'Robotic Scientist' will run experiments too complex for humans -- to understand addiction
By Bill Steele
January 8, 2010
A "robotic scientist" that can automatically plan and execute experiments may soon provide new insights into the biology of addiction to drugs and alcohol.
Further down the road, the artificial intelligence (AI) that controls the experiments, dubbed "Eureqa," could be applied to a wide variety of problems in biology, including detecting disease organisms or traces of toxic chemicals, said Hod Lipson, associate professor of mechanical and aerospace engineering and computing and information science.
Lipson and graduate student Michael Schmidt have already demonstrated the system's ability to derive natural laws of motion from observations of a physical system. The new work focuses on biology, where there are often hundreds of interacting variables. "Many systems in biology are too complex to analyze manually," Schmidt said. "There may be new things we haven't found because they're ugly and complex, but to the computer they're obvious."
Unlike current drug tests that look for the drug itself or its breakdown products, the new approach will search for traces of previous use. Preliminary experiments suggest that drugs like alcohol and cocaine bring about changes in the metabolism of cells that might change the chemicals the cells secrete in response to certain stimuli. Detecting those secretions could make a test that's harder to fool, and information on past use could be valuable in choosing the best treatment for a drug abuser.
The quest for the new test is a collaboration among Cornell, Vanderbilt and Duke universities and the National Institute on Drug Abuse of the National Institutes of Health, which has provided $2.7 million in stimulus money from the American Reinvestment and Recovery Act (ARRA) to fund the project. It combines nanotechnology to isolate and manipulate a small number of immune-system cells called leukocytes, computer-controlled equipment to infuse the cells with various chemicals and analyze proteins and other materials they secrete in response, and Lipson and Schmidt's AI system to interpret the results of an experiment and direct the apparatus to conduct new experiments.
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