The Virtual Physiological Human ToolKit.

The Virtual Physiological Human (VPH) is a major European e-Science initiative intended to support the development of patient-specific computer models and their application in personalized and predictive healthcare. The VPH Network of Excellence (VPH-NoE) project is tasked with facilitating interaction between the various VPH projects and addressing issues of common concern. A key deliverable is the 'VPH ToolKit'--a collection of tools, methodologies and services to support and enable VPH research, integrating and extending existing work across Europe towards greater interoperability and sustainability. Owing to the diverse nature of the field, a single monolithic 'toolkit' is incapable of addressing the needs of the VPH. Rather, the VPH ToolKit should be considered more as a 'toolbox' of relevant technologies, interacting around a common set of standards. The latter apply to the information used by tools, including any data and the VPH models themselves, and also to the naming and categorizing of entities and concepts involved. Furthermore, the technologies and methodologies available need to be widely disseminated, and relevant tools and services easily found by researchers. The VPH-NoE has thus created an online resource for the VPH community to meet this need. It consists of a database of tools, methods and services for VPH research, with a Web front-end. This has facilities for searching the database, for adding or updating entries, and for providing user feedback on entries. Anyone is welcome to contribute.

Data integration in eHealth: a domain/disease specific roadmap.

The paper documents a series of data integration workshops held in 2006 at the UK National e-Science Centre, summarizing a range of the problem/solution scenarios in multi-site and multi-scale data integration with six HealthGrid projects using schizophrenia as a domain-specific test case. It outlines emerging strategies, recommendations and objectives for collaboration on shared ontology-building and harmonization of data for multi-site trials in this domain.

The NeuroGrid stroke exemplar clinical trial protocol.

RATIONALE: Trials of new treatments for neurological disorders like stroke require imaging as part of the patient assessment, but need to be large enough to obtain reliable results if treatment effects are likely to be modest. However, multicentre trials use many different scanners in different hospitals and present complex problems for image data collection, interpretation and analysis and long-term secure archiving. AIMS: NeuroGrid aims to develop and test grid technologies for collecting, analysing and interpreting, and secure archiving of neuroimaging data for large multicentre trials in common neurological and psychiatric disorders. DESIGN: A 3-year multicentre consortium of clinicians, neuroimaging centres and e-scientists are designing a Grid storage network, mechanisms for uploading, curating and retrieving image and metadata, combining image data from different scanners and an analysis tool box. Three clinical exemplars--stroke, dementia and psychosis--provide the data and 'real-world' clinical trial applications, and a set of specific and typical problems encountered with image data in multicentre trials for NeuroGrid to address. The stroke exemplar is using image data from two multicentre stroke trials: Third International Stroke Trial and Efficacy of Nitric Oxide in Stroke. OUTCOMES: The final product is intended to appear as an integrated capability consisting of services, both database and analyses, accessed through simple portals. These will include image submission, automated scan quality control, appropriate metadata linkage, streamlined image review and coding tools and long-term secure storage for future multicentre stroke trials.

Designing for e-Health: recurring scenarios in developing grid-based medical imaging systems.

The paper draws on a number of Grid projects, particularly on the experience of NeuroGrid, a UK project in the Neurosciences tasked with developing a Grid-based collaborative research environment to support the sharing of digital images and patient data across multiple distributed sites. It outlines recurrent socio-technical issues, highlighting the challenges of scaling up technological networks in advance of the regulatory networks which normally regulate their use in practice.

Working IT out in e-Science: experiences of requirements capture in a HealthGrid project.

This paper reports on our experiences of being involved in requirements capture for a HealthGrid project. Large scale, collaborative projects with multiple partners tend to experience numerous problems in the requirements capture phase (and often beyond) and HealthGrid projects are no exception. Projects with highly innovative objectives often have additional sets of problematics, however. In carving out new visions of, for example, clinical research and healthcare service delivery, HealthGrid projects have to reckon with--and work within--existing healthcare policy, legislative frameworks, professional cultures and organisational politics as well as the more common integration problem of dealing with legacy systems. Such factors are not conducive to the achievement in healthcare of the e-Science vision of seamless integration of information and collaborative working across administrative, professional and organisational boundaries. In this paper, we document some of the challenges we encountered in investigating the requirements for eDiaMoND, a flagship pilot UK e-Science project. We discuss what we might learn from these challenges, especially approaches to requirements capture that are appropriate for projects with innovative aims and are also sensitive to representing and addressing what may be complex professional and organisational interests.