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The Virtual Embryo Project (v-Embryo™):
A computational framework for developmental toxicity
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 (FRL-4038-3, December 5, 1991) are recorded in the Federal Register 56(234):63798-63826 and updated in a 1998 workshop (SAP Report No. 99-01C, January 22, 1999). Whereas the potential of an environmental chemical to cause adverse effects on the fetus is an important consideration in any health risk assessment, the limitations on the number of chemicals that can be reasonably tested using traditional animal studies, and the desire to reduce uncertainties in the extrapolation process of high-dose to low-dose and animal-to-humans, motivates development of computational tools to increase throughput and quantitatively integrate various sources of information 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.