Episode 7: Is Data Management the Glue of Modern Clinical Trials?

This video provides an in-depth exploration of the evolving role of data management in modern clinical trials, hosted by Richard Young of Veeva Vault CDMS and featuring Luis E. Torres, Head of Clinical Programming FSPx at Labcorp. The discussion centers on how data managers can adapt to the future of clinical trials by embracing new technologies and skills, particularly in the context of decentralized teams. It delves into the historical transformation of data management from paper-based systems to highly technical, integrated roles, emphasizing the need for innovation and problem-solving in an increasingly complex industry.

The conversation highlights the data manager's emerging role as the "glue" that connects various departments, such as biostatistics and programming, leveraging diverse technical skill sets. A central theme is the "Rubik's Cube" analogy, where challenges in clinical trials are viewed as interconnected facets—people, process, and technology—that must be addressed holistically. Luis Torres stresses that solving these challenges requires picking up the cube and focusing on these core elements, acknowledging that changes in one area inevitably impact others. The discussion also touches upon the pressure to accelerate database build times, the importance of end-user involvement in technology adoption, and the evolving standards for data cleanliness.

The speakers further explore the practical implications of these changes for Contract Research Organizations (CROs) like Labcorp. Luis shares Labcorp's strategies, including expanding resource pools globally (e.g., into Costa Rica) and leveraging both homegrown and off-the-shelf systems like Veeva CDMS and CDB. He underscores the critical need for continuous assessment of existing systems and the proactive adoption of new technologies, given their rapid evolution. The dialogue concludes with reflections on the ideal partnership between CROs and technology vendors, emphasizing the value of vendors listening to and incorporating industry experience and recommendations to drive collective progress.

Key Takeaways:

• Evolution of Data Management: Data management has transformed from a paper-intensive, data entry role to a highly technical and integrated function. Early processes were inefficient, requiring dedicated resources to track physical case report forms, a stark contrast to today's digital landscape.
• Data Manager as the "Glue": The modern data manager is becoming a central figure, acting as the "glue" that connects various departments like biostatistics and programming. This role demands a diverse set of technical and programming skills to navigate complex data ecosystems.
• The "Rubik's Cube" of Clinical Trials: Solving the multifaceted challenges in clinical trials requires a holistic approach, focusing on three core "centerpieces": people, process, and technology. Changes in one area inevitably affect the others, necessitating coordinated efforts.
• End-User Driven Technology Adoption: Successful technology implementation hinges on involving end-users, such as data managers, from day one. Excluding them can lead to the adoption of technologies that, while potentially great, are not practical or comfortable for the users, leading to failure (illustrated by the Alexa-Spanglish anecdote).
• Accelerated Database Build Times: The industry faces immense pressure to drastically reduce database build times, from historical 12-week cycles to ambitious goals of two weeks. Achieving this requires constant assessment of internal systems and proactive adoption of new, efficient technologies.
• CROs' Role in Data Quality and Ownership: CROs bear significant responsibility for delivering high-quality, clean data to sponsors. While sponsors own data quality, CROs must take personal ownership of the process to ensure data is "super clean" for downstream processes like SDTM and regulatory submissions.
• Shifting Data Cleanliness Standards: The concept of "perfection" in data cleanliness is evolving. With the explosion of data types and volume, a risk-based approach is becoming more common, focusing on ensuring "super clean" data for critical points rather than reviewing every single data point.
• Importance of Industry Standardization: A significant challenge in the industry is the lack of true standardization, with CROs often navigating multiple sponsor standards, their own SOPs, or hybrid approaches. Efforts by organizations like SCDM to introduce standards and guides are crucial for future efficiency.
• Future of Data Management with AI/ML: The future of data management will heavily involve automation, AI, and machine learning. A desired advancement is the capability for systems and platforms to allow users to query databases using natural language, similar to interacting with AI assistants.
• Strategic Technology Partnerships: Effective partnerships between CROs and technology vendors are vital. Vendors who actively listen to and implement recommendations from CROs—who possess years of diverse sponsor experience—contribute significantly to the advancement of the entire industry.
• Resource Expansion for Talent Challenges: To combat global resource shortages, organizations like Labcorp are expanding their talent pools into new regions (e.g., Costa Rica) to create a larger, more diverse workforce capable of supporting clinical programming and data review needs.
• Configurable Reporting for Data Managers: Data managers need the ability to configure their own ad hoc reports and dashboards without requiring programming assistance. This empowers them to perform data exploration, drill down into specific data, and respond quickly to data requests.

Tools/Resources Mentioned:

• Veeva Vault CDMS: A clinical data management system, specifically mentioned as a technology Labcorp enabled in 2020.
• Veeva CDB: A related Veeva platform, which Labcorp is also heavily involved with.
• Oracle Clinical: A legacy system mentioned as where the guest started their career doing database builds.
• Alexa: Amazon's AI voice assistant, used as an example to illustrate the importance of end-user comfort and language capabilities in technology adoption.
• SCDM (Society for Clinical Data Management): An organization recognized for its efforts in introducing standards and guides for the industry.
• CQL: Mentioned as a query language that the guest sees as a positive direction for natural language querying of databases.

Key Concepts:

• Data Management as "Glue": The idea that data managers serve as a central, connective force within clinical trial operations, bridging different functional areas and technical disciplines.
• Rubik's Cube Analogy: A framework for understanding and addressing complex, interconnected challenges in clinical trials, where "people, process, and technology" are the fundamental sides that must be aligned.
• End-User Driven Technology: The principle that technology development and adoption must be guided by the needs, comfort, and direct involvement of the ultimate users to ensure successful implementation and utility.
• "Super Clean" Data: A modern standard for data quality that moves beyond absolute perfection to a more risk-based approach, focusing on ensuring the highest level of cleanliness for critical data points while acknowledging that not every data point can or needs to be exhaustively reviewed.
• FSP (Functional Service Provider): A business model where a CRO provides specific functional services (like clinical programming) to a sponsor, often integrating into the sponsor's existing processes and standards.

Examples/Case Studies:

• Labcorp's 25 Years in Industry: Luis Torres's extensive experience at Labcorp, spanning from paper-based data entry to modern digital systems, provides a historical perspective on data management evolution.
• Labcorp's Expansion into Latin America (Costa Rica): An example of a strategic move to address resource challenges by expanding the talent pool for programming, data review, and testing, thereby creating a larger pool of resources.
• Veeva CDMS and CDB Enablement: Labcorp's adoption and active involvement with Veeva's clinical data management systems, highlighting a successful CRO-technology vendor partnership.
• Alexa-Spanglish Anecdote: A personal story illustrating how technology, despite its capabilities, can fail if it doesn't meet the specific needs and context (e.g., language) of its end-users.