![\"\"](\"https:\/\/www.veeva.com\/wp-content\/uploads\/2021\/12\/Vertex-Data-Management.png\")
<\/p>\n\nThe data management team at Vertex has
\nan impressive track record for operational
\nexcellence. In their trials, sites typically
\nenter data within 48 hours of the patient
\nvisit, and Vertex locks their data\u2014all study
\ndata\u2014within 15 to 18 days. Improving the
\nefficiency of study builds is their next step
\ntowards end-to-end operational efficiency.
\nAnd they\u2019re succeeding. Their first early phase study in ³Ô¹Ï±¬ÁÏ Clinical Data was built in just
\neight weeks, 40% faster than their historic norm of 13 to 14 weeks. The second was
\ncompleted in only six weeks, cutting their original corporate target of 12 weeks in half. Today,
\nthe target for completing study builds with ³Ô¹Ï±¬ÁÏ EDC is six to eight weeks. The long range
\ngoal is for all study builds to be completed within four to six weeks.\n<\/p>\n
<\/p>\n
\nHistorically, Vertex\u2019s builds took an average of 13-14 weeks. These timelines were in line with industry norms,
\nespecially for the complex studies Vertex was running, but much higher than they wanted. As a result, there was
\na risk to a database going live after first patient screened and thus the sites would need to wait to enter data.\n<\/p>\n
\nA major contributor to the long timelines was the back-and-forth with their vendor that took place during the casebook
\ndesign and again for user acceptance testing (UAT). At Vertex, the process for UAT was the more painful of the two.
\nHistorically, the vendor completed a UAT and sent the casebook to Vertex. Data management waited for comments
\nfrom the study team before returning the aggregated feedback. A revised casebook was sent to Vertex for the next
\nround of UAT. This \u201cping-pong\u201d approach was time-consuming, with each round taking one to two weeks.\n<\/p>\n
\nStakeholders outside of data management would often make suggestions and request changes without understanding
\nthe downstream implications on the EDC. This required offline conversations between data management and other
\nstudy team members, slowing the process even more.\n<\/p>\n
\nWhen Vertex executives set a Development-level goal to speed studies from protocol finalization to data coming in,
\nthe data management team knew that speeding study builds would become a top priority.\n<\/p>\n
\nVertex partnered with ³Ô¹Ï±¬ÁÏ and set an initial target for build times of six-to-eight weeks, and a long-term goal of just
\nfour-to-six weeks for early phase studies. Condensing 13-14 weeks into eight, and eventually four was a daunting task,
\nand would take a combination of modernized EDC functionality and improved processes.\n<\/p>\n
\nPrior to the first study, ³Ô¹Ï±¬ÁÏ services built a casebook template based on Vertex\u2019s extensive standards library.
\nUsing the templated Case Report Forms (CRFs) greatly improved build efficiency; all but one of the forms for the first
\ntwo studies were drawn from the template study and modified as needed.\n<\/p>\n
![\"\"](\"https:\/\/www.veeva.com\/wp-content\/uploads\/2021\/12\/Vertex-Data-Management2.png\")
<\/p>\n
Diagram 1. \u201cPartial reuse\u201d or modifying the template study forms increased from <1% to >48% between the first and second study \nVertex does not provide ³Ô¹Ï±¬ÁÏ with specs for building studies. As part of an Agile Design methodology, the ³Ô¹Ï±¬ÁÏ \n“It is easier to provide constructive feedback when looking at actual \nAn official spec is created at the end of the process in the form of a system-generated spreadsheet called the Study \n“The protocol is your spec. Everything that needs to be analyzed is in the \nThere were a few aspects of Studio, the design environment within ³Ô¹Ï±¬ÁÏ Clinical Data, that helped reduce build times.\n<\/p>\n \nWhen it came time for UAT, the data management team implemented ³Ô¹Ï±¬ÁÏ\u2019s live, interactive \u201croundtable\u201d approach. \n\u201cLive UAT updates are a game-changer,\u201d noted Gulati. \u201cBy providing feedback, fixing problems, and testing updates \nMore complex changes to the casebook that cannot be completed within the live UAT conference are documented \nTo reduce the sheer number of items checked during UAT, Vertex adopted a risk-based approach which eliminates \n \nVertex embraced change and transformed the way their studies are built. Using ³Ô¹Ï±¬ÁÏ Clinical Data and Agile Design \n“On average, our build times with ³Ô¹Ï±¬ÁÏ are seven and a half weeks–and we\u2019ve had some Vertex’s data management team cuts EDC build times by 50% with ³Ô¹Ï±¬ÁÏ Clinical Data.<\/p>\n","protected":false},"featured_media":62792,"parent":0,"template":"","product-link-list":[],"class_list":["post-65231","customer-stories","type-customer-stories","status-publish","has-post-thumbnail","hentry"],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/www.veeva.com\/eu\/wp-json\/wp\/v2\/customer-stories\/65231"}],"collection":[{"href":"https:\/\/www.veeva.com\/eu\/wp-json\/wp\/v2\/customer-stories"}],"about":[{"href":"https:\/\/www.veeva.com\/eu\/wp-json\/wp\/v2\/types\/customer-stories"}],"version-history":[{"count":4,"href":"https:\/\/www.veeva.com\/eu\/wp-json\/wp\/v2\/customer-stories\/65231\/revisions"}],"predecessor-version":[{"id":81899,"href":"https:\/\/www.veeva.com\/eu\/wp-json\/wp\/v2\/customer-stories\/65231\/revisions\/81899"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.veeva.com\/eu\/wp-json\/wp\/v2\/media\/62792"}],"wp:attachment":[{"href":"https:\/\/www.veeva.com\/eu\/wp-json\/wp\/v2\/media?parent=65231"}],"wp:term":[{"taxonomy":"product-link-list","embeddable":true,"href":"https:\/\/www.veeva.com\/eu\/wp-json\/wp\/v2\/product-link-list?post=65231"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
\nof one molecule.<\/em><\/p>\nSpec-less Design<\/h3>\n
\nteam interprets the protocols and draws from their libraries to generate real screens in a sandbox environment of ³Ô¹Ï±¬ÁÏ
\nEDC. The teams then meet face-to-face for an interactive design review meeting with clinical, stats, data management,
\nand other key contributors.\n<\/p>\n
\nscreens than it is when reviewing a traditional spec. It is a very efficient
\nprocess and the quality of reviews has gone up.”
\n\u2013 Michelle Harrison, director of clinical data management<\/span>\n<\/p><\/blockquote>\n
\nDesign Specification. Everything that exists in a traditional spec is included plus more. The Study Design Specification
\nis used for sign-off and any subsequent changes are captured in the Study Differences Report\u2014another form of
\nsystem-generated documentation.\n<\/p>\n
\nprotocol. ³Ô¹Ï±¬ÁÏ works from the protocol, just like they would from a spec.
\nWe\u2019re just eliminating a big time consuming step in the middle.”
\n\u2013 Vikas Gulati, executive director of clinical data management and metrics<\/span>\n<\/p><\/blockquote>\nEfficient Build Tools in Studio<\/h3>\n
\n
\ninformed consent dates. Once those were built, ³Ô¹Ï±¬ÁÏ reused the field across multiple forms.<\/li>\n
\nchild-bearing potential if the subject is female. Those fields wouldn\u2019t be included for male subjects, which reduces the
\nnumber of edit checks needed.<\/li>\n
\nthat information is already tracked and known as the \u201cevent date,\u201d and isn\u2019t needed on the CRFs.<\/li>\n<\/ul>\n Relevant, Real-time, and Risk-based UAT<\/h3>\n
\nBy having all stakeholders in the same room, the team is able to discuss and provide conclusive feedback. Behind the
\nscenes, the software is updated in real-time. These real-time updates are enabled by a modern, flexible architecture.
\nIn ³Ô¹Ï±¬ÁÏ Clinical Data, case report forms are maintained and managed separately from the data they collect. This allows
\nchanges to the forms or their rules to be displayed immediately in the user interface. In one example, Vertex and
\n³Ô¹Ï±¬ÁÏ completed what would have been three separate rounds of UAT in only two days, cutting multiple weeks of
\nwaiting out of the process.\n<\/p>\n
\nimmediately, we can eliminate three to four weeks from our timeline. This is a big departure from our historic approach.\u201d\n<\/p>\n
\nin a shared request-log that both ³Ô¹Ï±¬ÁÏ Clinical Data services and the Vertex data management team can access. While
\nthe ³Ô¹Ï±¬ÁÏ services team is revising the database within the sandbox development environment, the data management
\nteam has full visibility into the sandbox and ³Ô¹Ï±¬ÁÏ\u2019s progress. The Vertex team approves each update, or notes
\nadditional requests within the shared tracking log, creating a close collaboration between the organizations.\n<\/p>\n
\ntesting for forms and fields that were previously tested and haven\u2019t changed. The Study Differences Report within
\n³Ô¹Ï±¬ÁÏ EDC enables the risk-based approach by documenting any and all changes between two studies. Vertex uses the
\nreport to identify everything in a study that differs from their templated standards and only test the new or changed
\nelements. This approach reduced the amount of time and effort needed for a recent UAT by 50%.\n<\/p>\n
\nPrior to working with ³Ô¹Ï±¬ÁÏ, their UAT cycles would last multiple weeks. The UAT for their most recent study
\nwas completed by two individuals in just two days.
\n<\/strong>\n<\/p>\nThe Bottom Line: Improved Build Times with ³Ô¹Ï±¬ÁÏ Clinical Data<\/h2>\n
\nprocesses, they have cut their average build times for early phase studies in half while maintaining their high standard
\nfor quality. Vertex plans to conduct nearly 20 studies this year using ³Ô¹Ï±¬ÁÏ Clinical Data and over the next two years will
\ncontinue shortening timelines until they reach their goal of a four to six week build.\n<\/p>\n![\"\"](\"https:\/\/www.veeva.com\/wp-content\/uploads\/2021\/12\/Vertex-Data-Management3.png\")
<\/p>\n
\nmajor amendments in those studies. Even with putting things on hold, all our studies have
\ngone live before First Subject First Visit and that speaks to ³Ô¹Ï±¬ÁÏ\u2019s speed and agility.”
\n\u2013 Michelle Harrison, director of clinical data management<\/span>\n<\/p><\/blockquote>\n","protected":false},"excerpt":{"rendered":"