Science Inventory

The VIRTUAL EMBRYO. A Computational Framework for Developmental Toxicity

Citation:

KNUDSEN, T. B. The VIRTUAL EMBRYO. A Computational Framework for Developmental Toxicity. Chapter 3.3, Troy Seidle and Horst Spielmann (ed.), AXLR8-2 Alternative Testing Strategies Progress Report 2011. Springer-Verlag, Berlin, Germany, , 253-258, (2011).

Impact/Purpose:

Virtual Embryo models can be used in several ways to extrapolate predictions from cell-level data to developing organ systems, although a good amount of biological detail is needed to build cell-agent-based models and asses model performance. This exploits the advantages of a screening-level approach such as in vitro profiling, in which HTS data and in vitro assays probe lower levels of biological organization that are faster and less expensive than traditional animal studies to analyze key events in a potential adverse outcome pathway. Whereas computational modeling can significantly aid generating in vivo hypotheses from the in vitro data and yield insight into systems-level behavior, the virtual models must be grounded in results from actual experimentation.

Description:

EPA’s ‘Virtual Embryo Project’ (v-Embryo™) is focused on the predictive toxicology of children’s health and developmental defects following prenatal exposure to environmental chemicals. The research is motivated by scientific principles in systems biology as a framework for the generation, assessment and evaluation of data, tools and approaches in computational toxicology. The long-term objectives are to: determine the specificity and sensitivity of biological pathways relevant to human developmental health and disease; predict and understand key events during embryogenesis leading to adverse fetal outcomes; and assess the impacts of prenatal exposure to chemicals at various stages of development and scales of biological organization.

Record Details:

Record Type:DOCUMENT( BOOK CHAPTER)
Product Published Date:12/31/2011
Record Last Revised:10/25/2012
OMB Category:Other
Record ID: 241087