Let’s ask a trick question. 

Do you think your organization’s data is ready for AI, or AI Agents?

Most sponsors and CROs instinctively answer “not yet.” What this really means is that they don’t believe their data isn’t fully centralized, dictionaries aren’t perfectly aligned, and too many systems still operate in parallel. The result is that AI gets parked on the roadmap, waiting for a future state where everything is clean, standardized, and coordinated.

Here’s the twist; waiting for that moment is very thing holding organizations back.

When it comes to implementing agentic AI, the bigger risk right now isn’t imperfect data. Instead, it’s waiting for perfection before acting.

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eCOA’s time has come. The market is currently estimated to be worth $2.3 billion, with projections showing it reaching nearly $5 billion by 2030. Despite this, paper still plays a prominent role for some clinical trials today.  

At first glance, paper may seem simple and familiar, even economical. However, in today’s regulatory and operational environment, paper COAs are not a risk averse choice when held to the standards of what sponsors, CROs, and regulators are looking for trial data to prove.  

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Electronic clinical outcome assessments (eCOA) have become essential for modern clinical trials, offering numerous advantages over traditional paper-based methods. However, the benefits of eCOA can only be fully realized if the data collected is of the highest quality. Ensuring data quality in eCOA clinical trials requires a multifaceted approach, encompassing platform design, patient engagement strategies, robust data validation procedures, and strict adherence to regulatory guidelines. This blog post explores key strategies for achieving and maintaining data quality throughout the eCOA process.

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