Study delays due to growing clinical trial complexity and increasing volumes of data are being experienced more and more often by the clinical research industry. This means that sponsors and their development partners must look to more efficiently manage the performance of their clinical trials, and ensure they employ systems and processes to support faster clinical trial delivery and better decision making.
Managing large amounts of data being generated is one of the challenges of any clinical trial. Clinical trials often have data residing in multiple systems and databases including EDC, CTMS, CDMS, safety databases and others, and without a centralized approach, such databases can also be spread across multiple vendors and countries. This means data managers and other clinical staff become progressively polyvalent and proficient at managing data complexity. But these factors also increase the pressure on data managers trying to keep database locks on time.
Optimizing the capture and management of clinical trial data is now more important than ever in ensuring the success of any clinical trial. Consequently, the choice of software used for data capture plays a central role in ensuring the quality, accuracy and reliability of data. This software should ideally not just support the optimal collection of data but also proper management of the data. Sponsors and their partners, therefore, need a solution that helps them integrate and exchange clinical trial data in an integrated way, which gives them actionable views of the data at any point in the trial in real-time.
A number of new "eClinical"ť technologies are emerging with many new functionalities to improve and simplify the overall architecture of clinical trial data collection, management and analysis. These advancements in technology are already having a positive impact throughout the clinical and data management process by enhancing the quality and completeness of the data, and increasing the speed and efficiency of its capture and management. However, despite helping to speed some aspects of the trial process, the use of these different technologies often present significant challenges regarding efficient integrations and cross-platform functionality. Another challenge also lies in how quickly sponsors can collate and review data coming from different sources to inform their key business decisions. To address these challenges, a single system approach is required that can translate large volumes of any data and visualize it in a clear and insightful way. Both these attributes help speed key development decisions and enable sponsors to optimize their drug development plan for their compound.
The advent of cloud based technology is already proving to be well-suited to these challenges and provides the scalability and flexibility that is not available through the older traditional software models. Cloud-based technology, of course, is not new. But encapsia™, Cmed's clinical data suite of apps designed for data capture and clinical trial management leading to effective reporting, is the first cloud-hosted clinical data suite that has been specifically designed to take full advantage of being cloud hosted, and offers the solutions needed to address the current clinical and data management challenges.
Real-time, interactive visualizations of clinical data
It is important for sponsors and CROs to be able to combine, centralize and distribute clinical trial data in an accurate, quick and clever way, and make sense of the data collected. Cmed has developed encapsia™ to do just this.
encapsia™ enables everyone involved in running clinical trials to be able to quickly generate meaningful visualizations of the data, collaborate in real-time to both identify gaps and solutions. Fast clinical trial builds, combined with improved data quality, and faster decision making with its live data analytics and insights function, are all available with encapsia™, and all this is actionable within the one system. encapsia™ unifies data processes across multiple functions and streamlines clinical trial conduct by removing disparate point solutions and previously fragmented processes.
Insights is the app in the encapsia™ suite that provides real-time, sophisticated visualizations of the clinical data. These visualizations are not simply images on a screen, but are interactive and actionable real-time representations of the data. Each visualization is displayed within a dashboard that users can customize and adjust in numerous different ways, allowing personalized views of the data for each user. These customized views are also fully actionable, enabling users to drill down to individual data points and raise queries or flag issues for follow-up by the study team.
The Insights app really helps users to see and understand clinical trial data more clearly both close up and taking a big picture view. These two views help users to both fully understand each data point and see trends and outliers, leading to cleaner, higher quality clinical trial data.
The Analytics app is another powerful tool in the encapsia™ suite, from which data scientists can benefit from secure, real-time access to all encapsia™ data and metadata. The Analytics app supports multiple third-party programming environments and data interrogation.
The use of these analytics means users can create sophisticated programs with defined conditions which continuously check incoming data and automatically flag items for review when the conditions specified in the programs are satisfied. These live analytics allow users to take advantage of encapsia™'s complete audit trail while the real-time visibility of key data enables better, faster decisions and efficient clinical trial development.
In this webinar, speakers will demonstrate live the power of real-time clinical data insights and analytics, and what this means for clinical trial conduct and for clinical trial management activities. This webinar will also address the following questions, amongst others:
Keywords: Clinical Trials, Analytics
- How is data utilized to support the effective management of clinical trials?
- How can the data be reviewed expediently and also have a purpose for the reviewer?
- Do we get too close to the data which stops us identifying potential issues?