Computational Toxicology Research
Virtual Tissues and Multi-Cellular Models
Morphogenesis is a tissue phenomenon. Successful modeling must prescribe differential cell states (proliferation, differentiation, death, motility, shape, adhesivity, matrix remodeling) as well as heterogeneities in cellular competence and metabolic demands that unfold by the hour. The need for functional models to analyze and visualize critical steps leading to abnormal morphogenesis speaks to a second key challenge for science and technology, that being a ‘computational toolbox' with the capability to integrate heterogeneous data into biological networks to model emergent properties of a developing system. In silico models must provide quantitative predictions of in vivo dose-response as well as how the flow of molecular regulatory information is distributed across toxicity pathways and intercellular signaling networks. As such, simple replication of single-cell data is likely to fail in tissue models.
Computational models of morphogenesis can be used to derive the logic of molecular and cellular networks and apply this logic to predicting effects that would be difficult or costly to derive by traditional means. Modeling complex behaviors from the myriad of interacting factors that may influence higher-level functions requires information about basic entities at a lower level of the system (‘agents'). A pattern-oriented strategy assumes codification of essential features of the system that can be computed in a reasonable way. Agent-based, hybrid cellular automata simulators such as CompuCell3D (CC3D) have been used build cell-based models of spatial patterning and growth during limb morphogenesis. Cell configuration at a lattice site of the automaton would be specified by complex parameters such as local gene regulatory networks, cellular and ECM properties, and cell-cell or cell-environment interactions.