The purpose of this report is to develop organisational principles and frameworks that could be used to build a developmental toxicity ontology that would help in the creation of AOPs and an IATA to predict developmental toxicity. Whereas the ultimate goal would be to produce an ontology that encompasses quantitative AOPs, in this report we propose that the starting point has to be a state-of-the-science MOA ontology. From the computer science perspective, the structure of an AOP ontology will be similar to an MOA ontology. However, moving from an approach using qualitative molecular initiating events (MIEs) and qualitative KEs towards a quantitative AOP approach requires consideration of the non-linearity of dynamic biological systems and critical periods in development (e.g. the same MIE at different time points in development might produce different outcomes). By starting with an MOA, containing as much biology and signalling mechanism as current knowledge allows, we will move closer to building a quantitative AOP.
In this report, we aim to explore how this may be done by demonstrating how relevant qualitative and quantitative information from structured data (formal data sets) and unstructured data (from literature) can be organised into a logical ontology framework. Relevant Information will include existing knowledge and interrelationships between developmental biology, developmental defects caused by known chemicals, molecular pathways, molecular targets, and models that describe interrelationships. While the benefits of understanding and linking complex biological information in a structured format to understand and predict developmental toxicological outcomes are clear, the challenge in developing an ontology is to make it user-friendly and understandable to health scientists.
The report also aims to show how case studies of well-understood developmental toxicants can be used to elucidate the elements to be incorporated into formalised developmental toxicology.
Currently, there is no single source of information providing a comprehensive ontology of developmental toxicity linked to the MIEs and AOPs responsible for these effects. A developmental toxicity ontology (DTO) would be invaluable for scientists as it would contribute knowledge and understanding for:
- Development of in vitro approaches (including high-throughput screening) and in silico models for developmental toxicity.
- Development of AOPs, to elucidate what is known, what are the data gaps, and what are the potential inter-relationships between different biological pathways.
- Generation of hypotheses around critical events underlying adverse developmental outcomes, including the complex relationships between environment, genetics and host factors (e.g. nutritional status).
- Development of biomarkers of developmental toxicity.
- Hazard and risk assessment of chemicals for developmental toxicity.
- Furthering of research on the biology of reproduction.
Use of rational design in product development (e.g. computerised structural design to create molecules).