The main objective of the ViroLab project is to develop a Virtual Laboratory for Infectious Diseases that facilitates medical knowledge discovery and decision support for, e.g., HIV drug resistance. Large, high quality in-vitro and clinical patient databases have become available which can be used to relate genotype to drug-susceptibility phenotype. Relevant data has two main characteristics: it spans all temporal and spatial scales from the genome up to the clinical data, and it is inherently distributed over various sources - virological, clinical and drugs databases - that change dynamically over time.
Such data comes also from a considerable proportion of patients for whom drugs fail to completely suppress the virus resulting in the rapid selection of drug-resistant HIV and loss of drug efficacy. To avoid the rapid selection of drug-resistance, HIV-1 replication should be completely suppressed, in order to delay the destruction of the immune system by inhibiting the depletion of CD4+ cells. Genotypic assays, based on nucleic acid sequencing of the viral reverse-transcriptase and protease genes are widely used to determine drug resistance and identify mutations associated with resistance to antiretroviral drugs.
The Virtual Laboratory endorses tools for statistical analysis, visualization, modelling and simulation, to prognosticate the temporal virological and immunological response of viruses with complex mutation patterns to drug therapy. Equipping medical doctors with a decision support system classing drugs targeted at patients, and providing virologists with an advanced environment to study trends on an individual, population and epidemiological level is the core function and objective of the Grid's architecture.
At the core of the ViroLab Virtual Laboratory is a rule-based ranking system, like Retrogram. Because Retrogram is currently a monolithic programme, the project participants separate and virtualize its components to use it in a Grid environment. Using a Grid-based service oriented architecture, the team vertically integrates 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.
By virtualizing the hardware, compute infrastructure and databases, the ViroLab virtual laboratory is a user-friendly environment, with tailored work flow 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.
GridwiseTech joined this venture together with the following bodies from The Netherlands, Poland and Germany: Universiteit van Amsterdam, Institute Universitair Medisch Centrum Utrecht, Institute of computer Science AGH, Academic Computer Centre Cyfronet, Virology Education B.V, and Universität Stuttgart. GridwiseTech is playing a strategic role in the project as it is solely responsible for designing and building the Grid infrastructure for Virolab.
GridwiseTech is proud to be part of such a beneficial project. Only by means of a Grid-based service, which it is developing for Virolab, is the integration of biomedical information, patients, and literature made possible on a vast scale. GridwiseTech has been invited to the consortium owing to its unique experience in building Grids. Virolab is a European Union-funded IST STREP Project. More information will become available soon at the Virolab Web site.