Table 1.

Objectives of the eTRANSAFE project.

Item	What	Why
Preclinical database	Collect and build the largest existing preclinical database/repository (including external data sources).	Necessary for data mining, modelling and translational assessment.
Clinical database(s)	Collect as much human study data as possible (clinical trials, PSURs, etc.).	Necessary for data mining, modelling and translational assessment.
Translation	Build a computational system to allow the systematic assessment of animal data for their validity and value in human safety.	Looking into details, species by species, organ by organ, toxicity by toxicity, target by target, where animals are relevant and where not, to anticipate potential human safety outcome. Potential to modify the future way of running preclinical safety assessment.
Data mining and analysis	Build query tools for joint data retrieval and mining in several databases/repositories.	Read-across analysis, finding precedents to user cases.
Graphic	Establish efficient data visualization, zooming in on essential.	Speed and ease of analysis. Efficient communication. Toxicology report input.
Toxicological models	Explanatory and predictive in silico models build on high quality data.	Improve relevance of models to match the druggable chemical space used in pharma. Emergence of Predictive Safety in pharma, which needs reliable models built using collective pharma history.
Policies	Formulate principles and rules for data sharing and model validation.	Facilitate current and future initiatives of data transparency and precompetitive data sharing.
Sustainability	To assure continuity and potentially commercial viability after end of project.	Pharmaceutical companies (and other parties) will want to continue using the system after end of the project.