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Workshop Introduction: Systems Biology and Biological Models
Citation:
EDWARDS, S. W. AND C. TIMCHALK. Workshop Introduction: Systems Biology and Biological Models. Presented at SOT48th Annual Meeting and ToxExpo, Baltimore, MD, March 15 - 19, 2009.
Impact/Purpose:
Presentaiton To discuss different modeling approaches for toxicity testing.
Description:
As we consider the future of toxicity testing, the importance of applying biological models to this problem is clear. Modeling efforts exist along a continuum with respect to the level of organization (e.g. cell, tissue, organism) linked to the resolution of the model. Generally, a tradeoff is made whereby higher levels of organization are models with lower resolution. In this workshop, we will consider modeling efforts across the full range of this spectrum. First, a model will be described for intracellular signaling including important information on how the choice of cell type for in vitro studies affects the signaling seen. Next, two systems approaches will be highlighted which model genome-wide molecular changes (i.e. Omics) within and between tissues and the application to pharmaceutical target discovery and toxicity testing. Finally, biologically-based dose-response models for risk assessment and data requirements associated with these models will be covered followed by a progress report on the development of detailed tissue models and integration of such models with molecular and cellular changes. If incorporated into future toxicity testing, these approaches should greatly facilitate the definition and quantitative modeling of mode of action for important environmental stressors. The systems approaches also have the potential to greatly improve interspecies extrapolation. In addition, the models described in this workshop will facilitate the use of in vitro data for risk assessment thereby increasing the number of chemicals that can be evaluated each year. In considering these different modeling approaches, we hope to gain a better understanding of the future opportunities and challenges we face as we strive for increasingly higher resolution models at greater levels of organization. [This abstract does not reflect EPA policy.]