Introduction
Chapter 1:
A New Era for EDC Implementation
Chapter 2:
Addressing Speed and Efficiency Challenges
Chapter 3:
Handling Complex Trial Requirements
Chapter 4:
Iterative Quality Control
Chapter 5:
Collaboration, Communication, and Flexiblity
Conclusion
1 2 4 6 7 8 9
Against a backdrop of growing trial complexity, with increasing demands for real-time data access and cycle time pressures, an effective and easy-to-use Electronic Data Capture (EDC) system remains a core component of successful clinical research. With the right EDC system in place, clinical researchers hold the potential to enhance the speed and efficiency of data management processes.
Data management professionals are tasked with navigating a complicated ecosystem of digital tools, regulatory requirements, data sources, and collection strategies to drive research forward. This shift necessitates a deeper understanding of how EDC systems can be leveraged to streamline data management processes. This is particularly true in the case of growing trial complexity with innovative trial designs such as master protocols and adaptive approaches, increased numbers of endpoints, and the need to address increasingly common protocol amendments more easily.
On the other hand, delays in setting up and implementing EDC systems can lead to significant setbacks, including prolonged study timelines, increased costs, and missed opportunities for innovation. Therefore, the optimization of an EDC system and data collection strategy are paramount, requiring a balanced approach that accommodates the need for rapid deployment alongside the flexibility to accommodate the evolving needs of modern clinical trials.
Selecting and implementing an EDC system that meets the demands of modern clinical trials requires a strategic approach that emphasizes flexibility, scalability, and integration capabilities. A truly robust EDC build is not a purely technical achievement, rather it relies upon a strong understanding of the clinical research objectives –what does the team want to achieve with the data being collected? By treating the protocol as a guide and aligning the EDC system accordingly, clinical data teams can minimize discrepancies and enhance the overall quality of data collection and analysis. Alongside their technical skills, the clinical programmers building the EDC should be equipped with the clinical domain knowledge to read and translate even the most complex protocols. By providing comprehensive protocol training to programmers, data managers, and the quality control (QC) team, a shared understanding of research objectives may be developed, ensuring that the EDC design is efficient and that it supports collection of the necessary data points. In essence, the protocol serves as the bedrock for constructing the EDC, and ensuring a one-to-one correlation between the protocol and the EDC system is vital to maintaining accuracy and data integrity.
• Streamline communications during the build through consistent personnel assignment and process.
• Begin with the end in mind. Does the data collection answer the research question? Clinically trained database developers and close alignment with statistics groups help here.
• Be flexible. Every study has its unique challenges. Standardization is critical, but meeting the needs of increasingly complex trials often requires flexibility.
• Embed quality through processes, people and technology. Achieving quality while working at speed needs a multi-faceted approach with robust processes, expertise development and deep technology knowledge.
• Build efficiencies through standardization, long-term partnership and innovation. We know that by working in partnership with sponsors, we can achieve up to 60% savings in go-live timelines. These efficiencies are derived from strong partnerships and commitment to standards. Incorporating newer approaches like automation also streamlines delivery and adds value to partners.
Rapid EDC implementation enables clinical trial sponsors to shorten the time from protocol development to study start. The more quickly a team can get their EDC up and running has a significant impact across the study’s entire data life cycle and these incremental gains add up when considered across entire trial portfolios. Certainly, accelerating cycle times is a top priority for data management leadersi with aggressive goals for both First Patient First Visit (FPFV) and database go-live (DBL). By identifying and eliminating bottlenecks, optimizing workflows, and leveraging technology tools, researchers can significantly enhance efficiency without compromising quality. For example, utilizing technology to automate routine set up tasks can help teams build out their casebooks faster, and freeing team members up from these tasks allows them to focus on more strategic study build needs, making the entire process more efficient.
Additionally, cloud-based EDC solutions provide unprecedented scalability and flexibility, allowing for the efficient management of large datasets and facilitating seamless collaboration among global research teams. This technological ecosystem not only optimizes data management processes for highly complex study designs, but also empowers clinical trial stakeholders to harness the full potential of their data.
Standardization, also, is vital to ensuring both data quality and EDC build speed. This focus on standardization extends beyond casebook consistency from one study to the next, but also in the context of wider build activities, validations, documentation, and review cycles. Through standardization, review cycles for subsequent EDC builds will be shortened and the overall database roll out can be achieved more efficiently. In all, embracing agile methodologies and adopting innovative approaches can result in faster and more efficient research outcomes.
i Agrawal, G., Keane, H., Parry, B., Sartori, V., Kautzky, J., & Silverstein, A. (2024, January 22). Accelerating clinical trials to improve biopharma R&D productivity. McKinsey & Company. https://www.mckinsey.com/industries/life-sciences/ our-insights/accelerating-clinical-trials-to-improve-biopharma-r-and-d-productivity
The shift towards more complex clinical trial designs, such as adaptive study designs and master protocols, inherently necessitates a higher degree of flexibility and sophistication from EDC solutions. This evolution is underscored by a notable uptick in the number of trial endpoints, with pivotal trials witnessing a 69% increase in total endpoints (from an average of 13 to 22) between 2010 and 2020.ii Three-quarters (75%) of trial protocols necessitate at least one substantial amendment, alongside a 60% increase in the mean number of protocol amendments per study, escalating from an average of 2.1 to 3.3.iii These dynamics underscore the critical need for both deep clinical knowledge and flexible, tailored EDC builds capable of accommodating these intricate trial designs.
Addressing these challenges requires a shift in how we approach EDC builds. Incorporating statistical input upfront in the design of EDC systems can help researchers determine the right data collection strategies and enhance data quality. Further, adopting agile design approaches is essential to effectively manage and swiftly accommodate protocol amendments. This adaptability, complemented by internal and external team members with the expertise and skill to execute these modifications quickly, is essential to navigating the complexities of modern clinical trials.
As an example of a successful implementation, the eClinical Solutions team worked with a client to make improvements that would enable faster EDC builds for its entire portfolio of complex studies. The eClinical Solutions team developed an innovative and proprietary approach which allowed the master protocol to be incorporated within a single database and streamline its structure – effectively building multiple studies in one, drastically accelerating the study build process. The team also used automation to reduce the burden of repeatable manual tasks commonly involved in the study build process, resulting in additional time savings.
ii Getz, K. (2023, October) New Strategies to Optimize the Vendor Selection Process, presented at Clinical Operations Retreat for Executives (CORE) East Conference.
iii Getz, K., Smith, Z., Botto, E., Murphy, E., Dauchy A. New Benchmarks on Protocol Amendment Practices, Trends and their Impact on Clinical Trial Performance. Ther Innov Regul Sci. 2024 Mar 4. doi: 10.1007/s43441-024-00622-9. Epub ahead of print. PMID: 38438658.
To make sure that the EDC will be able to meet objectives for speed, efficiency, and complex data management, it is a best practice to include a comprehensive approach to QC. For example, the eClinical Solutions’ QC team works closely with the clinical programming team to implement an iterative QC process across all deliverables and minimize errors. The QC team, like the clinical programming team, also need to understand the different nuances of the protocol, including data collection points and cohorts so they may ask the right questions and proactively review validation checks and/or identify discrepancies.
Involving the QC team at every step of the build process allows for early identification and resolution of potential issues, ensuring high-quality outcomes. This iterative approach also enables ongoing refinement and optimization, resulting in improved efficiency. To ensure oversight, compliance, and documentation quality, implementing quality gates at pivotal milestones throughout the build process (think, checkpoints), allows for meticulous review and verification of documentation, ensuring all necessary requirements are met. These quality checkpoints also enable teams to remain audit-ready and promptly resolve any documentation issues.
Active engagement and open communication among all stakeholders, both internal and external, are fundamental drivers of efficiency in clinical research. Effective collaboration ensures alignment with research objectives and reduces the likelihood of miscommunications or delays. Prioritizing soft skills within clinical programming teams alongside technical expertise enables teams to work together more seamlessly and efficiently. Regular checkins, status updates, and collaborative problem-solving cultivate a sense of collective responsibility and open accountability, driving the EDC implementation project towards success.
It isn’t uncommon for issues to pop up during an EDC build, especially in the context of growing complexity already discussed. Even the best-planned and executed initiatives experience occasional roadblocks. This is why it helps to choose partners that understand these realities and can pivot with internal research teams to reach common goals. For example, being open to accommodating split releases, if necessary, is a useful tool that leaders can deploy to help meet aggressive First patient in (FPI) timelines. This flexibility allows for adjustments based on evolving protocol needs, ensuring progress continues without unnecessary delays. By prioritizing agility and adaptability, internal and external teams can work as one to maintain momentum and successfully meet timelines.
As clinical trials continue to grow more complex and nuanced, advanced EDC systems built to handle the needs of modern clinical trials, particularly the needs to move quickly, produce quality data, and handle complex data requirements become critically important. These solutions can empower clinical trial data management professionals with the tools needed to navigate the complexities of modern research, from handling data proliferation, to enabling a seamless experience for sites. However, optimizing the speed and efficiency of EDC systems is not merely about operational improvement; it’s about developing an EDC to represent a strategic advantage that can significantly affect clinical trial success.
From accelerating patient enrollment to ensuring compliance and enhancing decision-making, there are many benefits of investment in efficient EDC set-up. The strategic implementation of these systems not only enhances the efficiency and quality of data management processes but also enables research sponsors to stay at the forefront of scientific discovery. By fostering a culture of innovation and adopting flexible, scalable EDC solutions, we can effectively address the challenges of today’s trials while paving the way for future advancements.
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eClinical Solutions’ industry-leading data and analytics platform and biometrics services experts help biopharma researchers at large, mid-size, and emerging life sciences organizations manage trial complexity in less time and with fewer resources. Clients get accurate and timely data insights for better decisionmaking –– enabling them to reduce cycle times, improve productivity, easily scale and develop tomorrow’s breakthroughs with today’s resources.
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