The consortium is in its final year of work towards giving clinicians a comprehensive view of a child’s health by vertically integrating biomedical data, information and knowledge that spans the entire spectrum from imaging to genetic to clinical and epidemiological data. Utilising the power of the GRID the consortium has developed a biomedical information platform which supports sophisticated and robust search, optimisation and matching techniques for heterogeneous information.

The Health-e-Child platform is based on the EGEE gLite grid middleware. Work is concluding in the integration of innovative predictive disease models, complex data visualization and knowledge discovery applications, with the ultimate goal of supporting clinical decision making in cardiology, rheumatology and neuro-oncology. The system has been demonstrated in major international conferences and tested by its end-users through a 15 site growing grid network.

The Health-e-Child Gateway has undergone security assessment, has been released in production since Dec 2008, and is securely and anonymously hosting the health records of patients enrolled for the Health-e-Child project. Clinicians and researchers are working with the system to:

• Develop integrated disease models exploiting all available information levels

• Develop personalised healthcare for children using database-guided biomedical support

• Exploit large-scale, cross-modality and longitudinal information fusion and data mining for biomedical knowledge discovery

The Health-e-Child consortium is made up of 15 partners from 8 European member states. The major industrial partners are Siemens AG and maatG. The project brings together four major European paediatric hospitals, NECKER Enfants Malades in Paris, in France, Ospedale Pediatrico Bambino Gesù in Rome and Istituto Giannina Gaslini in Genova, in Italy, as well as the Great Ormond Street Hospital in London, in the UK, with several further European university groups and research centres to create a unique blend of inter-disciplinary expertise in information-based medical technology.