Inroads to predict in vivo toxicology-an introduction to the eTOX Project

Abstract

There is a widespread awareness that the wealth of preclinical toxicity data that the pharmaceutical industry has generated in recent decades is not exploited as efficiently as it could be. Enhanced data availability for compound comparison ("read-across"), or for data mining to build predictive tools, should lead to a more efficient drug development process and contribute to the reduction of animal use (3Rs principle). In order to achieve these goals, a consortium approach, grouping numbers of relevant partners, is required. The eTOX ("electronic toxicity") consortium represents such a project and is a public-private partnership within the framework of the European Innovative Medicines Initiative (IMI). The project aims at the development of in silico prediction systems for organ and in vivo toxicity. The backbone of the project will be a database consisting of preclinical toxicity data for drug compounds or candidates extracted from previously unpublished, legacy reports from thirteen European and European operation-based pharmaceutical companies. The database will be enhanced by incorporation of publically available, high quality toxicology data. Seven academic institutes and five small-to-medium size enterprises (SMEs) contribute with their expertise in data gathering, database curation, data mining, chemoinformatics and predictive systems development. The outcome of the project will be a predictive system contributing to early potential hazard identification and risk assessment during the drug development process. The concept and strategy of the eTOX project is described here, together with current achievements and future deliverables.

Keywords: Data Integration; Decision Support System; Expert Systems; Knowledge Management; Manual Curation; QSAR; computational models; data sharing; histopathology; in silico toxicity; in vitro toxicity; in vivo toxicity; ontology; predictive toxicology.

Figure 1

Overview of the eTOX project strategy. eTOX collects toxicological data from pharmaceutical (EFPIA) companies and public sources, and incorporates them into a database hosted by the “honest broker” to safeguard IP issues related to these data. The database will then serve as a source for the development of in silico models to predict the in vivo toxicity of new drugs.

Figure 2

The sensitivity classifications used in the eTOX project

Figure 3

Summary of the data transfer process.

Figure 4

Gathering and harmonization of data from EFPIA partners and public sources: Strategy to populate the eTOXdb with data suitable for model building.

Figure 5

Conceptual design and a potential workflow of the eTOX system (eTOXsys, prediction system established by eTOX).

Figure 6

Screenshots of the current version of the eTOX system (eTOXsys).