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ViroLab – A virtual laboratory for decision support in viral diseases treatment
ViroLab is sponsored by the European Union (contract number )
D.A.M.C. van de Vijver (1), P. Sloot (2), A. Hoekstra (2), B. Ó Nualláin (2), A. Tirado-Ramos (2), S. Wesner (3), A. De Luca (4), L. Ruiz (5), C. Torti (6),
A.-M Vandamme (7), V. Müller (8), P. Plaszczak (9), M. Bubak (10), P. Coveney (11), W. Keulen (12), C.A.B. Boucher (1) on behalf of the ViroLab project
website:
Background
Recently the ViroLab project has received funding from the European Commission under the sixth framework programme. The main objective of ViroLab is to develop a virtual laboratory for infectious diseases. The virtual laboratory will provide an environment that automates virological and clinical workflows. At the core of ViroLab will be a decision support system for prediction of HIV drug susceptibility. In this abstract, an overview will be given of the methods that will be used and the anticipated results.
Figure 1 ViroLab functional architecture: the decision support system software interprets the genotype. In order to cover the latest available information, ViroLab will apply simulation, statistical analysis and datamining
Decision support system
To decision support
Methods
To meet its objectives, ViroLab will use a number of sophisticated Grid-based-, simulation-, statistical- and epidemiological techniques.
ViroLab will integrate information from viruses (e.g. sequences), patients (e.g. viral load) and literature (drug resistance experiments). Special attention will be given to the development of a user-friendly environment (Figure 1). In addition, ViroLab will include advanced tools for (bio) statistical analysis, visualization, modelling and simulation. The statistical analysis will be used to identify mutations that are relevant for resistance to particular drugs. The modelling and simulation tools will enable the prediction of the temporal virological and immunological response of antiretroviral drugs. The results of the statistical analysis and simulation will be provided to experts in HIV drug resistance, who will define rules for predicting antiretroviral drug susceptibility. Importantly, the virological and immunological efficacy of the rules will be studied in an epidemiological study and validated in independent datasets.
Figure 2 List of participants
Results
ViroLab will develop a virtual laboratory for European researchers and medical doctors. The laboratory will function as a user friendly rule-based decision support system for HIV drug resistance testing and treatment. ViroLab will reliably predict drug susceptibility and virological response and provide researchers with a support environment to study trends on HIV resistance on individual and population (epidemiological) level.
Conclusion
ViroLab provides a collaboration between experts in computer technology, simulation, statistics, epidemiology and HIV drug resistance. Importantly, HIV drug resistance is one of the few areas in medicine where genetic information has been used for a considerable number of years. ViroLab therefore offers a unique opportunity as a blueprint for the potentially many diseases where genetic information becomes important in future years.
1Dept. of virology, University Medical Centre Utrecht, the Netherlands, 2Dept. of computational science, University of Amsterdam, the Netherlands, 3University of Stuttgart, High Performance Computing Centre, Germany, 4Catholic University, Institute of Clinical Infectious Diseases, Rome, Italy, 5Institut de recerca de la SIDA, IRSICAIXA Foundation, Spain, 6Institute of Infectious and Tropical Diseases, University of Brescia, Italy, 7Rega Institute, Katholieke Universiteit Leuven, Leuven, Belgium, 8Eötvös Loránd University, Budapest, Hungary, 9Gridwise Technologies, Gridwise, Poland, 10University of Science and Technology, Institute of Computer Science and Academic Computer Center Cyfronet, AGH, Poland, 11University College London, Department of Chemistry, UCL, United Kingdom, 12 Virology education BV, Utrecht, the Netherlands