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Comprehensive analysis of correspondence and validity of animal data for human safety

Drug discovery and development is a knowledge-intensive process that can benefit from integrative analysis of different data types, produced by functions within the drug development chain. These integrative approaches can facilitate decision making across the drug discovery and development pipeline, improving lead optimisation and enhancing risk assessment. A pre-requisite for this is the availability of relevant, high quality datasets. However, to maximally leverage these data, important challenges such as encouraging information sharing among competing organisations, or promoting adequate data quality control, standardisation and annotation are required.

The Enhancing TRANslational SAFEty Assessment through Integrative Knowledge Management (eTRANSAFE) project develops an integrative data infrastructure and innovative computational methods and tools that aim to drastically improve the feasibility and reliability of translational safety assessment during the drug development process. This infrastructure will be underpinned by development of open standards and robust policies widely accepted by stakeholders, including regulatory agencies and international organisations.