AI-powered Insights in Clinical Trials | A Medidata NEXT Global Series

Medidata’s annual event series—NEXT Global—brought together leaders from across the life sciences industry, including representatives from Medicenna, Duke University Medical Center, and more, to explore the future of AI-powered technologies in the clinical trial space. We’ve compiled highlights of these discussions below to help define how AI-powered insights are driving clinical trial advancements.

How can breakthrough innovations like the Synthetic Control Arm® (SCA®) de-risk rare disease clinical trials? And how can our industry successfully bridge the gap between clinical trial data and real-world data to optimize patient outcomes? Discover how AI and analytics are being leveraged to transform life sciences.

Accelerating Breakthroughs in Rare Disease Clinical Trials

Rare diseases represent unique and difficult challenges for clinical trials. Many rare cancers, like recurrent glioblastoma (rGBM), lack an effective standard of care treatment. In these instances, patients may be reluctant to enroll in a randomized controlled trial where there is a chance of being assigned to the standard of care arm. Even once enrolled, patients assigned to the control arm may be likely to discontinue early, upon realizing or being informed of their treatment assignment.

These circumstances make it difficult to recruit control arms for studies. As a result, Medidata has developed the Synthetic Control Arm. An SCA utilizes historical data from past patients to create an external control arm to augment or replace the number of patients required to participate in the control group. Artificial intelligence is used to select candidates for the SCA that closely match the patients of the clinical trial being conducted.

In 2020, Medicenna was granted FDA-approval to design a phase III clinical trial for rGBMa using a Synthetic Control Arm—a precedent-setting agreement for the industry. By leveraging the SCA and AI-insights, sponsors can enhance patient trust and participation, reduce costs, and accelerate the pace of rare disease clinical trials. The continued usage of the SCA in trials will contribute to the growth of a larger, synthetic-controlled database over time for more powerful insights.

“We have seen uptake on the approach [SCA], taking place in various different cancers, and we are happy to see that we have triggered a process that we think would be much better for quality in general.”

– Fahar Merchant, President and CEO, Medicenna

AI-Powered Innovations During COVID-19

AI and analytics took center stage to keep trials running during the COVID-19 pandemic. Early on, the virus drove industry-wide disruptions that left companies scrambling to preserve clinical trial enrollment. Sponsors started turning more strongly to data and insights to assess the impact and determine where to focus their efforts—all the way down to the site level. By using a comprehensive data management solution, they were able to access and act on this data in real-time to continue trials and research.

Going forward, the innovations and insights that accelerated COVID trials can support any type of clinical trial. Sponsors will continue to rely on real-time industry data to inform their decision making. These advancements can improve processes throughout all aspects of a clinical trial, including study planning, delivering supplies to patients, and source document verification.

“The whole range of innovations that we needed because of COVID-19, from study planning, using real-time data, getting supplies to patients at home, and other decentralized activities…have vastly improved the way that we can help and work with sponsors, sites, and CROs to execute clinical trials.”

– Stephanie Chamberlain, MD, VP, Business Development, Acorn AI®, Medidata

Using AI to Link Clinical Trial Data with Real-World Data

AI-innovations have allowed us to bridge the experimental world with the real-world. Historically, clinical trial data and real-world data have been in silos separate from one another. Bringing together these datasets can create a never-before-seen view of the patient journey. This is known as longitudinal patient data.

Linked data lets sponsors glean enhanced patient insights for recruiting or baselining to minimize trial delays and future-proof trials. Following the clinical trial, linked data provides a head start in evidence generation and can capture endpoints that were not in the initial trial. These insights can be gained without additional burden to patients. However, it is critical that the proper security and compliance measures are in place to protect patients and their data.

“Linking clinical trial data with real-world data helps sponsors and researchers unlock a new frontier of patient data, furthering science to save lives.”

– Akiko Shimamura, Senior Director, Medidata Link, Medidata

Summary

Artificial intelligence and advanced analytics are at the forefront of clinical trial modernization. Innovations like the Synthetic Control Arm, as well as clinical and real-world data linkage, have paved the way for better insights, faster trials, and increased patient enrollment. While these trends were accelerated out of necessity due to the COVID crisis, they are now positioned to play a prominent role in the future of drug development.

Learn more about the impact of AI and analytics on clinical trials—as told by top industry experts.

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