Episode 2. What Should be in Your Digital Trial Toolkit?

This video provides an in-depth exploration of the evolution of clinical data management and the essential components of a "digital trial toolkit," featuring a discussion between Richard Young, VP of Vault CDMS Strategy at Veeva, and Tanya du Plessis, Chief Data Strategist and Solutions Officer at Bioforum the Data Masters, a data-focused CRO. The discussion centers on the dramatic shift from traditional, paper-based, linear clinical trial processes to modern, digital, and patient-centric approaches. It highlights how changing regulations and technological advancements are propelling data managers from administrative roles to central, strategic positions within clinical operations.

The conversation begins by contrasting the "old days" of data management, characterized by extensive paper pushing, manual tracking, and administrative tasks, with the current landscape where data managers are expected to leverage insights and knowledge to ensure data quality and integrity. Tanya du Plessis recounts her early career, describing the role as akin to a "data librarian" or "data police," focused on documenting and validating physical records. This historical context sets the stage for understanding the profound transformation, driven by the increasing complexity of study designs, the need for speed, and the sheer volume and veracity of data in multi-dimensional trials. The speakers emphasize that a linear approach to data management is no longer viable in an adaptive and rapidly evolving clinical trial environment.

A significant portion of the discussion addresses the impact of digital and decentralized trials, accelerated by factors like the COVID-19 pandemic and the broader digitization of everyday life. The speakers underscore that patients no longer want to fill out paper forms, pushing the industry towards patient-centric digital solutions. For mid-market CROs and smaller companies, this transition presents challenges related to resource limitations, budget constraints, and the complexity of managing multiple technology vendors. The video highlights the critical role of technology partnerships, such as Bioforum's collaboration with Veeva, in streamlining operations and achieving significant efficiencies, citing a 70% efficiency gain in managing protocol amendments as a key example. The dialogue concludes with a forward-looking perspective, stressing the need for data managers to embrace their new, more influential role at the table from the study design phase, rather than being brought in later, and advocating for greater automation of repetitive tasks to unlock their strategic potential.

Key Takeaways:

• Transformative Shift in Data Management: Clinical data management has evolved from a largely administrative, paper-pushing role to a highly analytical and strategic function focused on data quality, integrity, and insights. Early roles involved physical tracking and validation of paper, while modern roles demand critical thinking and data interpretation.
• Data Managers as Strategic Contributors: The role of data managers is moving from "librarians" or "data police" to essential contributors who influence study design and ensure data veracity. They are now expected to contribute at a high level to the quality of data at the end of a trial.
• Impact of Regulatory Changes (E8): Regulations, specifically ICH E8, are actively forcing data management to the forefront of clinical trial design. Data management teams are now explicitly required to be involved from the study design phase, not just before database build, necessitating a proactive and integrated approach.
• Necessity of Digital Trials: The industry is being compelled to adopt digital and decentralized trial models due to factors like the COVID-19 pandemic, the general digitization of society, and the imperative for patient-centricity. Paper-based processes are seen as anchors that hinder flexibility and efficiency.
• Challenges for Mid-Market CROs: Smaller and mid-sized companies often face significant hurdles in adopting digital solutions due to limited resources, budget constraints, and the complexity of integrating multiple vendors for various trial components (e.g., patient diaries, EDC, RTSM).
• Critical Role of Technology Partnerships: Partnering with the right technology vendors is crucial for companies, especially mid-market CROs, to navigate the complexities of digital trials, achieve operational efficiency, and bridge resource gaps. These partnerships enable companies to be smart and clever in their approach.
• Efficiency Gains through Technology: Strategic technology adoption can lead to substantial efficiency improvements. Bioforum, for instance, achieved a 70% increase in efficiency in managing protocol amendments by partnering with Veeva, highlighting the tangible benefits of integrated solutions.
• End-to-End Data Vision: There is a critical need for an end-to-end perspective on data, from initial study design (including considerations like SCTM packages) through to final analysis. This holistic view ensures consistent data structure, quality, and integrity across all data sources, including often-overlooked data like RTSM.
• Focus on Data Veracity: Beyond simply ensuring data is error-free, the concept of "veracity" is paramount. This involves understanding the truthfulness, accuracy, and context of data, especially given the diverse and complex data streams in modern multi-dimensional trials.
• Upskilling and Re-skilling Workforce: Data management teams need to be upskilled and retrained to meet the demands of the evolving landscape. Hiring should prioritize analytical capabilities, critical thinking, and the ability to dive into data, rather than traditional administrative skills.
• Automation of Repetitive Tasks: While AI and ML offer advanced capabilities, there's a foundational need for automation of basic, repetitive tasks such as the creation of statistical listings, reports, and patient profiles. Automating these "human-influenced" tasks frees data managers for higher-value, analytical work.
• Avoiding "Blanket Cleaning": Regulatory guidance is moving away from the need for "a thousand data checks" or "blanket cleaning." Instead, the focus is shifting towards more targeted and insightful data quality approaches, requiring data managers to think differently about data review.
• Embrace the Seat at the Table: Data managers are encouraged to actively embrace their newfound invitation to the study design table. They must overcome traditional shyness and contribute their expertise from the outset to make clinical trials more effective and improve patient- and site-centricity.

Tools/Resources Mentioned:

• Veeva's Vault CDMS: Clinical Data Management System, a product from Veeva Systems Inc.
• SCDM: Society for Clinical Data Management, an organization involved in setting standards and discussions around data management.
• E8 (ICH E8 Guideline): An ICH guideline related to general considerations for clinical studies, specifically mentioned for its implications on data management's role in study design.
• EDC (Electronic Data Capture): A system for collecting clinical trial data in electronic format.
• RTSM (Randomization and Trial Supply Management): Systems used for managing patient randomization and drug supply in clinical trials.

Key Concepts:

• Digital Trials: Clinical trials that leverage digital technologies for various aspects, from data collection to patient engagement.
• Decentralized Trials: Trials where some or all trial-related activities occur at participants' homes or local facilities rather than centralized sites, often enabled by digital tools.
• Patient-Centricity: Designing and conducting clinical trials with the patient's needs and experiences at the forefront, aiming to reduce burden and improve engagement.
• Data Veracity: The truthfulness, accuracy, and reliability of data, especially important in complex, multi-source clinical trials.
• End-to-End Data Vision: A holistic approach to data management that considers the entire data lifecycle, from initial collection and structuring to final analysis and reporting.
• Rolling Locks: A modern approach to database lock where portions of the database are locked incrementally as data becomes clean, rather than a single, final lock at the end of the study.
• Protocol Amendments: Changes made to an approved clinical trial protocol during the course of a study, often a complex and resource-intensive process.
• SCTM (Standard for Clinical Trial Metadata/Terminology): Likely refers to CDISC (Clinical Data Interchange Standards Consortium) standards, which provide a framework for organizing and exchanging clinical trial data.

Examples/Case Studies:

• Bioforum's experience with Veeva's technology led to a 70% efficiency gain in managing protocol amendments, demonstrating the direct business impact of strategic technology partnerships.
• The historical contrast of data management involved "yellow sticky notes and green pins" for QCing paper documents and "faxing back DCFs (data discrepancy forms)" to sites, illustrating the administrative burden of past methods.