There Is More to CDMS Than EDC

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.

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 — prioritizing one user’s preferences over another.

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.

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 — 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.

Solving hard problems

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.

Data scientists at Eli Lilly envisioned a better way to manage this data. Among their requirements:

• A complete and concurrent database of all the information from a given clinical trial
• A central place from which to clean the data and manage queries
• A more durable way to bring data together that did not require as many custom integrations

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.

The result, Veeva Clinical Database (CDB), is now part of Veeva Vault 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:

1. A database that can scale to hold the amount of data generated in today’s clinical trials
2. A durable way to translate and bring in data without breaking or requiring custom coding, and harmonize data from various sources
3. A data model that is robust enough to handle the advanced requirements of complex trials, yet flexible enough to adjust as trials evolve over time
4. Automation tools that catch errors upon import and detect changes, reducing the need for manual efforts from data managers
5. A centralized process for data cleaning so that all data queries can be tracked and resolved from one place, rather than relying on spreadsheets and emails
6. A way to provide data managers, sponsors, and data providers appropriate visibility into the data they need to report on or analyze

The combination of Vault EDC and Veeva CDB creates a new concept for clinical data management, providing the ability to capture, clean, and report on clinical data at all times – at any stage of the study. These two components make up Veeva Vault CDMS and create a data foundation for adaptive, patient-centric clinical trials that can handle today’s data requirements.

So far, the results we’ve 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, and Vault 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.

Why holistic clinical data management matters

Veeva Vault 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 CDB empowers data managers by giving them better tools to aggregate, clean, and provide data with less manual effort.

Veeva is committed to transforming the total experience of data management, and Vault CDMS is proof that we are solving hard problems and driving change holistically. It’s not just EDC; it’s not just data cleaning; it’s Clinical Data Management. It’s the foundation for patient-centric digital trials, and it exists today.

Want to know more? Learn more about Veeva CDB, Veeva Vault CDMS, or Veeva Digital Trials Platform.