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International Clinical Trials

Learning to Fish in Data Lakes





Today, clinical operations teams are drowning in data but starving for information, at a time of intense pressure to speed up clinical trials and restrain costs (1). The massive volumes of data generated during clinical trials are woefully inadequate at helping stakeholders spot risk factors and bottlenecks that can disrupt cycle times and budgets, primarily due to the inefficient ways in which operational data are captured and analysed, often relying on outdated methods such as Excel. Excel was not designed to collect and analyse clinical trial data as it lacks project management capability, yet its extensive use persists (2-3).

Having technology that can automate or assist in the timely monitoring of trials is a huge improvement over the current status quo of manual methods such as spreadsheets, which are cumbersome and erroneous, not to mention they only provide a dated view of trial performance.

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About the author


Craig Morgan is responsible for directing the global marketing strategy and team for the Oracle Health Sciences suite of study startup applications, working with sponsors, CROs, medical device manufacturers, and sites to reduce cycle times and improve collaboration and oversight in clinical trials. He is a technology and life science management professional with over 15 years’ experience in the application of informatics and bioinformatics to drug discovery, and eClinical technology associated with starting clinical trials. Craig holds degrees in Analytical Chemistry, Information Systems, and Business Administration and is a certified Project Manager with the Project Management Institute.
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