- Introduction
- Motivation
- Science Challenges
- Experimental Approaches
- Knowledge Discovery
- Computer Simulation
- Pilot Study
Motivation
Relevancy
Developmental toxicity refers to adverse effects produced prior to conception or during pregnancy and childhood. EPA's guidelines for developmental toxicity risk assessment are recorded in a 1991 Federal Registry and were updated at a 1998 Scientific Advisory Panel (SAP) workshop.
- EPA's Guidelines for Developmental Toxicity Risk Assessment (Federal Register) (PDF, 83pp, 0.2mb, About PDF)
- EPA's 1998 Scientific Advisory Panel Final Report (PDF, 12pp, 0.3mb, About PDF)
The potential of an environmental chemical to cause adverse effects on a fetus is an important risk assessment consideration. There are limitations to the number of chemicals that can be tested using traditional animal studies and there are uncertainties associated with extrapolating animal testing results to humans. Due to limitations, there are motivations to develop computational tools to increase the number of chemicals that can be tested and quantitatively integrate numerous information sources in developmental risk assessment.
Rationale for computational systems biology
Developmental biology is fundamental to all biological systems. It addresses questions such as what processes determine anatomical structures (morphogenesis) and tissues (differentiation) and the mechanisms through which these processes are controlled by the genome. Teratogenesis refers to the complex processes by which chemicals perturb or subvert these processes to invoke altered developmental phenotypes or adverse pregnancy outcome. Understanding developmental toxicity thus dictates information superimposed across multiple biological scales. Evaluating the potential for developmental defects is an exceedingly complex problem.
Expert systems are needed that can apply this knowledge across scales and computationally dissect the relative contributions of genetic variation, stage vulnerability, dose-response patterns, chemical mechanisms, fetal (epigenetic) programming, and maternal-fetal interactions to developmental defects. A key challenge for computational systems biology is to build useful multi-scale models that can be used to investigate systematically any or all interactions between the complex variables. At ends, we can hope to predict ‘lever-points' for toxicity pathways and cellular networks in altered development.