When electronic data capture (EDC) first appeared 30 to 40 years ago, it was a hugely disruptive technology for clinical data management, and over time, EDC became the primary tool for data collection and management. Unfortunately, the needs of each data contributor and consumer were merged, as one set of features defined not only the user experience but also the content (i.e., data experience). Principal investigators and site staff entering data would use the same defined page layout to enter data that CRAs used for monitoring and data managers used for data cleaning.<\/p>\n
If we explore the total experience of a clinical trial, it is easy to see the flaws in this plan. Different users need to view and interact with data differently, and those needs define their user requirements. Traditional EDC solutions do not offer customized, or role-based experiences, but rather compromise \u2014 prioritizing one user’s preferences over another.<\/p>\n
Additionally, over time, trials have included an explosion of data, more flexible trial designs, along with adaptive and master protocols. Operationally, digital (and decentralized) trials were developed to better meet site and patient demands.<\/p>\n
With this evolution toward more complex scientific and operational requirements, the need to shift from a pure EDC focus is clear. The driving focus is complete and concurrent data \u2014 all your data, all in one place, all the time. However, the data must be available for specific roles in a way that makes sense to them. The data must be usable, contextually correct, and suitable for key decision-making.<\/p>\n
Up to now, companies have been using manual methods to aggregate and clean external data. However, as the number of data sources and volume of data continues to grow, data scientists have realized that these processes cannot scale to handle this quantity of data. It is now not unusual to see studies with 15 or more external data sources and types. The result has been a patchwork of solutions that require complex data integrations and still rely heavily on emails and spreadsheets to track data queries and cleanliness. <\/p>\n
Data scientists at Eli Lilly envisioned a better way to manage this data. Among their requirements: <\/p>\n
Veeva began working with Eli Lilly to co-design a clinical database to make this possible. A little later, GSK joined the effort as well.<\/p>\n
The result, Veeva DQS<\/a>, is now part of Veeva CDMS. It addresses these three critical areas identified by Eli Lilly and establishes a foundation for ongoing improvements to make data management easier and faster. It tackles challenges that have remained unaddressed for the last 20 years, including the need for: <\/p>\n The combination of Veeva EDC and Veeva DQS creates a new concept for clinical data management, providing the ability to capture, clean, and report on clinical data at all times \u2013 at any stage of the study. These two components make up Veeva CDMS and create a data foundation for adaptive, patient-centric clinical trials that can handle today\u2019s data requirements. <\/p>\n So far, the results we\u2019ve seen with Eli Lilly and GSK have been extremely promising. Eli Lilly has taken a systematic approach, using Veeva CDMS initially with small Phase II studies and now for complex global studies. GSK has already cut average study build times by half<\/a>, and Veeva CDMS has allowed them to standardize processes, eliminate complexity, and reduce the manual data cleaning effort. Veeva and our design partners are thrilled with the progress so far and the potential that we believe we can achieve going forward. <\/p>\n Veeva CDMS will change how data managers manage clinical trial data. First, Veeva EDC empowered data managers with the tools to build studies themselves without relying on custom code. It saved them time by eliminating migrations and downtimes that would extend trial timelines. Veeva DQS empowers data managers by giving them better tools to aggregate, clean, and provide data with less manual effort. <\/p>\n Veeva is committed to transforming the total experience of data management, and Veeva CDMS is proof that we are solving hard problems and driving change holistically. It\u2019s not just EDC; it\u2019s not just data cleaning; it\u2019s Clinical Data Management. It\u2019s the foundation for patient-centric digital trials, and it exists today. <\/p>\n Want to know more? Learn more about Veeva DQS<\/a>, Veeva CDMS<\/a>, or Veeva Digital Trials Platform<\/a>.<\/p>\n","protected":false},"excerpt":{"rendered":" EDC alone cannot solve the data challenges posed by hybrid digital trials. Veeva CDMS is taking on this role by also aggregating, cleaning, and providing user-based access to all trial data. <\/p>\n","protected":false},"author":80,"featured_media":28459,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":"","_members_access_role":[],"_members_access_error":""},"categories":[1],"tags":[],"product":[982],"area":[970],"coauthors":[1679],"class_list":["post-66353","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized","product-dqs","area-clinical-data","blog-html-content-yes"],"aioseo_notices":[],"aioseo_head":"\n\t\t\n\t\n\t\n\t\n\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n
Why holistic clinical data management matters<\/h2>\n