EDC Database Development Often Leads to Clinical Trial Delays, Study Shows
September 28, 2017
By Alex Keown, BioSpace.com Breaking News Staff
BOSTON – It has long been thought that electronic data collection, also known as EDC, would be a time-saver when it comes to running clinical trials. But that may not be the case, according to a joint study released this week by Tufts University and Veeva Systems.
The Tufts-Veeva 2017 eClinical Landscape Study report, published this month, reveals that that the time it takes companies to design and release clinical study databases is having a negative impact on conducting and completing trials. According to the survey, more than three-fourths of participants (77 percent) said they have issues loading data into an EDC application. Additionally, 65 percent of survey participants said that EDC system or integration issues are the primary reasons they are unable to load study data.
As researchers collect data from multiple sources, such as wearable technology, handheld devices, social media platforms and more, they are having difficulty loading that data in a timely manner. That delay is leading to longer clinical trial times, according to the study. Not only does that delay lead to extended trial time, it also leads to additional study costs that can add up to millions of dollars.
Hugo Cervantes, Veeva’s vice president of electronic data collection, said the study was designed to assess the challenge the industry is facing with EDC. He told BioSpace that the majority of study respondents, about 83 percent, reported they released databases after the clinical studies began. Much of the EDC technology used by companies is old, which also leads to issues, Cervantes added.
“It creates downstream delays of about a month. It’s quite significant,” Cervantes said from his Raleigh, N.C. office.
Ken Getz, director for the Tufts Center for the Study of Drug Development, told BioSpace that the study confirmed the suspicions about EDC and clinical trials.
“It was an expected outcome from the study. We believed we would see a data management environment that is feeling the impact of a dramatic changing environment,” Getz said in an exclusive interview.
The study found that delays in releasing the study database lead to increased time for other data management processes, such as patient data entry and time to lock the database at the end of the study. Respondents that always deliver the database after first patient, first visit (FPFV), take nearly twice as long to enter patient data and about 75 percent longer to lock the study database when compared to those that never deliver the final database before FPFV, the study said.
Challenges for companies were largely in protocol changes. Cervantes said 45 percent of survey participants cited that as their biggest challenges. The organizations are having to build the database without a final protocol in the design, he said.
Those protocols, coupled with the multiple applications for collecting data produces a system that’s overwhelmed by its challenges. Those challenges though are being recognized more and more. Getz said he believes companies are at an inflection point and will begin investing more in data management and data security alongside clinical research. The new environment is calling for a set of new skills that a lot of organizations, particularly smaller startup companies may not possess, Getz said. There are some indications that contract service providers have recognized the challenges and are farther ahead with data management.
“Many of the large companies have chief data officers who have experience integrating the sources,” Getz said. “Historically, data management has been a tactical support function, but now it’s a strategic function.”
That’s certainly something that incoming Novartis Chief Executive Officer Vasant Narasimhan has recognized. In an interview with Swiss Info Narasimhan said more efficient use of digital technology could save the company millions of dollars when it comes to clinical trials. Narasimhan said he will partner with a company or acquire artificial intelligence and data analytics companies. Taking such a step will “supplement Novartis’s strong but scattered data science capability,” Narasimhan told Swiss Info.