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How to Move Past the Clinical Trial Data Deluge?

May 14, 2020 - 2 min read
How to Move Past the Clinical Trial Data Deluge?

Clinical trials research organizations are virtually awash in data today.  Growing volumes of patient reported outcomes, omics data and data derived from wearable/biosensors  of every stripe are collected from almost every patient who joins a trial. Over a single decade, the number of countries participating in trials rose 100%, the number of investigative sites joining trials rose 63%, and the number of procedures measured by trials jumped 70%.This data crunch is not limited to trials themselves. Post-trial follow-ups with trial participants are also up 25%.[1]  In all, the stream of data points fed into clinical trials is adding up to a flood.

Clinical trials managers are stuck asking, “Where is my data? Which system is it in?” Instead, the only question that should be asked is, “Is the data I have collected sufficient to answer the research questions I have set out to study?” The good news is that today, powerful enterprise data storage technology exists that can help manage the data deluge so that organizations can retrieve the right data from any source—in the right place, at the right time, for the right person.

What should you look for when you shop around for a good enterprise data storage system? You want something that can simplify the process of collecting and keeping all of this complex data secure, storing it so that it is easy to track and sort, and protecting its quality and consistency. It should allow your teams to unify workflows without unnecessary and burdensome data uploads and integrations, and orchestrate research and data analysis efforts all in one place, which will ultimately accelerate your clinical studies.

Ideally, your enterprise data storage system will come with tools and utilities that enable a common user interface, navigation, and access to all of your study data. It should manage multiple data types and formats, including data from any electronic data capture system, third-party labs, imaging, and from real world clinical settings. Processing should allow it to seamlessly integrate with existing data on patient IDs, visits and procedures, and to align and synchronize downstream and across the entire platform.

Want to analyze different trials together? You should be able to do this, too. Want to extract your datasets in standardized formats for interim analysis or regulatory submissions? Then be sure your platform can support various formats, such as SAS, PDF, XLS, and CSV. Simple, powerful and secure application programming interfaces, or APIs, and web services should also provide you with programmatic access to raw, transformed and analytics data to enable interoperability and distribution of data.

The Medidata Rave Clinical CloudTM is built to help manage this mountain of data so that organizations can retrieve the right data from any source—in the right place, at the right time, for the right person.

Want to see this in action? Watch an interactive demo of Medidata’s EDC, RTSM and eCOA/ePRO capabilities to learn how adopting one platform can help unify your data and workflows across study execution, allowing for rapid study startup, more streamlined execution with cleaner data, and the elimination of unnecessary reconciliation efforts.

For more information, check out this on-demand webinar about the power of an unified data platform formed by bringing two data collection environments together - medical imaging and EDC—to save time, resources, and cost.

Learn more about how to simplify data complexity here.

[1] Tufts Center for the Study of Drug Development, July/August 2018

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