Episode 3. Will Traditional EDC Exist Ten Years From Now?

This video provides an insightful discussion on the evolving landscape of Electronic Data Capture (EDC) and clinical trial technology, featuring Richard Young, VP of Vault CDMS Strategy at Veeva, and Doug Bain, Chief Technology Officer at KCR, a Contract Research Organization (CRO). The central theme revolves around the diminishing relevance of traditional EDC systems, which often still mirror paper-based Case Report Forms (CRFs), and the imperative for the pharmaceutical industry to embrace more integrated, platform-based digital solutions. The conversation highlights that only a fraction of clinical trial data now originates from traditional EDC, prompting a critical examination of its future and the tangible opportunities presented by truly digital clinical trials to alleviate burdens on sites and patients.

The discussion progresses from a historical perspective, tracing the journey from paper-based trials in the 1980s to the advent of EDC, acknowledging that while EDC was a significant step, it hasn't fully realized its potential. Doug Bain argues for a radical simplification of clinical trial technology, moving away from a "best of breed" approach that has led to an "avalanche of systems" and frustrated sites. He champions platform-based solutions, exemplified by Veeva, which can integrate various functionalities and inherently improve over time, eventually becoming "best of breed" across all verticals without compromise. This shift is crucial for enhancing efficiency and transparency in clinical operations.

Furthermore, the video delves into the changing role of data managers, envisioning them with a broader scope encompassing the entire data lifecycle, from study build to reporting and data administration, rather than just data cleaning. The speakers advocate for process automation, where Sops are embedded into intelligent systems that guide and govern the clinical trial lifecycle, moving beyond static documents. The conversation also addresses the "buzzword" of decentralized clinical trials (DCTs), emphasizing that true decentralization requires a protocol-level design and a flexible "toolkit" approach to patient participation, rather than retrofitting traditional protocols. The ultimate goal is to achieve genuine site and patient centricity by listening to their needs, simplifying their interactions with technology, and providing value back to patients through user-friendly applications.

Key Takeaways:

• EDC's Evolving Role: Traditional Electronic Data Capture (EDC) systems, often still a digital representation of paper CRFs, are becoming less central as only a fraction of clinical trial data now originates from them. The industry needs to move beyond this legacy definition of data capture.
• Simplification through Platforms: The current "best of breed" approach has led to an overly complex ecosystem of disparate systems, causing inefficiency and site burden. A shift towards integrated, platform-based solutions (like Veeva) is essential to simplify operations and enhance overall capability.
• Veeva as a Platform Leader: The discussion positions Veeva as a prime example of a platform developer that is building layers of functionality, suggesting that such platforms will eventually become "best of breed" across all clinical trial verticals, eliminating the need for compromises.
• Expanded Role for Data Managers: The future of data management involves a broader scope, moving beyond mere data cleaning to encompass the entire data lifecycle, from initial study design and data definition to reporting and administration, effectively bridging silos between different functions.
• Process Automation and Intelligent Systems: Instead of relying on static Standard Operating Procedures (SOPs), the vision is for intelligent, system-defined processes that guide and govern the clinical trial lifecycle, effectively teaching the computer the trial's workflow and automating oversight.
• Designing for Digital/Decentralized Trials: Decentralized Clinical Trials (DCTs) should not be an afterthought but integrated into the protocol design from day one. A "toolkit" approach is needed to offer patient-specific flexibility, especially for vulnerable populations, rather than enforcing rigid visit schedules.
• True Site and Patient Centricity: Achieving site and patient centricity requires actively listening to their frustrations (e.g., using multiple, disconnected systems) and designing technology that genuinely supports their needs, making their jobs easier and providing value back to patients.
• Eliminating "Paper Thinking": The industry must move beyond the misconception that scanning paper documents into PDFs constitutes "digital." True digital transformation involves replacing all paper-based processes with rich, electronic forms that allow data to be surfaced, cleaned, and checked effectively.
• Holistic Data Definition and Transparency: A more holistic definition of data is needed, moving away from silos to a continuous loop of understanding data needs, capture mechanisms, and how data is manifested to different stakeholders (e.g., medical monitors, data managers) in a useful, transparent way.
• Regulatory Catalysts for Change: Regulatory bodies, such as those behind E8 guidelines, are increasingly emphasizing early data management involvement. There's an opportunity for regulators to drive innovation, for example, by mandating long-term follow-up with conditional approvals, which technology can now support seamlessly.
• Seamless Long-Term Follow-up: Technology can enable continuous long-term follow-up within the same data environment, particularly for vaccine or oncology studies, breaking down the traditional siloing between drug development and post-marketing activities like registries.
• Cloud-Enabled Collaboration: Cloud-based systems will facilitate a future where there is essentially "one trial in one database," allowing all stakeholders, including patients, to collaborate in real-time within the same technology environment, fostering greater efficiency and transparency.

Tools/Resources Mentioned:

• Veeva (specifically Vault CDMS)
• Apple Macintosh (historical context of early clinical trial systems)
• IBM (historical context of CTMS and EDC systems)
• Microsoft Word (cited as an example of an outdated tool for process definition)
• ePRO apps (Electronic Patient-Reported Outcomes applications)

Key Concepts:

• Electronic Data Capture (EDC): Systems designed to collect clinical trial data in an electronic format.
• Case Report Form (CRF): A document (paper or electronic) used in clinical trials to record protocol-required information about a participant.
• Clinical Trial Management System (CTMS): Software that manages and tracks various aspects of clinical trials, from planning to closeout.
• Platform-based Solutions: Integrated software ecosystems that provide a comprehensive suite of functionalities, often built on a common data model, as opposed to disparate "best of breed" systems.
• Digital Clinical Trials: Clinical trials that leverage digital technologies and processes throughout their lifecycle to enhance efficiency, data quality, and patient experience.
• Decentralized Clinical Trials (DCTs): Trials that incorporate virtual elements and allow participants to engage from their homes or local healthcare facilities, reducing the need for frequent site visits.
• Site-centricity: Designing clinical trials and technologies with the needs and workflows of investigator sites in mind to reduce burden and improve efficiency.
• Patient-centricity: Designing clinical trials and technologies with the patient's experience, preferences, and convenience at the forefront, aiming to reduce patient burden and improve engagement.
• Metadata: Data that provides information about other data, crucial for defining and managing clinical trial data holistically.
• Adaptive Clinical Trials: Clinical trials that allow for pre-specified modifications to the trial design based on accumulating data, often requiring real-time data access and analysis.
• Long-term Follow-up (LTFU): The extended monitoring of participants after the primary treatment or study period, often to assess long-term safety or efficacy.
• ePRO (Electronic Patient-Reported Outcomes): The direct capture of patient-reported health information using electronic devices.
• Standard Operating Procedure (SOP): Detailed, written instructions to achieve uniformity of the performance of a specific function.