Exploring The Future Of Data Management In Clinical Research

By Alan Frederickson, Head of Technology & Automation Solutions at QuintilesIMS

How electronic tools are transforming the way we capture, monitor and react to trends in clinical research.

Most data management professionals cannot remember a time when every piece of information collected was manually entered on paper forms that had to be reviewed, edited and analyzed, with queries faxed out to trial sites. It was an incredibly time-consuming and inefficient way to manage data.

Fortunately, the data management role in clinical research has evolved considerably in the past 20 years. Advances in technology and shifts in regulatory expectations for risk management have changed how the role is performed, and the benefits these professionals bring to the research process. The ultimate goal of making sure the data collected meets quality, integrity and reliability standards to protect patients and support the regulatory approval process is still the same. But how this goal is achieved looks markedly different from previous generations.

Clinical trials are getting more complex, often requiring sophisticated monitoring and oversight processes, particularly in early phase trials where changing standards of care and multiple arms can make data collection and management more complicated. Sponsors are also facing pressure to deliver post market observational research to support value claims, which demand a unique data management approach. At the same time, the biopharma industry is under constant pressure to speed deliverables, without losing focus on patient safety. This is where today’s data managers play a pivotal role.

The evolution of data capture

Over time, the data management processes in clinical research have become more automated, with the introduction of tools such as electronic data capture (EDC) systems and electronic case report forms (eCRF). These tools helped streamline data collection, abstraction and management, and made it easier to analyze the data for trends, submit queries, and pinpoint indications of patient safety issues earlier in the trial process.

These were followed by the more recent introduction of risk-based monitoring (RBM), which moves away from the traditional approach of frequent on-site visits and 100 percent source data verification, towards a combination of activities, including centralized data collection and monitoring. RBM is a more proactive approach to risk management, allocating monitoring resources based on the level of risk identified in the data for a specific trial or site.  This enables the research team to focus on preventing or mitigating risks to data quality and safety, which drives efficiency while potentially improving patient safety and enhancing trial management.

However, even RBM tools still require data managers to transfer source data from one system into another. In some cases, monitors will wait days or even weeks to move the data, especially in observational studies, which creates gaps in the ability to rapidly analyze and respond to data trends. Though a more recent advancement may finally address this gap in the flow of clinical research data.

Real-time data with eSource technology

eSource is the latest evolution and buzz word in clinical data management technology. It is an umbrella term that can include everything from electronic capture of patient reported outcomes (ePRO), to the integration of electronic medical records (EMR) into the data management process. The key benefit of eSource is that it allows for direct data capture in real time during the patient visit, eliminating the need for data to be transferred from one system or report to another. It also dramatically reduces the need for editing and source data verification (SDV) as the data is captured and reviewed electronically at every step in the process. This cuts the cycle time while reducing the risk of data errors.

At the recent Society of Clinical Data Management (SCDM) conference, industry professionals gathered to discuss the latest data management trends in the research environment, talked about new, innovative data solutions, and shared ideas and best practices for future endeavors. Among the important industry topics discussed during the conference sessions, eSource was one of the key themes this year.

The U.S. Food and Drug Administration (FDA) has come out in support of the use of eSource technology, arguing in guidance documents that these tools [assist] “in ensuring the reliability, quality, integrity, and traceability of electronic source data. These tools also help to eliminate the need to track down source data, cutting further time and risk from the data management process.”

Using eSource tools, site monitors don’t have the option of capturing information in one document or database and transferring it later. Data capture has to be done in real-time, which means the research team has instant access to the latest patient information for every site across the trial. This rapid access to information enables more effective risk-based-monitoring by allowing researchers to analyze data as it is captured so that they can identify trends and anomalies in real-time, which is critical to staying ahead of patient safety issues. Something as simple as an unexpected blood pressure reading, or a missing patient form can be identified instantly using algorithms designed to detect risk factors, with tracking tools and custom alerts programmed to draw monitors’ attention to any piece of information that does not conform to protocols.

The quality and cost benefits of using such electronic systems have been recognized with strong support from regulators and industry organizations in achieving a more robust and safety focused monitoring environment. These benefits can translate to fewer patient safety events and more rapid decision making about dosing and effectiveness, which can cut costs and speed the path to approval. 

The transformation from paper-based systems to fully automated eSource solutions bring many benefits to the data management aspect of clinical research. The minimization of errors, improved transparency, and the potential for near real-time safety reviews are game changing for the research team and for data management professionals. Some people argue that advances in technology have diminished their role, but I believe that it has made the position a more critical component within the biopharma industry. Data managers who are able to optimize their use of electronic data records to make data more actionable in real-time while still meeting requirements for patient safety will drive measurable value to trial operations, making themselves indispensable to the research process.