We hope you like the new look of Xtalks.com. Take a site tour. Now you can join the community or login.

X

Clinical Trial Operations: 5 Things You’re Probably Doing Wrong

Electronic data capture (EDC) and eSource are becoming increasingly common in modern clinical trials, however both of these tools are rarely integrated with any significant capability, leading to wasted time and resources.

Clinical Trial Operations: 5 Things You’re Probably Doing Wrong

By: Sarah Hand, M.Sc.

Posted on: in Blogs | Life Science Blogs

In 2007, there were nearly 50,000 clinical trials registered with ClinicalTrials.gov, the National Institutes of Health’s (NIH) database of active clinical trials. In the past decade, that number has increased exponentially to just over 250,000 clinical trials registered this year to-date.

With the explosion of activity in the clinical trials space, clinical research organizations (CROs) and other vendors have developed innovative new ways to deal with regulatory requirements and manage the always-expanding wealth of clinical data. But with increased complexity comes increased operational demand, which creates more cost, and yet our clinical sites are still not operating at peak effectiveness.

Electronic data capture (EDC) and eSource are becoming increasingly common in modern clinical trials, however both of these tools are rarely integrated with any significant capability, leading to wasted time and resources. The pharmaceutical industry’s historically conservative attitude, combined with technological barriers, have been touted as some of the main explanations for the slow adoption of such technologies.

“I think that 90 percent [of sponsors] would be extremely open to moving away from such an inefficient model,” says Hugo Cervantes, VP of Vault EDC for Veeva, a cloud-based software provider for the life sciences industry. “They’d absolutely be willing, especially in the US, to move away from that model, but in this industry there is always a reluctance to change from something that’s proven but might not be working perfectly.”

In terms of managing the collection, organization and analysis of critical study data during a clinical trial, there are five major inefficiencies that need to be addressed. Without implementing a more holistic clinical data management system, sites are destined to run at a sub-optimal level, patients are destined to see research cycles extended, all ultimately compromising the success of the study.

1. Creating Study-Specific Paper Source Forms

Even sites that have already adopted EDC still use custom paper source forms for each and every clinical trial they run. This can create multiple problems, not least of which is the time spent creating these forms based on specific requirements provided by each sponsor.

“Pen and paper is ubiquitous, relied on everywhere as the gold standard, however it doesn’t do anything for the patient when they leave [the doctor’s] office,” says Richard Young, VP of Vault EDC for Veeva. “What we have to do is replace the reliance on pen and paper and show that technology can not only replace it, but actually consign it to history.”

According to the Society for Clinical Research Sites (SCRS), 90 percent of clinical sites using EDC also create study-specific source data forms. For each study conducted by those sites, the clinical researchers spend an average of three days generating these paper forms.

Time and resources spent creating these documents could be better used to recruit patients to the trial, with patient recruitment and retention being one of the greatest challenges that many sites face. What’s more, the inefficacies of this practice don’t end with the creation of these study forms; all of the physically-collected data must eventually be entered into the EDC system for analysis.

2. Manually Transcribing Data into EDC

Data collected on paper during patient site visits must inevitably be entered into the EDC solution. Manual transcription can take hours of time after each patient visit, and data entry tasks are often delayed weeks after the data was initially collected.

This presents site coordinators with an overwhelming backlog of clinical data to enter into EDC. Since manual transcription is not always accurate, data entry professionals could be entering the same data multiple times as source data verification (SDV) identifies inconsistencies between the original paper source forms and what was entered into EDC.

When asked about some of the barriers to adopting an eSource system that could remove the need for manual data transcription into EDC, Young points to the doctor-patient relationship and how poorly-designed technologies could do more harm than good.

“So much importance goes into that interaction, and if a doctor is fighting the technology and can’t get it to work, that weakens the relationship between patient and caregiver.”

3. Trying to Achieve 100 Percent Source Data Verification

“Why have we done SDV for the last 40 years? Because someone claimed it was essential,” explains Young. “There’s not a single regulation that says you have to do SDV and yet we spend billions of dollars every year doing it.”

SDV is one of the most time and cost-intensive stages in a clinical trial, especially for large, late-stage studies. Traditionally, clinical trial coordinators have tried to achieve 100 percent SDV, however this goal is often unnecessary as some estimates suggest that data entry is up to 97 percent accurate.

With this in mind, sites have begun implementing a risk-based monitoring approach (RBM) to trials, whereby the quality of the most critical study data is prioritized. But this too has its flaws as identified study errors can trigger costly site visits.

“Forty percent of the average trial budget goes down to monitoring,” says Young. “A very large proportion of that is SDV, but if you automate the source, you no longer have to do SDV. This can cut 30 percent off the average spend of the clinical trial. That means we’ve got more money, time and ability to invest in delivering better and better assets.”

The solution to this problem is to combine eSource and EDC. With this approach, data accuracy is maintained from the site of electronic collection through to the EDC system and eventual analysis. While data monitoring and verification is still occasionally required, Young suggests an approach he calls, “risk-based everything (RBX).”

“If you digitize the source from the point of collection in front of the patient, SDV requirements go to zero percent,” says Young. “The true definition [of risk-based monitoring] is monitoring the overall stage and status of your project, and not focusing on individual data points.”

4. Choosing Separate Vendors for EDC and eSource

Clinical sites and sponsors who are well-aware of the inefficiencies of paper data collection are starting to adopt eSource systems as well. Unfortunately, more often than not, sites opt to engage two different vendors for their eSource and EDC systems, creating more problems as opposed to offering solutions.

Even overlooking the challenges inherent in managing two separate vendors, study coordinators must attempt to integrate two unique systems that were not necessarily designed to be synergistic. Sites can be forgiven for choosing to implement only EDC when you consider that few vendors offer a combined eSource and EDC system.

“You’re having to pay for two vendors, two designs and builds, with two study teams focusing on additional applications design,” explains Cervantes. “Then, you have to integrate these two disparate systems so that whole integration is taking away a lot of the benefits of eSource, which is supposed to be real-time access to the data.”

Veeva’s Vault Clinical Suite is the first unified cloud-based platform that requires just one study build. Their EDC and eSource platforms are already designed to work together so users aren’t tasked with making two different solutions fit their needs.

5. Settling for Study Builds that Take Weeks

It can be a long and arduous process to set up a clinical trial, and investigators are often concerned that including technology into the build will result in more programming-related delays. It’s true that creating paper source forms takes a significant amount of time but even when EDC and eSource are being incorporated into the trial framework, a study build can take weeks.

Why is this? Organizations that chose two separate vendors to setup their EDC and eSource solutions must deal with two different designs, two different builds and two different timelines. At the same time, site coordinators must also address regulatory requirements in an effort to get the study underway as quickly as possible.

“A lot of the time that goes into a build – whether it’s an EDC or eSource study – is spent in the review and approval part of the cycle,” says Cervantes. “A modern platform should be able to alleviate that by having built-in workflows that manage the triggers and notifications of who should be doing what, and when.”

Using an integrated eSource/EDC system developed by a single software provider can cut the time devoted to study builds from weeks to days. Not only does this type of system accelerate study start-up, but it also provides clinical investigators with access to real-time study data for better decision-making.

Learn more about managing clinical data using eSource and EDC by watching Veeva’s on-demand webinar now.

How do you manage clinical data collection? Are you still using paper source forms? Share your opinions in the comments section below!


Related Vitals


Leave a Reply

Your email address will not be published. Required fields are marked *