“In the world of clinical development, information is stored in a multitude of places, from clinical trial management systems and electronic data capture systems to third-party labs and Excel spreadsheets. Understanding if important milestones are being hit or missed requires a harmonized view of all that data in real time and in an actionable format—ideally, in the context of what users are most needing to know.
“This is the playground of Saama Technologies, whose Life Science Analytics Cloud (LSAC) makes pragmatic and targeted use of machine learning to create knowledge maps specific to job roles and query preferences, says Amit Gulwadi, senior vice president of clinical innovations.”
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