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  • Conversation: Impact of data management on clinical trials: new study

    • December 18, 2017 11:27 AM GMT
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      Impact of data management on clinical trials: new study

      Recent research found a correlation between the upfront time to build and release a clinical database and its impact on downstream data management processes in conducting and completing trials. Richard Young reviews the study findings and offers guidance to improve the process.
      Clinical trials continue to increase in complexity and scope. A typical phase 3 protocol, for example, now has many more endpoints, procedures, and data points collected compared to a decade ago.1 At the same time, data management processes have become more complicated, as contract research organisations (CROs) and sponsors manage a variety of clinical trial data. Real-world evidence, electronic clinical outcome assessments, mobile device-driven data, social media communities, and electronic health and medical records are some of the new data sources now captured during clinical trials.
      The volume and diversity of data presents integration, compatibility, and interoperability challenges that the pharma industry must address in order to optimise drug development.
      A new survey we conducted with the US Tufts Center for the Study of Drug Development (CSDD) examines the state of clinical data management in life sciences and its impact on drug development. One of the largest, most in-depth studies of clinical data management professionals, the 2017 eClinical Landscape Study found a correlation between the upfront time to build and release the clinical database and its impact on downstream data management processes in conducting and completing trials.
      “The study results indicate that companies face a growing number of challenges in building and managing clinical study databases,” said Ken Getz, research associate professor and director at the Tufts CSDD.
      Read more: http://bit.ly/DataManagementImpact

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