Metadata-Driven Trial Data Management-Application in Clinical Data Lakes

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Join this live webinar on Thursday, March 21, 2019 at 1pm EDT to learn how a metadata-driven approach will help data analysts and bioinformaticians focus on data analysis without worrying about data management-related activities. Clinical data lakes store, cleanse and unify data that can come from different source systems.

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A Metadata-Driven Approach for Trial Data Management & Analysis for Application in Scalable Clinical Data Lakes By Nikhil Gopinath | June 5, 2019 In clinical research and development, data is central to optimizing clinical trials, especially the way the studies are designed and executed.

Comprehensive and Meticulous. veristat delivers comprehensive data management services utilizing efficient yet meticulous processes coupled with state-of-the-art technologies. We design, build, and deploy clinical trial databases faster than the industry norm; and our highly experienced team of data management professionals manages your clinical trial data with zealous precision and accuracy.

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Find out how Saama’s metadata-driven approach to clinical data lakes can help companies in clinical development focus on improving patient outcomes with faster access to processed information and machine analysis, without worrying about data management-related activities.

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So some clinical data management systems with easy user interface, data integration, data sharing and cost saving are needed for the efficient and effective clinical trial data management. Here we introduce the ClinData Express, a metadata driven web-based clinical research data management system for secondary use of clinical data.

Data Management and Analysis for Successful Clinical Research Lily Wang, PhD. Provide an overview on data management and analysis aspects of clinical research Minimize errors in datasets Ensure statistical software packages. Record data in a file and call it "Raw_xxx.xls

Metadata-Driven Trial Data Management-Application in Clinical Data Lakes These tests are typically read by visual inspection, and accurate record keeping and data aggregation remains a substantial. of mobile-phone imaging of RDTs linked to a clinical database management.. Reduce the time it takes to get a complete answer.

During the data analysis process in a drug development environment, we are faced with the sometimes-overwhelming task of efficiently and effectively managing different kinds of data. The examples of those data are clinical trial patient data which are collected on Case Report Forms (CRF), definition data for