Challenges with Clinical Data Management: Findings by Tufts

This video provides an in-depth exploration of the challenges and opportunities in clinical data management, drawing upon findings from a recent Tufts University study commissioned by Veeva Systems. Richard Young, Vice President of Vault EDC at Veeva Systems, discusses the evolving landscape of electronic data capture (EDC) and the increasing complexity of clinical trials. The core purpose of the study was to examine current and evolving EDC and clinical data usage practices across drug development, specifically questioning whether traditional systems are still fit for purpose given the growing demands of data collection, management, and reporting. The study surveyed over 250 senior industry professionals with an average of 20 years of experience, aiming to surface current and future challenges in the field.

Young highlights a critical issue with the term "EDC" itself, noting that traditional EDC systems, often built in the 1990s, primarily function as electronic case report forms (eCRFs), capturing only 20-30% of the total study data. This leaves a vast amount of diverse data—such as lab data, biomarkers, PK data, and increasingly, millions of data points from mobile health devices like Fitbits and Garmins—unmanaged by these systems. He introduces a four-stage framework for data management: "design, collect, decide, and act." The challenges users face stem from the inability of outdated systems to support designing the trial one truly wants to run, collecting all necessary data types, making confident and timely decisions based on comprehensive data, and acting effectively on those decisions amidst growing project complexity.

A key finding from the Tufts research reveals a strong correlation between the initial stages of a clinical trial and subsequent delays. The study demonstrated that delays in building the study database directly lead to longer data entry times and slower database lock times. This insight underscores the principle that "if you start behind, you never catch up," emphasizing the critical need for upfront efficiency and robust preparation. Young further discusses the "four V's" of clinical data management—Volume, Variety, Velocity, and Veracity—which collectively lead to the "fifth V," Value. He stresses that the sheer volume of data, its diverse formats, the demand for real-time access, and the understanding that not every data point requires absolute perfection (veracity, focusing resources on critical data) are paramount considerations for modern data management strategies. Veeva's proposed solution is a unified, "true platform" that seamlessly consolidates data, content, and workflows, addressing the industry's current reliance on over 160 disparate systems.

Key Takeaways:

• Outdated EDC Systems: Traditional Electronic Data Capture (EDC) systems, often developed in the 1990s, are no longer fit for purpose. They primarily function as electronic forms, capturing only 20-30% of total clinical study data and failing to manage the growing volume and variety of modern data sources.
• Expanding Data Landscape: Clinical trials now involve a vast array of data beyond traditional eCRFs, including lab data, biomarkers, PK data, and millions of data points from mobile health devices (e.g., Fitbits, Garmins). Current systems struggle to integrate and manage this diverse and high-volume data.
• The "Design, Collect, Decide, Act" Framework: Effective data management can be broken down into four critical stages: designing the trial without technological limitations, collecting all types of relevant data, making confident and timely decisions based on comprehensive data, and acting decisively on those insights.
• Correlation of Early Delays to Later Inefficiencies: The Tufts study revealed a direct and perfect correlation: delays in building the study database significantly prolong data entry times and slow down database lock. This highlights the critical importance of upfront planning and efficient setup.
• "If You Start Behind, You Never Catch Up": This powerful insight from the research emphasizes that initial project delays create a cascading effect, leading to persistent inefficiencies throughout the clinical trial lifecycle. Proactive and timely execution in early phases is crucial.
• The Four V's of Clinical Data: Modern clinical data management must contend with: Volume (exponential growth, e.g., billions of data points per patient from mobile health), Variety (diverse data types and formats), Velocity (demand for real-time access and processing), and Veracity (strategic focus on the most important data points, acknowledging that not all data requires absolute perfection).
• Achieving Data Value: By effectively managing the four V's, organizations can unlock the "fifth V"—Value. The goal is to ensure systems help identify the true value of data to drive better decisions, primarily concerning patient safety and efficacy.
• Industry's System Fragmentation: A major challenge in pharma is the use of numerous disparate systems (some companies use over 160 systems for data management, clinical, and statistical work), leading to inefficiencies, data silos, and integration complexities.
• Need for a Unified Platform: The vision for the future of clinical data management involves a unified, "true platform" capable of managing all data, content, and workflows concurrently and seamlessly. Such a platform would enable data flow to all consumers and contributors without delay, driving actions and informing decisions.
• Seamless Consolidation: A unified platform should facilitate the seamless consolidation not just of structured data, but also unstructured data (e.g., Twitter feeds), content (documentation), and workflows. This integration is essential for comprehensive oversight and operational efficiency.

Tools/Resources Mentioned:

• Veeva Systems Inc: The company that commissioned the Tufts study and whose Vice President of Vault EDC was the speaker. Veeva is presented as a leader in cloud-based software for the global life sciences industry, advocating for a unified platform approach.
• Tufts University: Specifically, Tufts Center for the Study of Drug Development (CSDD), which conducted the research study on clinical data management and EDC practices.
• EDC (Electronic Data Capture): The primary technology discussed, though the video highlights its limitations in its traditional form.
• Mobile Health Devices (Fitbits, Garmins): Mentioned as examples of sources generating massive volumes of new clinical data.

Key Concepts:

• eClinical Landscape: Refers to the ecosystem of electronic systems and processes used in clinical trials, including EDC, clinical trial management systems (CTMS), and other data management tools.
• Database Build Delays: The time taken to set up and validate the study database before patient enrollment, identified as a critical factor impacting subsequent trial timelines.
• Data Entry Cycle Times: The duration from patient visit to the transcription of data into the EDC system.
• Database Lock: The final stage of data management where the clinical database is finalized and locked for analysis, a key milestone in trial completion.
• Four V's of Data (Volume, Variety, Velocity, Veracity): A framework used to characterize the challenges and requirements of managing big data, applied here specifically to clinical data.
  • Volume: The sheer amount of data being generated.
  • Variety: The different types and formats of data.
  • Velocity: The speed at which data is generated, processed, and accessed.
  • Veracity: The quality, accuracy, and trustworthiness of the data, with an emphasis on strategically focusing resources on the most critical data points rather than striving for absolute perfection across all.
• Unified Platform: A single, integrated software solution designed to manage all aspects of data, content, and workflows across an enterprise, contrasting with fragmented, bolted-together systems.