E-infrastructures fostering multi-centre collaborative research into the intensive care management of patients with brain injury

Clinical research is becoming ever more collaborative with multi-centre trials now a common practice. With this in mind, never has it been more important to have secure access to data and, in so doing, tackle the challenges of inter-organisational data access and usage. This is especially the case for research conducted within the brain injury domain due to the complicated multi-trauma nature of the disease with its associated complex collation of time-series data of varying resolution and quality. It is now widely accepted that advances in treatment within this group of patients will only be delivered if the technical infrastructures underpinning the collection and validation of multi-centre research data for clinical trials is improved. In recognition of this need, IT-based multi-centre e-Infrastructures such as the Brain Monitoring with Information Technology group (BrainIT - www.brainit.org) and Cooperative Study on Brain Injury Depolarisations (COSBID - www.cosbid.de) have been formed. A serious impediment to the effective implementation of these networks is access to the know-how and experience needed to install, deploy and manage security-oriented middleware systems that provide secure access to distributed hospital based datasets and especially the linkage of these data sets across sites. The recently funded EU framework VII ICT project Advanced Arterial Hypotension Adverse Event prediction through a Novel Bayesian Neural Network (AVERT-IT) is focused upon tackling these challenges. This chapter describes the problems inherent to data collection within the brain injury medical domain, the current IT-based solutions designed to address these problems and how they perform in practice. We outline how the authors have collaborated towards developing Grid solutions to address the major technical issues. Towards this end we describe a prototype solution which ultimately formed the basis for the AVERT-IT project. We describe the design of the underlying Grid infrastructure for AVERT-IT and how it will be used to produce novel approaches to data collection, data validation and clinical trial design is also presented

Data privacy by design: digital infrastructures for clinical collaborations

The clinical sciences have arguably the most stringent security demands on the adoption and roll-out of collaborative e-Infrastructure solutions such as those based upon Grid-based middleware. Experiences from the Medical Research Council (MRC) funded Virtual Organisations for Trials and Epidemiological Studies (VOTES) project and numerous other real world security driven projects at the UK e-Science National e-Science Centre (NeSC – www.nesc.ac.uk) have shown that whilst advanced Grid security and middleware solutions now offer capabilities to address many of the distributed data and security challenges in the clinical domain, the real clinical world as typified by organizations such as the National Health Service (NHS) in the UK are extremely wary of adoption of such technologies: firewalls; ethics; information governance, software validation, and the actual realities of existing infrastructures need to be considered from the outset. Based on these experiences we present a novel data linkage and anonymisation infrastructure that has been developed with close co-operation of the various stakeholders in the clinical domain (including the NHS) that addresses their concerns and satisfies the needs of the academic clinical research community. We demonstrate the implementation of this infrastructure through a representative clinical study on chronic diseases in Scotland

Innovative in silico approaches to address avian flu using grid technology

The recent years have seen the emergence of diseases which have spread very quickly all around the world either through human travels like SARS or animal migration like avian flu. Among the biggest challenges raised by infectious emerging diseases, one is related to the constant mutation of the viruses which turns them into continuously moving targets for drug and vaccine discovery. Another challenge is related to the early detection and surveillance of the diseases as new cases can appear just anywhere due to the globalization of exchanges and the circulation of people and animals around the earth, as recently demonstrated by the avian flu epidemics. For 3 years now, a collaboration of teams in Europe and Asia has been exploring some innovative in silico approaches to better tackle avian flu taking advantage of the very large computing resources available on international grid infrastructures. Grids were used to study the impact of mutations on the effectiveness of existing drugs against H5N1 and to find potentially new leads active on mutated strains. Grids allow also the integration of distributed data in a completely secured way. The paper presents how we are currently exploring how to integrate the existing data sources towards a global surveillance network for molecular epidemiology.Comment: 7 pages, submitted to Infectious Disorders - Drug Target

Semantic security: specification and enforcement of semantic policies for security-driven collaborations

Collaborative research can often have demands on finer-grained security that go beyond the authentication-only paradigm as typified by many e-Infrastructure/Grid based solutions. Supporting finer-grained access control is often essential for domains where the specification and subsequent enforcement of authorization policies is needed. The clinical domain is one area in particular where this is so. However it is the case that existing security authorization solutions are fragile, inflexible and difficult to establish and maintain. As a result they often do not meet the needs of real world collaborations where robustness and flexibility of policy specification and enforcement, and ease of maintenance are essential. In this paper we present results of the JISC funded Advanced Grid Authorisation through Semantic Technologies (AGAST) project (www.nesc.ac.uk/hub/projects/agast) and show how semantic-based approaches to security policy specification and enforcement can address many of the limitations with existing security solutions. These are demonstrated into the clinical trials domain through the MRC funded Virtual Organisations for Trials and Epidemiological Studies (VOTES) project (www.nesc.ac.uk/hub/projects/votes) and the epidemiological domain through the JISC funded SeeGEO project (www.nesc.ac.uk/hub/projects/seegeo)

Supporting UK-wide e-clinical trials and studies

As clinical trials and epidemiological studies become increasingly large, covering wider (national) geographical areas and involving ever broader populations, the need to provide an information management infrastructure that can support such endeavours is essential. A wealth of clinical data now exists at varying levels of care (primary care, secondary care, etc.). Simple, secure access to such data would greatly benefit the key processes involved in clinical trials and epidemiological studies: patient recruitment, data collection and study management. The Grid paradigm provides one model for seamless access to such data and support of these processes. The VOTES project (Virtual Organisations for Trials and Epidemiological Studies) is a collaboration between several UK institutions to implement a generic framework that effectively leverages the available health-care information across the UK to support more efficient gathering and processing of trial information. The structure of the information available in the health-care domain in the UK itself varies broadly in-line with the national boundaries of the constituent states (England, Scotland, Wales and Northern Ireland). Technologies must address these political boundaries and the impact these boundaries have in terms of for example, information governance, policies, and of course large-scale heterogeneous distribution of the data sets themselves. This paper outlines the methodology in implementing the framework between three specific data sources that serve as useful case studies: Scottish data from the Scottish Care Information (SCI) Store data repository, data on the General Practice Research Database (GPRD) diabetes trial at Imperial College London, and benign prostate hypoplasia (BPH) data from the University of Nottingham. The design, implementation and wider research issues are discussed along with the technological challenges encountered in the project in the application of Grid technologies

Grid infrastructures for secure access to and use of bioinformatics data: experiences from the BRIDGES project

The BRIDGES project was funded by the UK Department of Trade and Industry (DTI) to address the needs of cardiovascular research scientists investigating the genetic causes of hypertension as part of the Wellcome Trust funded (£4.34M) cardiovascular functional genomics (CFG) project. Security was at the heart of the BRIDGES project and an advanced data and compute grid infrastructure incorporating latest grid authorisation technologies was developed and delivered to the scientists. We outline these grid infrastructures and describe the perceived security requirements at the project start including data classifications and how these evolved throughout the lifetime of the project. The uptake and adoption of the project results are also presented along with the challenges that must be overcome to support the secure exchange of life science data sets. We also present how we will use the BRIDGES experiences in future projects at the National e-Science Centre

A generic vobe framework to manage home healthcare collaboration

In this paper we propose a conceptual framework to manage Home HealthCare (HHC) provision and stakeholder collaborations using the concepts of Virtual Breeding Environment (VBE) and Virtual Organisation (VO). Providing healthcare at home is gaining popularity as more and more patients prefer to receive care in the comfort of their homes. Providing care at home is complex and involves many stakeholders; collaboration and resource sharing between these stakeholders is essential for a successful home healthcare provision. In this paper we outline a framework to classify different parties involved in Home Healthcare (HHC) collaboration based on their roles. The framework consists of two main components which we call HHC-VBE and HHC-VO. The proposed framework is applied to a simple home healthcare case study and it is later evaluated. The result shows that the framework is simple and flexible and can be applied to other scenarios. This research contributes towards addressing the ongoing challenge of HHC collaboration management

Assured information sharing for ad-hoc collaboration

Collaborative information sharing tends to be highly dynamic and often ad hoc among organizations. The dynamic natures and sharing patterns in ad-hoc collaboration impose a need for a comprehensive and flexible approach to reflecting and coping with the unique access control requirements associated with the environment. This dissertation outlines a Role-based Access Management for Ad-hoc Resource Shar- ing framework (RAMARS) to enable secure and selective information sharing in the het- erogeneous ad-hoc collaborative environment. Our framework incorporates a role-based approach to addressing originator control, delegation and dissemination control. A special trust-aware feature is incorporated to deal with dynamic user and trust management, and a novel resource modeling scheme is proposed to support fine-grained selective sharing of composite data. As a policy-driven approach, we formally specify the necessary pol- icy components in our framework and develop access control policies using standardized eXtensible Access Control Markup Language (XACML). The feasibility of our approach is evaluated in two emerging collaborative information sharing infrastructures: peer-to- peer networking (P2P) and Grid computing. As a potential application domain, RAMARS framework is further extended and adopted in secure healthcare services, with a unified patient-centric access control scheme being proposed to enable selective and authorized sharing of Electronic Health Records (EHRs), accommodating various privacy protection requirements at different levels of granularity

Enhancing Privacy and Authorization Control Scalability in the Grid through Ontologies

© 2009 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.The use of data Grids for sharing relevant data has proven to be successful in many research disciplines. However, the use of these environments when personal data are involved (such as in health) is reduced due to its lack of trust. There are many approaches that provide encrypted storages and key shares to prevent the access from unauthorized users. However, these approaches are additional layers that should be managed along with the authorization policies. We present in this paper a privacy-enhancing technique that uses encryption and relates to the structure of the data and their organizations, providing a natural way to propagate authorization and also a framework that fits with many use cases. The paper describes the architecture and processes, and also shows results obtained in a medical imaging platform.Manuscript received November 19, 2007; revised July 27, 2008. First published August 4,2008; cur-rent version published January 4,2009. This work was supported in part by the Spanish Ministry of Education and Science to develop the project "ngGrid-New Generation Components for the Efficient Exploitation of eScience Infrastructures," under Grant TIN2006-12860 and in part by the Structural Funds of the European Regional Development Fund (ERDF).Blanquer Espert, I.; Hernández García, V.; Segrelles Quilis, JD.; Torres Serrano, E. (2009). Enhancing Privacy and Authorization Control Scalability in the Grid through Ontologies. IEEE Transactions on Information Technology in Biomedicine. 13(1):16-24. https://doi.org/10.1109/TITB.2008.2003369S162413