IBM Watson Delves Even Deeper Into Data
“On average, a scientist might read between one and five research papers on a good day,” said Dr. Olivier Lichtarge, the principal investigator and professor of molecular and human genetics, biochemistry and molecular biology at Baylor College of Medicine, in a statement. “To put this in perspective with p53, there are over 70,000 papers published on this protein. Even if I’m reading five papers a day, it could take me nearly 38 years to completely understand all of the research already available today on this protein. Watson has demonstrated the potential to accelerate the rate and the quality of breakthrough discoveries." Meanwhile, Johnson & Johnson is collaborating with the IBM Watson Discovery Advisor team to teach the computer to read and understand scientific papers that detail clinical trial outcomes used to develop and evaluate medications and other treatments. The collaboration hopes to accelerate the conduct of comparative effectiveness studies of drugs. These studies help doctors match a drug with the right set of patients to maximize effectiveness and minimize side effects. Typically comparative effectiveness studies are done manually, in which three people spend an average of 10 months–or 2.5 man-years--just to collect the data and prepare it for use before they are able to start analyzing, generating and validating hypothesis, IBM said. In this research study, the team hopes to teach Watson to quickly synthesize the information directly from the medical literature and allow researchers to start asking questions about the data immediately to determine the effectiveness of a treatment compared to other medications, as well as its side effects. In addition, IBM and the New York Genome Center are working together on a clinical study to advance genomic medicine using Watson. The collaboration will initially focus on clinical applications of the cognitive computing system to help oncologists deliver DNA-based treatment for glioblastoma, an aggressive form of brain cancer that kills more than 13,000 Americans each year, IBM said. The clinical study is designed to evaluate Watson’s ability to help doctors cut through the data to identify personalized treatment options for gliobalstoma patients, based on their specific genetic mutations.Watson is now able to provide supporting evidence for the answers it provides to queries. “The accuracy of that supporting evidence is as important, if not more important, as the accuracy of the answer,” High said. “How this applies to the cognitive computing world is we see this as not just about doing the work of humans, but enabling humans to work better,” High added. “It introduces what I think of as ‘inspiration’ into the equation. We can inspire people with new ideas that they by themselves might not have come to. We are helping people ask the questions they might not have thought of otherwise.” Discovering something new is applicable to many domains such as medicine, law or finance that require deep insight into a large body of information and protocols. Cognitive computing will allow human experts to interact with large bodies of data and research and the knowledge and insight of many other experts in their field. IBM Watson Discovery Advisor for life sciences is an integrated package of technologies delivered as a cloud service. The technology makes a map of information by reasoning over patterns it sees in available data, transforming raw data into new knowledge. IBM Power Systems will support Watson’s data learning by providing faster access to big data. Watson Discovery Advisor has the potential to transform industries and professions that rely heavily on data, including law, pharmaceuticals, biotech, education, chemicals, metals, scientific research, engineering, and criminal investigations, IBM said. Three years after its triumph on the television quiz show Jeopardy!, IBM has advanced Watson from a game-playing innovation into a commercial technology. Now delivered from the cloud, powering new consumer and enterprise apps, Watson is smarter, faster and smaller, with a 240 percent improvement in performance and a 75 percent reduction in physical size.
“We've been concentrating on the problem of how we enable people to answer the questions they’re asking. Now we’ve extended that capability into the discovery phase–to help people find out about the things they’re not asking but should be,” High told eWEEK.