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The primary focus of the UK e‐Science Programme is the development of software architectures, middleware and applications to support the end‐user scientific community in the undertaking of large‐scale research. A significant subset of e‐Science projects is concerned with the healthcare domain: as well as satisfying the needs of the end users, such projects have to consider the legal, ethical and security constraints associated with the use of sensitive patient data—these concerns are particularly relevant within the context of the U.K.'s National Health Service (NHS). In this paper we present a vision for Grid‐enabled healthcare that is sensitive to the information security requirements both of the NHS and the projects themselves. Although our motivation is principally derived from U.K.‐based e‐Health projects, this paper should be of interest to the worldwide health Grid community. By restricting ourselves to information security, we do not consider, for example, physical security or audit trail capabilities, which are outside the scope of this paper. The vision we describe is grounded in terms of experience, and reflects the challenges faced by the e‐DiaMoND project team. Copyright © 2005 John Wiley & Sons, Ltd.

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The utilisation of grid computing to support healthcare research is becoming increasingly widespread, as is the use of IT to support healthcare delivery. Furthermore, it seems that the two areas are on an inevitable convergence path as clinical communities in several countries start to investigate how real data stored in electronic patient records can be utilised to facilitate research. The use of IT within healthcare gives rise to unique social and ethical challenges; the area of grid computing has given rise to significant novel security challenges; and the anticipated convergence of these two fields will inevitably give a new lease of life to established challenges. In this paper we consider the phenomenon of tracker attacks in this emerging context, and outline a potential approach to addressing the problem.

A vast array of mathematical models have been proposed for all stages of cancer formation across a wide range of spatio -temporal scales. Attention is now turning to coupling these models across scales and building models of "virtual tumours" for use in in silico testing of novel drugs and treatment regimes. This leads naturally to the requirement for detailed knowledge of the underlying geometry and physiological properties of individual tumours for use in: (i) multi-scale mathematical models of in vivo tumour growth and development; (ii) fusion of multi-scale, multimodal medical imaging techniques to improve the diagnosis and treatment of individual patients; and (iii) training of cancer specialists and surgeons.