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.
VIROLAB is to focus on a specific problem and target user group. We have decided to focus our efforts on the specific problem of HIV antiviral resistance (and thereby on a specific scientific community and patient group) for the purpose of creating a prototype for the broader application for infectious diseases. The reason for choosing HIV antiviral resistance is twofold: the problem needs continued and intensive attention from the scientific community and it is an area in which genetic information is widely available and used throughout Europe for a considerable number of years. With ViroLab, the increased need of medical doctors and scientists across Europe for standardised rules, definitions and systems for genotypic resistance interpretation, enable reliable quantitative and qualitative prediction of virological and immunological response for all retroviral drugs will be fulfilled. This is a major contribution towards solving the problem of HIV antiviral resistance.
Major problems to be addressed in the development of a Virtual laboratory are the highly distributed and heterogeneous nature of the data (virological, immunological, clinical and experimental), the high dimensionality and complexity of the (genetic and patient) data, as well as the inaccessibility and (lack of) interoperability of advanced modelling, simulation and analyses tools. Recent advances in Grid computing tackle these problems by virtualizing the resources (data, instruments, compute nodes, tools, users, etc.) and making them transparently available.
Genetic information is likely to become increasingly significant in many areas of medicine. This provides an unparalleled opportunity to advance the understanding of the
role of genetic factors in human health and disease, to allow more precise definition of the non-genetic factors involved, and to apply this insight rapidly to the prevention, diagnosis and treatment of disease. Large numbers of complex genetic sequences are increasingly becoming available, providing a unique opportunity for studying the many diseases where genetic information will become important in future years, such as in the case of infectious diseases. As a prototype the problem of HIV drug resistance is addressed. ViroLab integrates biomedical information from viruses (e.g., proteins and mutations), patients (e.g., viral load) and literature (e.g., drug resistance experiments),
resulting in a rule-based distributed decision support system for drug ranking, as well as
advanced tools for (bio)statistical analysis, visualization, modelling and simulation.
The main objectives of ViroLab are to:
The collaborative research will result in a virtual laboratory for decision support in infectious diseases treatment. We focus on HIV antiviral resistance (and thereby on a specific scientific community and patient group) for the purpose of creating a prototype for the broader application for infectious diseases. The project will benefit from the development of innovative pharmaceutical research, (antiviral drug development and use of information of clinical trials). ViroLab will lead to new valuable clinical data and information on treatment of HIVinfected persons, which will provide essential insights into the prevalence of drug resistance patterns in treated individuals on a continuous basis. It is of crucial importance for future development of new drugs effective against drug resistant HIV. ViroLab will demonstrate measurable, quantifiable benefits, respecting all aspects of confidentiality, fulfilling the urgent need for standardised rules and systems for reliable quantitative HIV-1 genotypic resistance interpretation, providing medical doctors throughout Europe with accessible and userfriendly tools for significantly improving the clinical usefulness of genotypic assay results. The virtual laboratory will function as Europe's first rulebased decision support system for drug ranking, including advanced tools for (bio)statistical analysis, modelling and simulation, enabling prediction the temporal virological and immunological response of viruses with complex mutation patterns to drug therapy, leading to better individual based treatment. ViroLab will be validated in epidemiological studies and will include elaborate and advanced Grid security infrastructures, respecting the aspects of confidentiality, security and trust.
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.
Figure 1: Virtual Laboratory system architecture. Distributed resources (computer elements, data and storage that the biomedical applications use are coordinated with the Grid middleware and a virtual runtime system. Resources are automated and visualised, and the resulting data is fed to anonymising components, as well as directly to the Decision Support System).
Figure 2: VIROLAB offers clinicians a distributed virtual laboratory that is securely accessible from their hospitals and institutes throughout Europe.