Modern clinical trials continue to increase in complexity, with an expanding array of high-volume and high-velocity data coming from a wide array of sources, including decentralized clinical trial (DCTs), adaptive designs, use of real-world evidence, sensors, and more.
A recent estimate indicates that data points collected in Phase III trials have increased threefold in the last 10 years, reaching an average of 3.6 million (Tufts CSDD, 2021). This trend will undoubtedly continue, with 70% of trials expected to incorporate digital health technologies (DHTs)—including high-volume and high-velocity wearables and sensors—in the next few years (Myshko, 2019).
Many of these data streams now come from sources outside of electronic case report forms (eCRFs) and are increasingly managed outside of electronic data capture (EDC) systems (Zozus, 2021; Wilkinson, 2019), which further compounds the issue trial data silos.
This has created significant data management challenges, as traditional clinical data management technologies and manual processes to review, clean, and lock data have not progressed as fast. Data is often managed with tools and processes that are not able to work at the speed required to support the realities of today’s clinical trials. As clinical trials become more digital, sponsors and contract research organizations (CROs) are turning towards Clinical Data Management Systems (CDMS) to collect, validate, and transform their data across the lifecycle of a trial, including study design, planning, conduct, closeout, and post-trial analysis.
Given this context, Medidata sought to better understand how small, medium, and large biopharmaceutical companies are managing their data in this complex environment and gain their perspectives on what they are looking for in a CDMS that handles study design, planning, execution, analysis, and submission. Medidata commissioned a survey of 102 buyers and users of clinical data management tools, including managers through C-suite executives, and spanning a wide range of roles, including clinical operations, data management, data science, therapeutic area heads, and information technology (IT).
The survey asked participants about their current pain points, current CDMS solutions, and features/functionalities they desire in a future CDMS. While the study identified a few notable differences between large and small to medium companies, for the most part, all companies, no matter their size, are facing similar challenges and seeking similar solutions. The overarching conclusion from the data is that buyers and users have big pain points with data integration, largely driven by increasing trial complexity and the concurrent surge in data volume. Respondents also indicated that they are not yet seeking more advanced features, such as search, semantic layers, and metadata management.
This white paper discusses the key results of this survey.