Real-Time Clinical Trials Are Here. Are Your Data and Biometrics Infrastructure Ready? 

In April, the FDA announced that it would begin using AI and data science tools to monitor clinical trial data in real time, starting with two proof-of-concept trials involving AstraZeneca and Amgen. According to the announcement, the goal of these real-time clinical trials (RTCTs) is to shorten drug development timelines by giving the agency earlier visibility into emerging trial data. For many in the industry, this is exciting news. But it also puts new pressure on a familiar problem: Many clinical trial data review models are still fragmented, late, and query heavy.  

If trial oversight becomes more continuous without upfront governance, this could mean more noise, more follow-up, and more burden for sites and study teams.  

So how can sponsors get ahead of a more continuous review environment without making trial execution harder for the people closest to the data? 

The Issue With Traditional Data Review Models and Real-Time Clinical Trials 

In a traditional trial, biometrics teams are typically brought into high-pressure moments. By then, data quality issues are often already baked in: late transfers, unresolved discrepancies, inconsistent vendor formats, and reconciliation gaps that should have been visible weeks earlier. They are downstream consequences, and there is still time, however painful, to address them. 

RTCTs remove that buffer. When the FDA is viewing safety signals and endpoints as the trial progresses, the data reaching the agency must be reliable enough to act on. A signal that reaches the agency before it has been properly monitored, contextualized, and reviewed could trigger unnecessary follow-up, premature concern, or operational disruption based on incomplete information. 

A more continuous review environment requires answering questions at study startup that most teams currently defer until well into a study: 

• How will data from EDC, labs, imaging, eCOA, safety systems, and external vendors be integrated into a single, reviewable environment — and how quickly? 
• What review cadence is appropriate for each data domain, given the endpoints and the regulatory expectations of a real-time model? 
• How will discrepancies, missingness, outliers, protocol deviations, and reconciliation issues be identified, escalated, and resolved in time to matter? 
• What governance structure ensures that the data reaching the FDA has been properly monitored and contextualized before it is interpreted? 
• Who, across clinical operations, data management, biostatistics, and medical review, is responsible for each piece of that chain? 

In an RTCT model, by the first interim analysis, the operating model should already have been tested through months of live data review.  

Move Biometrics Upstream 

Biometrics expertise alone cannot answer those questions if the underlying data isn’t ready to support them. The data infrastructure has to ingest diverse data streams early, identifying quality issues as they emerge rather than waiting until database lock, and giving biometrics teams the visibility they need to monitor, query, and contextualize data in time for it to matter. 

For sponsors moving toward an RTCT model, that means evaluating whether their current data infrastructure can actually support what their biometrics teams will need to do. To effectively move biometrics upstream, sponsors should: 

Map the protocol-driven data flow, including each source system, vendor, transfer cadence, review dependency, and decision point.

This includes designing your reporting and dashboards so that review is focused on appropriate safety and efficacy signals. You also want to make sure that the right teams are reviewing at the right times. 

Identify likely pain points before study start. For instance: What are you going to do if your data doesn’t come in on time or in an expected format? Having answers to questions like this will be integral to real-time data review.  

Building Toward Real-Time Readiness 

Sponsors best positioned for real-time clinical trial oversight will be the ones that design biometrics strategy and data infrastructure together before the study begins, not as separate workstreams that converge under pressure later. 

Real-time clinical trials will not be enabled by faster data movement alone. To enable effective real-time clinical trials, sponsors will need:  

• A coordinated foundation of data infrastructure that supports visibility and standardization 
• Governance around ownership, expectations, accountability, and review strategy
• An experienced biometrics team that can connect strategy with execution to drive the creation of decision-ready evidence that real-time clinical trials require. 

Preparing for real-time clinical trial oversight? Learn how eClinical Solutions’ Biometrics Services and the elluminate^® Clinical Data Intelligence Platform can help you build the data foundation, governance model, and biometrics support needed before the study begins.