Science Inventory

Predictive Models and Computational Embryology

Citation:

KNUDSEN, T. B. Predictive Models and Computational Embryology . Presented at Michigan Society of Toxicology (MISOT),Southwest Michigan Innovation Center, Kalamazoo, MI, May 10, 2013.

Impact/Purpose:

Multicellular in silico computer models of the developing tissues are engineered with CompuCell3D. These small working prototype models can capture bioactivity profiles from HTS data, AOP framework information, and theoretical exposures to predict systems-level responses and dose effects. The capacity of these in silico models to engage the normal biology and simulate the behavior of a complex system steps us closer to in vitro profiling environmental chemicals for potential adverse effects on in vivo development and reproduction.

Description:

EPA’s ‘virtual embryo’ project is building an integrative systems biology framework for predictive models of developmental toxicity. One schema involves a knowledge-driven adverse outcome pathway (AOP) framework utilizing information from public databases, standardized ontologies, semi-automated literature mining tools, and curated MeSH annotations to map relationships of adverse developmental outcomes to potential key events involving genes, proteins, molecular pathways, and chemicals. A data-driven approach identifies significant statistical linkages between molecular pathway targets (e.g., retinoic acid receptor and TGF-beta signaling) for distinct developmental features such as disruption of blood vessel development, cleft palate, male urogenital defects and limb abnormalities. Specifically, the target-feature associations are mined from 3.2 million in vitro data points in the high-throughput screening (HTS) and in vivo toxicity profiling data from EPA’s ToxCast and ToxRefDB databases. Multicellular in silico computer models of the developing tissues are engineered with CompuCell3D. These small working prototype models can capture bioactivity profiles from HTS data, AOP framework information, and theoretical exposures to predict systems-level responses and dose effects. The capacity of these in silico models to engage the normal biology and simulate the behavior of a complex system steps us closer to in vitro profiling environmental chemicals for potential adverse effects on in vivo development and reproduction. This abstract does not necessarily reflect US EPA policy.

URLs/Downloads:

Predictive Models and Computational Embryology   (PDF,NA pp, 61 KB,  about PDF)

Record Details:

Record Type: DOCUMENT (PRESENTATION/ABSTRACT)
Product Published Date: 05/10/2013
Record Last Revised: 09/04/2013
OMB Category: Other
Record ID: 259646