Why a Data Fabric Could Future-Proof Clinical Trials


As researchers attempt to future proof clinical trials against massive disruption, their infrastructure needs must embrace the new world of data.

In the rush to research and offer solutions for COVID-19, a glaring gap has emerged. Clinical trials, the hallmark of medical research, typically happen in close quarters. Research followups and in-person evaluations have all but stopped — for COVID research and existing clinical trials for a variety of medical questions.

Medical trials already strain the limits of human participation with researchers relying on the good faith and interest of participants for months or even years as they collect data. These trials plan for some loss of participation as the trial goes on, but with global disruptions like a pandemic, teams are experiencing unprecedented loss of participation and, thus, data. There’s never been a more critical time for embracing digital transformation.

See also: Academics May Use AI To Greenlight Research Projects

Embracing Remote Clinical Trials

Like companies who couldn’t imagine a majority remote workforce a few years ago, moving clinical trials online was also an incomprehensible feat. However, unprecedented times call for new, innovative methods.

Early interest in remote trial components was there, but post-COVID, the field has exploded. Crunchbase identifies several startups aimed at facilitating remote trials. Large trials that track participants for years could benefit the most from online components. Still, even massive efforts to find quick solutions in response to this and future pandemics are paying attention.

Everything in our lives is available to us through wearables and apps, reducing our need to take time from our schedules to run errands or accomplish tasks. Researchers envision the same convenience for trials, utilizing data collection from distributed systems like IoT (wearables, for example).

The Price of Remote Trials

While these remote options may inspire more people to volunteer for trials — especially ones happening fast and happening now — executing trials at this scale will require new, creative systems to process data, and new systems to manage the workflow.

Research teams aren’t always trained in machine learning engineers or data scientists. As systems become more complex, organizations must have a grasp of what data they have and where it is.

Research benefits from data availability, but it’s also subject to some of the most stringent compliance regulations. In-house solutions coded to manage data governance while also reducing data silos are expensive and difficult to manage. Alternately, as technology solutions evolve, the price of moving data to the solution becomes prohibitive.

A Data Fabric Solution For Research

One of Gartner’s biggest buzzwords for 2019, Data Fabric, marries data democratization with governance. A data fabric addresses the needs of modern clinical trials by:

  • Improving data availability across the board
  • Providing better storage solutions that take advantage of today’s hybrid systems
  • Breaking down silos
  • Improving scalability by prioritizing not moving data (but moving the system to the data)
  • Account for legacy systems weighing on research teams

A proper data fabric allows teams not only to store data but to manage it actively. A data fabric provides unification solutions and ensures that organizations manage data loss and remain compliant with comprehensive governance.

As researchers attempt to future proof clinical trials against massive disruption, their infrastructure needs must embrace the new world of data. Nothing stays behind siloed firewalls and on-premise storage systems anymore. A data fabric could be just the solution research needs to follow through with digital transformation.

Elizabeth Wallace

About Elizabeth Wallace

Elizabeth Wallace is a Nashville-based freelance writer with a soft spot for data science and AI and a background in linguistics. She spent 13 years teaching language in higher ed and now helps startups and other organizations explain - clearly - what it is they do.

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