Staying Relevant: Forward Motion in Clinical Data Management

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Staying Relevant: Forward Motion in Clinical Data Management

By Cheryl Silva and Sara Doolittle |June 2, 2022

Industry wide, the past two years have seen rapid changes in the approach to clinical data management. To some extent, this is the natural result of working through a pandemic, where remote collaboration and efficiency are at a premium. Yet the seeds of change were planted far earlier, with artificial intelligence, data visualization, and other technological advances paving the way to sophisticated data management.  Now is the time for the industry to accelerate and embrace these shifts—and Functional Service Providers (FSP) are an increasingly effective means to do so.

People, technology, and approach: three factors for success

Clinical data management has two key elements: the professionals who manage all the data-related tasks, and the technology they use to perform those tasks. Both are critical to success. The most experienced data manager will be bogged down by poor technology; conversely, cutting-edge technology is worthless in the hands of someone who doesn’t know how to use it. There is a third overriding factor, as well: the willingness of study teams to include data mangers as integral parts of the team, using their insights to identify issues from the start, design issue-management plans, and deploy those plans to mitigate problems before they overwhelm the study.

Fortunately, the industry has begun embracing this strategy, viewing the study database holistically. The advantages are immediately obvious. Taking an analytical approach to data management and having data managers work closely with study teams helps ensure that data are appropriately prioritized, which speeds the trial overall. Data are processed correctly the first time, saving future costs and headaches, and allowing teams to be more nimble as they move through the changing clinical trial environment.

With the approach in place, what about the people and the technology?

Centralizing data management: the key to standardization

First, a word about centralization. Today, a record number of systems are being developed to support smart data management. As a result, many data managers are juggling multiple tools. The quest for efficiency seems to demand implementing more rigid rules that harmonize these tools—yet that strategy eliminates the flexibility to be able to treat each study uniquely. Choosing between streamlining and flexibility means the solution for one study doesn’t always make sense for another. Starting from scratch each time contributes to cost. The solution is one of the biggest innovations in data management today: Centralization.

Sponsors are not only centralizing the management of their data, but their data management technology, too. For large pharmaceutical companies with a dozen or more business units, this approach ensures alignment among groups. For smaller companies that outsource their studies, such centralization supports standardization even when dealing with multiple vendors. In both cases, centralization means taking a stable approach across studies, vendors, and teams, delivering clarity and consistency.

Outsourcing infrastructure: leveraging a functional service provider (FSP)

Of course, centralizing data management requires infrastructure.

By definition, FSPs assign experts to projects. Sponsors gain the advantage of that expertise, without the time, expense, and hard work of hiring and training a team. The FSP seamlessly becomes an extension of the in-house team—whether bolstering an existing in-house data management group or creating one as an extension of the larger study team—always operating under the sponsor’s SOPs and processes. This solution solves the people portion of sophisticated data management. It also instantly provides the ability to implement a centralized technology platform, by bringing that expertise in-house.

Ease and consistency: the value of the right technology tool

Having the right technology platform in the center of data management means that no matter which electronic data capture system (EDC) is being utilized, the approach can be consistent. The EDC is used for its intended purpose, data capture. The platform then creates and leverages a suite of core reports across all studies, all therapeutic areas, all study phases.

This provides a consistent starting point for creating custom visualizations and listings for study teams, with teams modifying similar reports to provide precisely what the team needs, when they need it. This approach maximizes reusability while minimizing stressors. From study to study, the reports and visualizations are familiar to study teams, decreasing learning curves, and simplifying review. Most importantly, the efficiencies built into this approach translate to cleaner data and faster, more cost-effective trials.

Centralized data management: the power of partnering people and technology

Implementing the right technology tool in partnership with an FSP data management team creates an ideal environment of efficiency. Partnering the two elevates data management, creating a sophisticated, analytics-based approach, with out-of-the -box operations delivering end-to-end data management that is both adaptive and cost focused.

Going forward, as trials scale, data multiply, and cost-pressures increase, these strategies supply a strong foundation for clinical trial data management. That this is the direction the industry is taking is cause for celebration.

Path to sophisticated data management

Watch this engaging 30-minute webinar where Premier Research experts explore clinical data management, sharing historical context, industry trends, and groundbreaking innovations.



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