What’s Driving the Adoption of Clinical Trial to Real-world Data Linkage?

The clinical trial landscape has become increasingly complex, resulting in fewer study starts, longer approval timelines, and greater budget cuts—ultimately challenging organizations to do more with less. Discover why sponsors are adopting data linkage to tackle the challenges of longer timelines, complex trials, and high costs in clinical development—and learn how linking clinical trial data (CTD) to real-world data (RWD) is helping to bridge evidence gaps and could become the new standard for more successful and efficient clinical trials. 

We sat down with Ana Fernández Oromendia, VP, Evidence Generation, Medidata, to discuss why organizations are turning to data linkage to help tackle some of these issues and accelerate clinical development. 

Q: Can you provide insight into why we’re seeing a recent uptick in the adoption of data linkage?

Ana: The clinical development landscape has become increasingly challenging in recent years as the need for more precise and targeted therapies emerge. Additionally, to bring a new therapy to market, regulators and payors are requiring increasingly robust and nuanced evidence for comparative safety, efficacy, and cost effectiveness. This has resulted in longer and costlier clinical trials, and has placed additional burden on patients and sponsors. 

By linking CTD to RWD, we can now generate insights that wouldn’t be possible from either dataset alone. We also have the technology solutions, data ecosystems, and regulatory guidance that allow RWD linkage to seamlessly become part of a clinical trial without adding extra layers of challenge and complexity. This means we can generate longitudinal patient datasets, without going outside of existing workflows and adding burden to patients and sites. 

Q: Do you see data linkage becoming a new norm in clinical research? 

Ana: When you link CTD to RWD, you can more holistically describe a patient’s health trajectory, characteristics, and outcomes—helping sponsors close critical gaps in evidence generation. This offers a tremendous competitive advantage to your trial as you look to make the cases to payors and regulators about the safety and effectiveness of your novel therapy; we see many sponsors using linkage capabilities for these reasons. Additionally, many others are at least putting the patient consent language and technology in place up front. This way, if they uncover evidence gaps later on, they can turn on data linkage to get additional insights without burdening patients or adding time and costs to the trial.

Q: Are there specific applications for linked datasets that you’re seeing sponsors gravitate towards to fill evidence gaps?

Ana: There are many applications for linked datasets, but there are a few specific ones where sponsors are seeing extra value. The first—understanding healthcare resource utilization and label expansion—immediately comes to mind, since data linkage gives teams a more complete understanding of real-world outcomes. Additionally, because linkage allows you to passively collect longitudinal data on participants' health journeys, many teams use linkage to augment long-term follow-up data, or even to continue to capture insights on patients that have been lost to follow-up.

This is helpful for all trials, but especially for conditions or treatments that require long follow-up periods, like CAR-T therapy and other cell and gene therapies. One use case that surprised us, and continues to add value to many sponsors, is the identification of professional patients—patients who enroll multiple times in the same trial—whose data may confound a trial’s results and threaten its integrity. 

Q: What are some of the data types that you’re seeing be leveraged by sponsors when linking? 

Ana: Working with our ecosystem partners, the whole spectrum of RWD can be linked to clinical trial datasets. The ones selected very much depend on the analytical question being answered, the nature of study outcomes, and the trial population. For example, some sponsors are interested in a patient's insurance claims data to better understand their healthcare resource utilization and cost of care. Others are interested in EHR data, as it provides more granularity on clinical variables and measurements when they want to look at or adjust for specific clinical outcomes.

Q: How are regulators viewing these capabilities?

Ana: Regulators encourage the use of RWD in clinical research to fill evidence gaps and increase efficiency of clinical trials and have issued very useful guidance on how and where it can be best applied¹. There’s a growing consensus that trials can gain additional valuable evidence on trial patients' outcomes if they can retrieve their diagnoses, procedural codes, and insurance payment information from claims data, structured medical records, physician notes in EHR, lab results, or pharmacy prescriptions.

New technology allows us to conduct data linkage at scale for all trials—especially in the U.S., where RWD data ecosystems are robust, and we have seen regulators look favorably upon this. In 2022, Medidata Link (Medidata’s linkage technology) won the Innovation Award from the Reagan Udall Foundation for the FDA, highlighting the excitement from the regulatory community towards linkage’s potential to reduce trial costs, timelines, and patient burden. 

Q: What are some things we can do to drive industry adoption of linkage and make the process more efficient? 

Ana: There are a few things that come to mind such as fostering collaboration between sites and clinical development teams, starting small and then expanding, and ensuring informed consent (ICF) language is easy to understand and patient-friendly.

Successfully deploying data linkage and gaining the maximum value requires collaboration between teams. Clinical development, HEOR, and RWD teams must work together to ensure that sites gather the right patient consent and PII data upfront, so the linked data can effectively address key clinical development questions and generate impactful evidence later on.

Particularly when data linkage is new to an organization, sponsors who start with an initial pilot study and then expand linkage into broader therapeutic areas have been able to train teams and build the relationships that then lead to the ability to successfully scale. 

Lastly, it’s critical to give the informed consent language careful consideration—crafting language that is simple, clear, and transparent for patient interpretation and ideally, generalizable across many trials within an organization to minimize re-work as linkage is deployed across the entire portfolio. It’s of utmost importance to also consider the patient’s ability to withdraw their consent to linkage at any time and to set up scalable solutions that allow them to do so easily. 

It’s an exciting time for data linkage, and we look forward to sharing perspectives from our team and partners in future blogs within this series.

References 

• 1. 1. Fda.gov, Real-World Data: Assessing Electronic Health Records and Medical Claims Data To Support Regulatory Decision-Making for Drug and Biological Products, September, 2021. Accessed May 30, 2024