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A virtual lab for decision support in viral diseases treatment
EC contribution
: € 3.334.840
: 36 months
Starting date
: 01/03/2006
Funding scheme
: Specific Targeted Research Project
: virtual laboratory, healthcare, grid computing, data management system, biomedical data, biomedical applications, integrative approach, HIV drug resistance, infectious diseases
Contract/Grant agreement number
: 027446
Project web-site


Developing a virtual laboratory for infectious diseases that facilitates medical knowledge discovery and decision support for e.g. HIV drug resistance, that is the main objective of the ViroLab project.

Large, high quality, clinical and patient databases have become available which can be used to relate genotype to drug-susceptibility phenotype. The relevant data has two main characteristics: it spans all temporal and spatial scales from the genome up to the clinical data; it is inherently distributed over various sources (virological-, clinical- and drugs-databases) that change dynamically over time. Using a Grid-based service oriented architecture, we 'vertically' integrate the biomedical information from viruses (proteins and mutations), patients (e.g. viral load) and literature (drug resistance experiments), resulting in a rule-based decision support system for drug ranking. The virtual laboratory supports tools for statistical analysis, visualization, modelling and simulation, to predict the temporal virological and immunological response of viruses with complex mutation patterns to drug therapy. The Virtual Laboratory provides the medical doctors with a decision support system to rank drugs targeted at patients. It provides the virologists with an advanced environment to study trends on an individual, population and epidemiological level. By virtualizing the hardware, compute infrastructure and databases, the virtual laboratory is a user friendly environment, with tailored workflow templates to harness and automate such diverse tasks as data archiving, data integration, data mining and analysis, and modelling and simulation. HIV drug resistance is one of the few areas in medicine where genetic information is widely used for a considerable number of years. Large numbers of complex genetic sequences are available, in addition to clinical data. ViroLab offers a unique opportunity as a blueprint for the potentially many diseases where genetic information becomes important in future years.

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