There are several possible approaches to create an ontology of developmental toxicity. Perhaps the most straightforward approach would be to mine the literature for reports that link chemicals with MIEs, and then on through the biological responses that result from these initial interactions. For this approach, the only information needed is chemical structure, putative MIE, and adverse outcome.
Another approach would be to take advantage of multi-scale modelling approaches, especially AOPs that define the KEs from MIE to ultimate outcome, as a starting point for such an ontology. Unfortunately, there are still too few AOPs that have been documented to date, as they also must rely on mechanistic data from the literature and require considerable effort to construct and validate. It would be impractical to wait for a critical mass of relevant AOPs before embarking on a developmental toxicity ontology, particularly given that the latter can inform and expedite AOP development.
For most chemicals or small molecules, the chemical structure is known information. Given that a critical component of the chemical-target interaction that constitutes an MIE is the chemical, a practical starting approach for ontology construction is to group developmental toxicants by chemical structural features that contribute to their MOA (e.g. known or inferred interaction with specific receptors, reactive characteristics that lead to DNA damage, etc.). The decision tree for developmental and reproductive toxicity end points, recently published by Wu et al. (2013), provides a structure for starting on an ontology. It is supported by the first approach (mechanistic studies from the literature) to add strength to conclusions about MOA.
In summary, we are considering two possible approaches to building an AOP ontology: (1) start from the chemicals and potential MIEs and work forwards through our knowledge of developmental biology to an adverse outcome, or (2) start from the adverse outcomes and work backwards to AOPs through our knowledge of developmental biology.