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Krembil affiliated researchers are eager to use big data to answer big research questions.
Posted On: June 17, 2016
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There has been massive growth in the scale of data thanks to the advent of cloud computing—the practice of using the internet, rather than personal computers, to store, manage, and process data.
Big research questions at Krembil can be answered using “big data”— large datasets that include multiple data types, from patient outcomes and biomarkers to brain imaging data and even non-medical data that may be relevant to care decisions. Exploiting this torrent of data requires advanced computational methods to find relevant insights and connections.
One example of the big data challenge is in the lab of Krembil Senior Scientist Dr. Karen Davis, where large brain imaging datasets can be further analyzed to better understand how individuals respond to pain differently.
“While conventional brain imaging studies, which usually have less than 20 participants, may provide useful information about the overall effectiveness of a particular drug, these studies cannot tell us what the optimal treatment is for individual patients—for that we need to adopt a big data approach,” says Dr. Davis.
There are many challenges to overcome to leverage big data. These include balancing the need to make data easily accessible for research, while maintaining participant privacy and security. To exploit big data, institutes must also make an investment in software development and computing hardware—what Dr. David Jaffray, Executive VP of Technology and Innovation at UHN, calls the “big machine.”
However, with support from federal funding agencies and generous donors, UHN, as the largest research hospital in Canada—and the volume of patient data that it carries—can become a leader in big data research. Investing in big data will help researchers produce useful insights for understanding biology and clinical care across multiple diseases.
One example of the big data challenge is in the lab of Krembil Senior Scientist Dr. Karen Davis, where large brain imaging datasets can be further analyzed to better understand how individuals respond to pain differently.
“While conventional brain imaging studies, which usually have less than 20 participants, may provide useful information about the overall effectiveness of a particular drug, these studies cannot tell us what the optimal treatment is for individual patients—for that we need to adopt a big data approach,” says Dr. Davis.
There are many challenges to overcome to leverage big data. These include balancing the need to make data easily accessible for research, while maintaining participant privacy and security. To exploit big data, institutes must also make an investment in software development and computing hardware—what Dr. David Jaffray, Executive VP of Technology and Innovation at UHN, calls the “big machine.”
However, with support from federal funding agencies and generous donors, UHN, as the largest research hospital in Canada—and the volume of patient data that it carries—can become a leader in big data research. Investing in big data will help researchers produce useful insights for understanding biology and clinical care across multiple diseases.