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Computational Embryology - Translational Applications in Modeling Developmental Toxicity
Citation:
Knudsen, T. Computational Embryology - Translational Applications in Modeling Developmental Toxicity. Presented at Safety Pharmacology Society (SPS) Annual Meeting, Washington, DC, September 30 - October 03, 2018. https://doi.org/10.23645/epacomptox.7195733
Impact/Purpose:
Presentation at the Safety Pharmacology Society (SPS) Annual Meeting Oct 2018
Description:
Experimental models that reduce a complex biological system to simpler assays for high-throughput screening (HTS) of large chemical inventories have the benefit of facilitating quantitative evaluation of cellular and molecular responses to chemical perturbation, providing substantial information about the compounds or closely related analogs. However, a drawback of these reductionist approaches is the elimination of cellular interactions and spatial dynamics of an intact system. To optimize the chance of predicting human developmental toxicity potential in the absence of vertebrate animal testing, we need to rebuild this complexity. Computational biology is uniquely positioned to translate in vitro data from cellular and molecular assays into phenotypic predictions for adverse developmental outcomes. One computational approach to recapitulate the spatial and temporal diversity of anatomical development is the use of cellular agent-based models (ABMs) in CompuCell3d.org. This modeling environment can be used to virtually reconstruct a morphogenetic field, cell-by-cell and interaction-by-interaction. Executing the ABM self-organizes cells (‘agents’) into higher-levels of biological structure and function, leading to emergent phenotypes driven by cellular behaviors in and biochemical signals in the microphysiological environment. In this way, ABMs can predict phenotypic outcomes in response to simulated perturbations in a dynamical system. Probabilistic rendering of where, when and how a developmental defect might occur in a virtual embryo following lesions from the ToxCast/Tox21 dataset. This abstract does not reflect US EPA policy.
URLs/Downloads:
DOI: Computational Embryology - Translational Applications in Modeling Developmental Toxicity
SPS_2018_FINAL_M.PDF (PDF, NA pp, 4439.264 KB, about PDF)