P46: Linking Diverse Clinical Trial and Real-World Data Sets to Enable Clinical Research in a Post Covid-19 World
Poster Presenter
Keith Wenzel
Volunteer
DIA Study Endpoints Community United States
Objectives
Illustrate the utility of linking clinical trial and real-world datasets (RWD) to better understand patients’ disease progression via a longitudinal view of the patient.
Method
We conducted a study that would incorporate record-level data from seven diverse clinical trial and real-world data sources with a focus on proving feasibility, we enrolled eight individuals into a U.S.-based study and incorporated data on those individual from all of these different sources.
Results
We designed a study that would incorporate record-level data from diverse sources:
• Electronic data capture system (EDC), the system through which data is ordinarily captured at clinical trial sites;
• Electronic health records (EHR), which includes data gathered in the ordinary course of care;
• Electronic clinical outcomes assessment (eCOA), which allow patients to reports outcomes directly;
• Patient wearables sources, including a continuous glucose monitor;
• Claims aggregators, which are useful for capturing both billing information and patient outcomes beyond the clinical trial;
• Labs, which contain valuable diagnostic information; and
• Consumer datasets, which contain valuable detail on the social determinants of health
We learned:
1. Data standards and mapping are critical; the importance of data standards only grows as the number of data sources increases
2. To make use of RWD, you need the ability to make record-level connections across datasets while protecting patient privacy
3. To capture the value of continuously generated data, you need a data infrastructure to support near real-time ingestion, processing and storage
4. You can’t do it alone – selecting world-class partners/technology is key
While more work is needed, we have refined the processes for: educating and consenting (including withdrawing consent) of clinical research subjects; sponsor and clinical trial site contracting; site and subject education and support; and secure, privacy-retaining subject and patient de-identification.
Our feasibility study successfully showed how to resolve the operational challenges that come with RWD, allowing researchers to focus on the opportunity that comes with being able to link diverse clinical trial and RWD datasets to the benefit of clinical research and, ultimately, the patient.
Conclusion
All of us in the life sciences have heard a lot about the promise of RWD, but a key question is often left unanswered: “Sounds great but tell me how it works.”
Collectively a successful real-world data study requires standards, data mapping, de-identification of patients, record-level linking and data ingestion and storage of diverse RWD datasets. In addition, supporting collateral and educational materials as well as site training and processes help complete the full circle to minimize the burden on patients and sites while providing complete transparency.
The importance of data standards only grows as the number of data sources increases and because real-world data is not collected with clinical research in mind, standardizing and mapping the data can require significantly more effort than a typical EDC system.
The implications for clinical research are non-trivial. Covid-19 is just one disease where the lessons of this research can be applied. But, the power of linking clinical trial data to real-world data is applicable to literally any indication where visibility into disease progression is of value. By linking multiple clinical trials and real-world data sources, researchers not only have a view into patient study endpoints during a clinical trial, but they also have insight into the patients’ disease progression, or lack thereof, and the first, second and third line therapies which made a difference and the safety events that occurred or, again, the lack thereof.
Our feasibility study successfully showed how to resolve the operational challenges that come with RWD, allowing researchers to focus on the opportunity that comes with being able to link diverse clinical trial and RWD datasets to have better visibility into disease progression beyond the clinical trial in the real world while protecting patient privacy.
