Virtual lab will match drugs to patients
Uses the latest advances in machine learning, data mining, modelling and simulation
Researchers and doctors in Europe will soon have a virtual laboratory for infectious diseases that will help them match drugs to patients and make treatments more effective.
The ViroLab Virtual Laboratory, the core components of which will be available online this year, uses the latest advances in machine learning, data mining, grid computing, modelling and simulation to turn the content of millions of scientific journal articles, disparate databases and patients’ own medical histories into knowledge that can effectively be used to treat disease.
Developed by a team of European researchers working on the EU-funded ViroLab project, the virtual laboratory is already being used in seven hospitals to provide personalised treatment to HIV patients.
‘ViroLab finds new pathways for treatment by integrating different kinds of data, from genetic information and molecular interactions within the body, measured in nanoseconds, up to sociological interactions on the epidemiological level spanning years of disease progression,’ says Peter Sloot, a computational scientist at the University of Amsterdam and the coordinator of ViroLab.
ViroLab uses a combination of technologies and methods to help doctors make decisions about the best medication to give each patient, accessed through a simple-to-use web interface.
The system continuously crawls grid-connected databases of virological, immunological, clinical, genetic and experimental data, extracts information from scientific journal articles and draws on other sources of information. This data is then processed to give it machine-readable semantic meaning and analysed to produce models of the likely effects of different drugs on a given patient. Each medication is ranked according to its predicted effectiveness in light of the patient’s personal medical history.
Crucially, the system incorporates the concept of provenance, ensuring that every step a doctor takes in creating a workflow to find the right drug for a patient and every step the system takes to provide a recommendation is recorded.
Because of the distributed nature of the virtual laboratory, cases can be compared with those of other patients living a few streets or thousands of kilometres away. The system can also generate models simulating the likely spread of different mutations of viruses based on medical data and sociological information.
‘If a government has €500m to spend on HIV research and wants to know whether it should focus on funding the development of new drugs or on preventive measures such as encouraging people to change their sexual behaviour, we can give them an answer as to what would be more effective,’ says Sloot.
Sloot and other members of the ViroLab consortium are also exploring the use of the ViroLab Virtual Laboratory to create personalised drug rankings to aid in the treatment of other diseases in DynaNets, a follow-on EU-funded project that will look at drug dynamics in groups of people infected with the H1N1 flu virus and co-infections, in addition to drug-resistant HIV.
ViroLab was funded under the ICT strand of the EU’s Seventh Framework Programme for research.
Source: ICT Results
