Current safety testing does not exploit state of the science. The data and information explosion in developmental biology and toxicology over the last few years has made it necessary to organize the information in the field of toxicology in a different way. These data come from high-throughput (HTP) assay batteries, global gene expression studies, and other sources that rely on harnessing biotechnology to provide information on chemical interactions with biological systems at basic levels of biological organization, as well as HTP methods for assessing the effects of chemicals on the development of model organisms such as zebrafish. In particular, the increasing amounts of data that inform us about molecular pathogenesis leading to human developmental toxicity, now motivate the implementation of human developmental toxicity Ontology.
Such an Ontology will inform the elucidation of AOPs relevant to systems toxicology and predictive toxicology for prenatal and neonatal life (Villeneuve reviews, Wu et al); help in the identification of mechanistically-based biomarkers and serve as a platform for systems toxicology for prenatal development (Sturla et al, 2014). It will also help guide the design of chemicals without evident potential for developmental toxicity.
This project will develop a formal system (ontology) that organizes the knowledge of chemical structure and developmental biology to predict and explain which chemicals will induce human developmental toxicity.
The projects objectives are to:
- Incorporate information at a variety of levels of biological organization, including but not limited to molecular targets and molecular initiating events and their associated chemistries. For example, one can identify chemical features that support binding to specific receptors or enzymes, or electrophilic attack of macromolecules.
- Comprehensively cover initial molecular interactions and downstream consequences using available information on the chemistry and biology shown to invoke developmental toxicity.
- Link biochemical changes, cellular consequences, embryological events, and developmental processes with enough specificity to support the formulation of hypotheses about the pathways leading from initial chemical interaction to specific adverse outcomes.
- Link with existing ontologies including those describing developmental processes and defects, where possible, to ensure interoperability (e.g OECD AOP- wiki).
- Enable the toxicology community to develop computational approaches and be compliant with open standards for ontologies (e.g. OWL) and systems biology (e.g. SBML). However it will also be user-friendly such that it is accessible and useable by the computer non-specialist.
The proposed ontology aims to formalize a system that integrates ‘vertical’ classification of adverse developmental outcomes (e.g. apical endpoints in a prenatal developmental toxicity animal study) with ‘horizontal’ classifications (in which the developmental lineages, spatial dynamics and staging of critical transitions leading to adverse outcomes can be derived from the expanding knowledge base of developmental biology, particularly from small model organisms and animal models of human disease).
This will be a toxicology-driven effort in collaboration with developmental biologists, toxicologists and ontologists. The investigators should consider data that is available in the peer reviewed literature as well as freely accessible data sources such as ToxCast; public repositories of gene expression information; compilations of toxicology data organised by chemical structure (e.g. ACToR, DSSTox); and previously developed ontologies - particularly those for developmental biology. See ‘references’ below for an additional source of information.
Download here the full version of the RfP LRI-AIMT5.