Trial complexity, info explosion driving data management evolution

As clinical trials become more complex, study data management is increasing in complexity as well. Outsourcing-Pharma spoke with Henry Levy, strategy lead for CDMS at Veeva Systems, about what factors are helping drive the changes, and why trial teams need technology that can adapt to changing needs.

OSP: Clinical data management has come a long way. Can you talk about its evolution?​

HL: The most important part of studies is the traceability of data and being able to answer questions like where it was collected, by whom, and when did it change. But clinical trials started on paper, making data verification hard. In the 1980s, pharmaceutical companies would print out forms on carbon paper to create copies; the process involved a lot of manual work, including shipping and filing documents in Iron Mountain.

In the 1990s, electronic data capture (EDC) changed how the industry worked by allowing healthcare professionals to enter data directly into a system. That’s become the standard, even though there's still use of paper in studies. Over the next 15 years or so, nothing much changed, not the technology or the processes used to capture data.

OSP: There has been an acceleration recently to advance clinical data management. What are the drivers?​

HL: In data management, there have been three significant changes. Let's start with the explosion of data.

Historically, there was a certain amount of information captured for each patient. The site entered most of it, with about one-fifth of the data coming from external sources, like blood analysis from a lab.

Today, the information entered by physicians is about one-fifth, and the majority of data comes from wearables, biomarkers, different types of labs, genetic reads, etc. This makes more data available for analysis from a greater number of sources, and the industry is looking for ways to bring it all together.

Then there's the growing complexity of the clinical trial. We now have adaptive trials that could change as you execute and where the data tells you what to do. For example, if a patient is not reacting to a drug, you can make decisions on the best next steps to take. Also, immune-oncology, multi-arm, and collaboration trials are adding new levels of complexity to how trials are run.

Finally, there has been a rise in study amendments. The most common amendment happens when you learn something new about a drug, so you have to make changes mid-study. The second is addition or exclusion requirements for patients participating in trials. During COVID-19, amendments have been exacerbated as studies changed so frequently.

Now, what does this mean for these EDC solutions that have remained primarily static? Suddenly, the industry needs systems that can be dynamic and address change.

OSP: How is modernization in data management evolving?​

HL: First, there’s the cloud, which is here to stay. Companies like Metadata, one of our competitors who’s an industry innovator, changed life sciences as one of the first cloud-like solutions when people didn't even know what the cloud was. The issue is that they built their stack almost 20 years ago, and rebuilding all your applications to meet the needs of today’s trials is very difficult and expensive.

At Veeva, because we started later, we can do things that are simple. For example, in most EDC systems, if a site coordinator enters data and gets pulled away, they get timed out, and the data is lost. Compare that to buying something on Amazon, if you leave and come back, the data is saved. We’ve incorporated simple technology advances like that, which really add to the user experience.

OSP: What is Veeva currently working on to accelerate modernization?​

HL: To provide the agility needed in modern trials, we have an EDC that allows painless mid-study amendments. You don't have to create an entirely new study and migrate data, which other systems have to do. You can do an amendment and roll it out in a matter of minutes. There’s absolutely no downtime because it’s a modern system.

Some of our competitors take between one and two weeks to do the same thing. Imagine if a sponsor has to do an amendment every week. That means they will always be behind.

With the proliferation of different data types and sources, the industry needs to find a way to bring it all together in one place. Today, no one has a good solution. We’re working on a product called CDB that delivers an environment that can consume and ingest data in an easy way.

If you look toward the future, electronic source (eSource) becomes the next exciting development to go mainstream in data management. Today, even with an EDC, investigators running trials still write things on paper. 

Clinical trials capture three to four times the amount of data you would produce in a standard health care environment. Because of that, electronic health records (EHR) aren’t suitable for studies. Sites have to pull out a paper form, write down lots of information, and manually enter it into an EDC. eSource delivers the ability to, instead of using paper, create an electronic form that can be used, stored, and audited.

As soon as the industry can do that, clinical trial efficiency will improve dramatically. The advancements to integrate different types of data and eSource will enable even more innovation. That's when the value for the industry really takes off.

OSP: The continued use of paper and a lack of technology adoption by users has been an ongoing issue in life sciences. What can be done to improve adoption?​

HL: Investigators have a difficult job, yet they do it with a commitment to quality and patient care. But the systems they need to use don’t make the job any easier. They are used to calling a cab or ordering lunch with a few clicks on their phones. At the research sites, they have to work with big machines to enter data.

The software should be as simple as consumer apps and deliver a familiar user experience. If we do that, they can focus on patients, not on administrative tasks.