Clinical development is becoming harder to predict. Increasing trial complexity, protocol amendments, expanding regulatory requirements, global and multisite execution, end point overcollection, and competition for patients and sites place growing pressure on sponsors to control risk and make informed decisions earlier. At the same time, study data are generated across an expanding range of clinical, patient, operational and digital sources. Yet more data does not automatically create more insight. Without a strategy for determining what matters and how that data will be used, growing data volumes can introduce noise, duplication, inconsistent standards, and downstream review burden.

The challenge facing pharma is no longer simply how to capture data. It is about ensuring the right data flows to the right people at the right time to support faster, more informed decisions. Too often, teams collect data because it is available rather than because it is necessary, creating duplication, review burden, and operational inefficiencies that can slow study execution. At the same time, rising expectations for near-real-time oversight, risk management and predictive decision-making are exposing the limitations of traditional approaches to clinical data collection and review.

Electronic data capture (EDC) catalyzed the industry’s transition from manual, labor-intensive collection to digital clinical data management. However, as trials have become more complex, the volume and diversity of data sources have expanded beyond what an EDC-centered model was originally designed to accommodate. The challenge is not to eliminate EDC, but to reduce the amount of transcription required by designing smarter, more direct data flows around the sources that matter most. Sponsors must determine which data are critical to the protocol, select reliable and nonduplicative sources, and design an end-to-end flow that makes those data available for review, monitoring, and analytics when decisions need to be made.

This webinar will explore how a criticality led, digital-first strategy can help sponsors connect the right data at the right time while reducing unnecessary reliance on transcriptive data collection. Expert speakers will examine how nontranscriptive collection methods can reduce site burden by limiting manual data entry and confirmatory queries linked to potential transcription errors. The discussion will also consider how reducing transcription can lessen internal review and query-management burden, accelerate data availability and help study teams make informed decisions sooner. By drawing on emerging approaches such as IQVIA’s eCOA and eSource capabilities, the webinar can show how connected patient and operational data support integrated review, monitoring and analytics, helping teams distinguish meaningful signals from noise and respond before emerging issues become operational delays.

Rather than presenting EDC-less development as an abrupt technology replacement, the session will outline a pragmatic evolution towards a connected clinical data ecosystem. Attendees will consider how purposeful digital data collection, automated data flow and an appropriate data foundation can support earlier data-driven decisions, reduced execution variability and more continuous insight across the study lifecycle. The webinar’s central message is clear: the next era of clinical development will not be defined by how much data a study captures, but by how effectively the right data are connected, understood and converted into action.

Key Takeaways

• Predictability Begins Before the First Data Point
Understand why sponsors need to define study criticality, intended decisions and data requirements before selecting collection technologies. Attendees will see how an integrated data strategy can help identify and address risk before it becomes a delay.
• Find the Signal Before It Is Lost in the Noise
Explore why collecting more data does not necessarily improve clinical insight. Learn how marginal relevance, duplication and inconsistent standards can increase downstream friction, consume resources and make meaningful signals harder to identify.
• Four Tests for Every Data Source
Leave with a practical framework for assessing clinical data and collection methods. Data should be directly relevant to the protocol, nonduplicative, reliable and capable of enhancing downstream processes.
• Move Beyond EDC Without Leaving Control Behind
Understand why Beyond EDC does not require the immediate removal of EDC. The webinar will explain how sponsors can reduce sole reliance on EDC while creating a more connected, digital-first model for collection, review, monitoring and analytics.
• Turn Connected Data Into Predictive Decisions
Discover how integrated patient and operational data can support earlier insight, faster course correction and more continuous decision-making across the study lifecycle. Attendees will also understand why a trusted, connected data foundation is essential to responsible AI-enabled acceleration.

Speakers:

Sabrina Steffen, Head of Clinical Data Management, IQVIA
Christina Lentz Larsen, Head of Data Ecosystem Transformation, IQVIA