterize hazards presented by exposure to environmental chemicals. Three overarching objectives recently identified by DTT as part of its strategic realignment are to: i) accelerate progress toward becoming a more predictive, precise, and preventive science through the deliberate application of a Translational Toxicology Pipeline (TTP); ii) provide an evidence-based approach to identifying and understanding potential environmental contributors to contemporary and common diseases; and iii) improve our ability to conduct and communicate substance-based hazard evaluations that are more translational, innovative, and responsive. DTT has identified the ability to develop and utilize multi-scale computational models of biological systems as a critical need. Multiscale modeling uses mathematics and computation to quantitatively represent and simulate a system at more than one scale while functionally linking the mathematical models across these scales, which include atomic, molecular, cellular, organ, system (e.g., cardiovascular, reproductive, etc..), individual, and (sub)populations. The purpose of this project is to further the research and development of tools that DTT can use in its Translational Toxicology Pipeline (TTP) to better predict potential adverse human health effects caused by acute and chronic exposure to environmental chemicals and mixtures thereof. The research plan under this interagency agreement involves the assessment of the application of advanced computational approaches that integrate and model data across multiple scales of human and rodent biology to begin addressing three key challenges that must be overcome to enable the adoption of safety assessment paradigms that are truly predictive of human health outcomes: Accounting for sex as a biological variable; accurately translating toxicological findings across biological scales and between species; characterizing inter-individual biological variability and susceptibility