Clinical trials are integral to the safe and efficient delivery of new pharmaceuticals. But this part of the development process comes with many unique challenges. Participants need to be carefully monitored for adverse impacts, disparate teams need easy access to the vast quantities of data that trials generate, and that data—often being collected from a number of different sources—needs to be reliable and high quality.
This is important not only for the outcome of the trial, but also for the work experience of the clinicians, data scientists, and others who are responsible for it.
An inefficient system wastes time and resources, can diminish morale, and ultimately hinders efforts to bring life-saving drugs to market.
Envisioning a Bold, New Clinical Trial Data Collaboration Solution
Our client, a top-five pharmaceutical leader, needed an overhaul of its legacy systems to improve efficiency, enhance collaboration, and accelerate development timelines.
Tasked with collaborating on trials and delivering groundbreaking innovations to market, the client’s teams struggled to collaborate or to rapidly make important decisions based on incoming clinical trial data across its multiple aging platforms. Costly, manual, and cumbersome to maintain, the current way of working stifled efficiency and innovation, hindering the progress of these important teams.
We Shared Our Client’s Vision For a Smarter, Faster Way of Working
Our client needed a solution that could integrate disparate data sources seamlessly into a robust and intuitive environment. This new environment needed to empower clinicians with machine intelligence to enhance data cleaning, review, and analysis—all while streamlining processes and improving communication among development teams.
Our vision was of a powerful and collaborative environment that would provide a near-real-time source of truth for collaborative clinical data review and discrepancy management. With this in mind, we developed a product-driven, platform-agnostic solution that ingested data from 13 sources and included bi-directional EDC integration and multiple AI models.
A Transformative Clinical Trial Data Environment That Accelerates Progress
The results were transformative. Our solution centralizes the clinical data review process to facilitate seamless collaboration and enable real-time analytics for critical decision making, and with the new platform, the client is able to proactively identify and respond to clinical trial challenges, scale productivity, and deliver innovative drugs and therapies to market faster.
A Solution That Accelerates Innovation and Helps Save Lives
- With both pre-built and customizable views and reports, the platform provides a robust and intuitive user experience for clinical review staff, that, in combination with machine intelligence, allows for enhanced data cleaning, review, and analysis.
- Automation allows developers to more quickly and easily identify and fix issues, and continuous integration and deployment has meant faster development and easy, hassle-free scalability.
- Built-in AI further boosts the speed and quality of collaboration, proactively identifying outliers, patterns, and signals to enable the clinical team to make important decisions faster.
For our client, the solution we developed has fundamentally improved the clinical collaboration and review process, increased efficiency, and accelerated delivery timelines for vital pharmaceutical innovations that ease and extend patients’ quality of life.
A True Partner In Innovation
As a leading life sciences consulting firm, we were uniquely positioned to guide our client through this critical initiative. Our deep understanding of clinical trial processes, data management, and platforms proved instrumental in delivering a solution that met—and exceeded—expectations. As we look to the future, we remain committed to driving positive change in the pharmaceutical industry, one groundbreaking solution at a time.
Want to know more about our approach to clinical trial data collaboration? Check out our guide on the subject.
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