The Importance of EDC: How EDC Can Support Early-stage Trials and Beyond

This blog was authored by Katrina Weigold, Vice President of Global Partners at Medidata. Katrina has grown and cultivated global partnerships at Medidata for over a decade, expanding the reach of the company’s transformative platform for clinical development, commercial, and real-world data.

In the first blog in this series, we looked at the increased complexity of Phase I clinical trials and how technology—specifically electronic data capture (EDC)—can support sponsors and partners in the conduct of these important studies. Leveraging tools like EDC can set the pace and success of the entire study. While these trials face considerable challenges in their early stages, a robust and intuitive solution can help to mitigate these obstacles.

What Is EDC?

EDC is a system for collecting, managing, and cleaning site-, patient-, and lab-reported data in an electronic format for use in clinical trials. EDC, first used in the 80s and 90s, replaces the traditional, paper-based data collection approach to streamlining and centralizing data collection, which drastically improves drug development timelines and costs.

EDC systems validate data entered by clinical trial sites to ensure accuracy. Data managers and clinical research associates (CRAs) can then review and query this data, with queries automatically flagged to the sites. Ultimately, an EDC system provides the central and secure place for validated, locked data ready for analysis at the close of the clinical trial.

Trials using paper and hybrid data collection tools are in massive decline and this decline is expected to continue. From 2019-2020, 81% of Phase I clinical trials were using only EDC. Looking ahead to 2022, 90% of Phase I clinical trials are expected to use only EDC applications¹.

Benefits of Using EDC

Secure Clinical Trial Data and Control

Collecting and managing clinical trial data in an electronic system, which is usually cloud-based, ensures secure access and control from anywhere. When data was collected manually and on paper, it could be lost and destroyed without any backup or recovery options.

EDC Validation and Quality

An EDC system will have standard built-in checks. Examples include basic checks like dates being entered in the right format or the age of a patient being within acceptable range for the study, or more complex checks like if a patient is female, then a pregnancy test might be warranted before participating in the study. An EDC system will also run automated data quality checks and flag any errors or data anomalies. Before electronic data capture, these checks were done manually and, as such, subject to human error. Automated checks can save sponsors and CROs a considerable amount of time, which during early-stage trials is of utmost importance.

Traceability

Having traceability of any changes to data or study design is also key. An EDC system will automatically store these audit trails, which can easily be viewed.

Accessibility and Availability

EDC systems provide faster and broader access to data. As soon as data is entered into the system, all users have access; a principal investigator (PI) is able to sign off the data, a CRA is able to review it remotely without coming into the site, a data manager can then approve the data, and the sponsor or CRO is able to track the study’s progress. The benefits of an EDC system during the COVID-19 pandemic cannot be overstated. Many clinical trials were able to continue due to electronic and remote data capture, as well as the ability for PIs and CRAs to remotely review and monitor data.

EDC System Benefits for Phase I Clinical Trials

With reduced budget and timelines for early-stage trials, using an EDC system from the start of the study can be hugely beneficial. Study teams are able to get an indication of results as quickly as possible. This is important as it's not uncommon for early-stage clinical trials to undergo changes and pivots (e.g., in dosing levels).

Additionally, being in an EDC system in Phase I clinical trials allows the opportunity to use other tools like eConsent (electronic consent) and RTSM (randomization and trial supply management) to help speed up timelines. eConsent informs patients on a clinical trial and allows them to consent to participate remotely; the pandemic truly demonstrated the value and importance of this tool.

RTSM randomizes patients into the study cohorts (e.g., placebo vs. investigational product, different dosing levels, etc.) RTSM can be seamlessly integrated with EDC to eliminate duplicate data entry and decrease the administrative burden associated with traditional data collection methods, which significantly reduces risk and costs.

For small to mid-sized CROs conducting Phase I clinical trials, an EDC system helps differentiate them from the competition by conducting efficient and high-quality trials and by being able to quickly scale and progress into Phase II and Phase III trials.

Things to Consider When Choosing an EDC Solution for Phase I Clinical Trials

Speed and Quality

The speed of having an EDC system up and running and being able to take in the clinical trial data from the first patient enrolled in the study is key, but the quality and robustness of the study build are also imperative to avoid errors and problems further into the study. One way to ensure speed and quality of an EDC system is by using a SaaS provider who has experience with early-stage trials and a proven track record building Phase I studies across therapeutic areas. This is particularly important for small to mid-sized CROs specialized in Phase I studies, in order to avoid costly errors and delays. 

Scalability and Flexibility

Equally important is experience across drug development phases and implementing an EDC management system that the study team can take forward into Phase II and III studies, as well as the ability to incorporate additional solutions like eConsent and RTSM.

While Phase I clinical trials are typically smaller in size, using a vendor that could scale larger Phase I trials (like the COVID-19 vaccine trials, for example) could be an important differentiator. Such a vendor would be capable of running a single site, 5-10 person study to a study using thousands of sites and tens of thousands of patients. This also means the ability to collect and manage an increased amount of data. When considering an EDC system for early-phase trials, it’s also an investment for subsequent studies, which will be larger in size.

The industry is looking at ways to speed up the development process, such as running trial phases in parallel. As such, an EDC system would be imperative for the scalability, flexibility, and ability to adapt as the trial progresses. 

Cost of Ownership

When it comes to data management technology, it’s not about the cheapest solution, but the most valuable one. A lower-cost solution could mean that you’re spending more time resolving issues and incurring costs due to the need to review and clean the data. As such, it’s important to look at the total cost of ownership and choose a system that is high-quality and efficient, as well as finding a pricing model that fits your study and budget.

One of the challenges in adopting EDC is the time and resources required to configure the EDC to support the study. With a straightforward, pre-configured solution, the study team can begin immediately, making a compelling case for early implementation of an EDC system.

In the final blog of this series, we will look specifically at Medidata’s Rave EDC and how this solution can support early-stage trials and beyond.

Read the first blog in this series here.

Medidata delivers tailored, flexible, and cost-effective solutions for small to medium-sized CROs. Supporting over 4,000 Phase I studies for 400 clients over the past two decades, Medidata helps its partners attract and win more sponsor bids and execute them successfully with its proven, innovative technology and unmatched partnership experience. Read more about Medidata’s EDC offering here.

¹ EDC Market Dynamics and Service Provider Performance (4th Edition), Industry Standard Research, December 2020.