{"id":81423,"date":"2024-05-24T15:30:55","date_gmt":"2024-05-24T13:30:55","guid":{"rendered":"https:\/\/www.veeva.com\/eu\/?post_type=resources&p=81423"},"modified":"2025-12-16T11:46:55","modified_gmt":"2025-12-16T10:46:55","slug":"clinical-data-workbenches-a-buyers-guide","status":"publish","type":"resources","link":"https:\/\/www.veeva.com\/eu\/resources\/clinical-data-workbenches-a-buyers-guide\/","title":{"rendered":"Clinical Data Workbenches: A Buyer\u2019s Guide"},"content":{"rendered":"

\nToday, clinical trials depend on increasing
\nvolumes of patient data from more diverse
\nsources than ever before.<\/strong>\n<\/p>\n

\nAn EDC system produces only about 30% of this data.
\nTo aggregate and clean the 70% of data that streams
\nin from third-party sources, most data management
\nteams use manual methods that involve the EDC,
\nstatistical computing environments, email, and
\nnumerous spreadsheets.\n<\/p>\n

\nThese manual methods increase effort, costs, and
\npotential risk. Taking data offline for cleaning delays
\nits availability for periods that range from a few days
\nto a few months, preventing more agile responses
\nif safety or quality issues arise.\n<\/p>\n

\nFaster, automated approaches are needed to speed
\nthe availability of clean, consistent clinical data.
\nAn emerging category<\/a> of solutions, clinical data
\nworkbenches (also referred to as clinical data platforms,
\nhubs, or data aggregation and management systems),
\naddresses these challenges.\n<\/p>\n

What are clinical data workbenches?<\/h2>\n

\nClinical data workbenches provide a single source of truth for all forms
\nof clinical data, making it faster and easier for cross-functional teams to
\nmanage the diverse patient data in today\u2019s clinical trials. Workbenches
\naddress challenges posed by the growing volumes of data from external
\nsources like labs, wearable devices, and ePRO solutions.\n<\/p>\n

\nThey centralize and harmonize the data, and use automation to reduce
\nreliance on manual processes for transformation and cleaning.
\nWorkbenches also enable better use of analytics, ensure data integrity
\nand quality, and improve collaboration among different stakeholder
\ngroups, thus facilitating increased trial agility and speed-to-market.\n<\/p>\n

\nProviding a single, central location for all trial data [Figure 1]<\/strong> improves
\naccessibility for adjacent and downstream processes such as safety
\nsurveillance or medical and clinical reviews. It also establishes a unified,
\nharmonized foundation for clinical data to ensure the successful
\napplication of AI and other emerging technologies.\n<\/p>\n

\nWhile the first workbench appeared on the market years ago, the
\nfirst-generation systems were never widely adopted. Today, there are
\nnew offerings from a diverse range of providers, including Edetek,
\nMedidata, Oracle, Saama, Signant Health, and ³Ô¹Ï±¬ÁÏ. Each employs
\na different model and approach. Across the category, workbenches
\nserve a wide range of functions, most of which deliver some but not all of
\nthe following: aggregation, review, query management, transformation,
\nstorage, visualization, and artificial intelligence.\n<\/p>\n

\"\"<\/p>\n

\nThe technological advances in this latest generation of clinical data
\nworkbenches deliver a better return on investment than their predecessors.
\nSponsors and CROs report seeing improvements from modern
\nworkbenches, including fewer manual processes, automated change
\ndetection, external patient data verification, and reduced cycle times for
\nquery management and database lock.\n<\/p>\n

\nThis guide offers a broad overview of data workbench technology,
\nsummarizing fundamentals for understanding basic system requirements,
\ndeveloping a business case for investment, and selecting the workbench
\nbest suited to your business needs.\n<\/p>\n

Determining what you need from
\na workbench<\/h2>\n

\nThe first step in evaluating clinical data workbenches is deciding
\nwhat your organization needs and how it could benefit most from
\nthis application. The checklist below summarizes the basic business
\nrequirements to consider.\n<\/p>\n

\nIf the data workbench will be a net new system, your data review and
\ncleaning processes should change to leverage its capabilities. Thus,
\nwhen defining requirements, \u201cask for a car, not a faster horse.\u201d Instead
\nof seeking to improve a legacy process, strive for greater advances by
\ninvestigating what\u2019s possible with these new systems. But verify vendor
\nclaims to ensure your \u201cfaster horse\u201d is not a \u201cflying car.\u201d\n<\/p>\n

CHECKLIST<\/h4>\n

System Requirements<\/h2>\n

\nThis checklist groups prospective capabilities into the following business requirements:
\nData Aggregation, Data Cleaning, Data Transformation, Data Analysis, and System Infrastructure.\n<\/p>\n

\n

Data Aggregation<\/h3>\n
\n