IBM Watson: Application of Cognitive Computing to Big Data Challenges

Source: Chen Y, Argentinis E, and Weber G. IBM Watson: How Cognitive Computing Can Be Applied to Big Data Challenges in Life Sciences. Clin Ther 2016. 38(4): 688-701.

Big data and personalized medicine are two phrases heard frequently by Medical Affairs professionals. In the biopharmaceutical industry, we are charged with not only compiling real-world evidence in the form of big data to demonstrate treatment effectiveness, but also applying big data to help bring precision medicine to the forefront. Cognitive computing—self-learning systems that use data mining, pattern recognition, and natural language processing to mimic the way the human brain works—is now being applied to drug development and analysis of big data. Among the best known is IBM Watson, a cognitive computing technology that has been configured to support life sciences research. Many of the major pharmaceutical companies are partnering with IBM Watson Health to apply cognitive computing to drug development, clinical trial design, and product innovation. An interesting publication by Chen and colleagues presents a rationale for cognitive computing in the life sciences, and reviews several pilot programs that successfully used IBM Watson in the areas of drug target identification and drug repurposing.

To access the full article, please visit: Chen_2016_IBM_Watson

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