‘Everything has changed’: Managing complex clinical trial data

By Maggie Lynch contact

- Last updated on GMT

Complex clinical trial data management

Related tags: trial transparency, Clinical trial, Clinical trial data, Data, Data collection, Data management, Research, Clinical trial design

As clinical trials create large amounts of data, and researchers seize the opportunity to use de-identified data as a means to develop and discovery, managing the information has become more and more complex.

With the addition of medical imaging and electronic health records (EHRs), more information is gathered through trials than ever before.

Outsourcing-pharma (OSP) spoke with Jim Bob Ward, CEO and director of Datatrak​, a clinical trial data management software as a service (SaaS) provider, on the ways in which the increasing amounts of data can be gathered and used to move research forward.

OSP:  What are some trends the industry has been seeing in regards to clinical trial data management?

JBW:​ Everything has changed. Electronic data collection (EDC) was a commodity but now everything in this world has to do with big data and big data analytics. With recent Food and Drug Administration (FDA) guidance on integrating medical imaging into the clinical trial process, you’ve got a structural shift in the industry where we now have to deal with more data then we have ever before.

Big data analytics is the new and ultimate trend in clinical research. Cloud-based Software as a Service (SaaS) platforms go beyond traditional EDC site data capture to include patient direct, wearable devices, and core lab images with endpoint image adjudication. The ability to collect data from every possible source (including IoT) has made stand-alone EDC systems a low price and low function commodity.

This amount of data has really shaken up the industry. To do a clinical trial you’re trying to collect data from every single source. [Like with image capture] within a scan is its own little database it keeps the DICOM standards and those standards include 4,000 packs of information structured standardized data.

When you go in and get a scan, you don’t always get one scan, you don’t always have one visit in a clinical trial, so, you’re talking about significant data captured on these images.

OSP: How has the industry kept up with the increasing amount of data?

JBW:​ Now that we have access to big data we need to use that advance protocols for research and development to create these products and that requires a new person and new methods; a data scientist.

It used to be we would have one endpoint in a trial and we would do trials that way, with the new advances we could have multiple endpoints within a trial, now you can use advanced techniques for adaptive trial design.

New regulatory driven methods of human and machine data capture are defining the next generation of SaaS platforms with big data analytics.

OSP: How can EDC, data management systems, etc. impact the success of clinical trials?

JBW:​ Clinical trial management systems give researchers the ability to do cross-study analysis so you can look at the entire research program, not just one study. Metrics within one study are great, but if you have multiple studies, clinical trial management services (CTMS) gives you the ability to measure the performance of your program, not one trial.

It's not just limited to how we collect data but what we do with the data to make better decisions.

The introduction of multiple endpoints within a clinical trial allows clients to derive maximum benefits from fewer numbers of trials.

The use of medical images in clinical trials to capture and qualify multiple endpoints through image endpoint adjudication creates unlimited possibilities for adaptive trial design to dynamically adapt treatment legs to optimize overall program return on investment.

OSP: What are some ways CROs or sponsors can best manage complex trial data?

JBW:​ The key to managing complex trial data is using a CTMS to standardize and automate intelligent workflow, Business Intelligence, and user-specific dashboard access to metrics and reporting capabilities.

The legacy ‘big iron’ systems are now being replaced by cloud-based platforms that are self-configured and driven by subject matter experts rather than a third party IT professional to optimize resources and deliver operational efficiencies across ALL trials in the sponsor’s R&D program. 

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