Robot Scientist offers more "intelligent" approach to drug discovery
Eve offers a more "intelligent" approach, says Ross King, a computer science researcher at the University of Wales, Aberystwyth where Eve is to be installed. The robot conducts the QSAR testing in assays itself, analyses the results and stores the data for future use. Over the course of numerous experiments, Eve learns which chemical structures are likely to be effective in specific assays. So, instead of choosing compounds to test at random, it can pick ones that are more likely to be effective. "We have carried out some preliminary trials and the compounds picked by Eve show more promise than those selected randomly," Dzeroski says. New data mining techniques developed by a team of researchers led by Dzeroski lie at the heart of Eve's groundbreaking drug discovery capabilities. Working in the EU-funded IQ project, the team developed new methods to analyse complex data, including chemical structures, from databases such as that in which Eve stores the results of its experiments. Unlike most data mining approaches, in which an individual analysis is carried out on a single dataset, such as a spreadsheet, the techniques developed in the IQ project allow knowledge discovery processes, consisting of several analysis steps, to be carried out across multiple sets of complex data. The techniques rely on the use of so-called inductive databases that contain not only raw data but also information about patterns and models valid in the data. In the case of drug discovery, the structures of the chemical compounds tested and their effectiveness would be the raw data, while molecular structures that appear commonly in effective compounds would be patterns, and the equations that predict a compound's effectiveness would be models. From experimental data collected by Eve, patterns would emerge that can then be used to make informed guesses about which compounds should be effective and which probably will not be. The same data mining techniques are also being applied by the IQ project partners in other fields, including genomics, systems biology and environmental sciences. "Because much more than raw data is being analysed, the same process for identifying different patterns can be reused, regardless of whether you are trying to develop a drug to treat AIDS or tuberculosis," Dzeroski explains. Eve will initially be put to work at the University of Wales to search for compounds that could be effective in treating malaria and schistosomiasis, so-called Third World diseases that are the focus of only limited research by commercial drug companies. King says their mission is both to demonstrate that the data mining technology works and to find new leads that could result in new drugs being developed in the future. Dzeroski foresees more robots like Eve being put to use in research labs and drug companies over the coming years. And although it will take 10 to 15 years for new drugs, based on compounds picked out by Eve, to start being used in treatments, the work done now "could have a major impact on the pharmaceutical industry and on healthcare in general in the future," he says. The IQ project received funding under the FET - Open scheme of the EU's Sixth Framework Programme for research. For further information, please visit:
http://www.aber.ac.uk/compsci/Research/bio/robotsci/ Source: ICT Results