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  • February 18, 2021

Data challenges in decentralized clinical trials

Alison Shurell
Global Head of Marketing
This is a syndicated post, view the original post here

In the span of a few months, the COVID-19 pandemic has greatly accelerated the adoption of decentralized clinical trials. According to a recent survey of 252 clinical research professionals conducted by Informa Engage on behalf of Oracle, 76% of clinical trial teams say they have sped up the use of decentralized trials methods, and just less than half are looking at new vendors to help in the process.

Significantly, there’s likely to be a continuation of the trend over the next two years. Despite some challenges, decentralized trials have made participation in clinical research easier for patients – vital at a time when the pandemic has made in-person site visits more difficult. In fact, the survey found that 64% of respondents had adopted patient-facing technologies or alternatives to in-clinic visits.

New data, new formats, new challenges

One of the issues decentralized trials presents for clinical teams is capturing, managing, and analyzing data from new sources, and in new forms. Two-thirds of those surveyed have implemented remote data collection in their trials – notably from patient apps, ePRO, and wearable devices – while more than half say they use or will introduce wearable devices within 18 months.

While these patient-worn sensors can provide a wealth of real-time patient data, almost half in the survey reported that effectively tracking all that data is one of their biggest concerns when it comes to decentralized trials. Of similar concern is the ability to integrate all that data together into a coherent view that can be accessed and used by all stakeholders to make critical decisions about the trial.

These considerations have companies re-evaluating the systems they use to manage trials, says James Streeter, Oracle’s global vice president life sciences product strategy.

“People don’t want to expand and manage a dozen vendors; they’re looking for companies that can unify the data as well as manage services for them, because they don’t want to have six patient help desks or six patient concierge services to deliver devices,” he says. “The system has to simplify how all the downstream data is handled so companies can see all the information together in one place.”

Smart systems to ensure reliability

With both more data and more data types resulting from decentralized trials, the survey showed that companies have big concerns about ensuring reliability and quality. That requires clinical trial systems to be flexible as well as integrated, so they are able to manage data in different ways for different uses.

For example, the raw data stream from a patient-worn device that tracks pulse rate likely contains far more information than is needed for purposes of determining safety and efficacy. The clinical trial system should make it simple to extract the relevant data from that stream, in a way that ensures it will meet regulatory requirements. That extraction is also important to deal with the “bad” data that is likely to be part of the raw feed.

“When you have patient-worn devices, people take them off sometimes or the batteries run down, leading to a false or missing reading,” Streeter notes. The challenge is to create new algorithms, or update existing ones, that can automatically clean the “bad” data.

At the same time, the system should allow others on the trial team to have access to the full data set, which can provide data scientists and analysts with the opportunity to glean additional insights for current and future trials.

“The data coming in today is much different than in the past,” according to Streeter. “As we build newer systems, we’ll be handling a lot more technology, and companies will need to have a more unified platform that lets them coordinate that.”

Join us on Feb 23rd for the Clinical Leader Live Event: Decentralized Trials: Top 5 Challenges (And How To Overcome Them) to hear key industry experts discuss the quick adoption rate of decentralized trials and what they are doing to effectively track data and ensure quality and compliance in this new environment.

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