RWD Into RWE: What Sponsors Need To Know For Trials

By Life Science Connect Editorial Staff

As sponsors look for ways to develop more effective and patient-centered trials, RWD and RWE are becoming increasingly important tools, though questions remain about how to use them most effectively. When applied strategically, these data sources can help drug sponsors address challenges associated with small sample sizes, limited patient diversity, and controlled environments that do not adequately reflect real-world conditions.

To help organizations navigate these opportunities and challenges, experts Aaron Kamauu, MD, CEO and Co-Founder of Navidence, and Kathleen Mandziuk, MPH, RN, Founder of Athena Innovations, shared their strategic recommendations during a recent Clinical Tech Leader live event, Turning RWD Into RWE That Works For Trials.

How To Evaluate RWD

While RWD can be highly valuable in clinical trial development and execution, no single data set is perfect, and sponsors must navigate a variety of data sources. Per Mandziuk, “We have broad, wide data such as claims data, which is high level, covers a large population, and can be highly representative. Then there are puddles of data, such as data from a lab, a subpopulation, or a network.” To successfully leverage RWD into RWE, sponsors must first define the question they are trying to answer for their trial and, from there, assess which data sets could provide the necessary insights.

When evaluating this information, sponsors should ask the following questions:

• What are the limitations of the data, and how will they be accounted for in the analysis?
• Is there enough data available to answer the scientific question with sufficient statistical power?
• Is the evidence robust enough to serve as an external control arm if needed?
• Why was this data documented in the first place? What was the primary use?
• What country did the information originate from and what is that country’s healthcare model? For example, is healthcare embedded into citizenship or is coverage contingent on employer-sponsored insurance? How does the data align with the study population and trial objectives?
• How do HIPAA, GDPR, and other privacy requirements impact these potential data sets?
• How should teams approach matching cohorts, outcome measures, and endpoints with the intended target patient population? How can these categories be defined to represent the patient?
• Can information from patient devices and wellness applications supplement more robust data pools?
• How will tokenization be applied to link multiple sources together while maintaining patient privacy and anonymity?

Kamauu emphasized the importance of maintaining patient privacy standards along the journey to identifying relevant RWD: “The more data you link together, the more you have to reevaluate, especially for clinical trial linkages. You must ensure that you are continuing to care for a patient’s privacy and confidentiality concerns.”

Where RWE Has A Transformative Impact

Many sponsors are still hesitant to incorporate RWD and RWE into their clinical trial ecosystems. In most cases, they are still determining where these data pools fit best into their workflows. But, if applied with precision, the data from real-world healthcare scenarios derisks the effort of bringing a new molecule to market.

First and foremost, RWD and RWE support improved site selection and patient enrollment, two persistent challenges for sponsors. Organizations can also gain RWD insight into inclusion and exclusion criteria by analyzing how eligibility criteria affect real-world patient availability and enrollment feasibility. If trial demands are too high, a patient is at a higher risk of dropping out or failing to comply with the protocol.

RWD allows comparison of a trial’s visit volume versus a patient’s standard visit volume; thus, sponsors can assess whether a trial protocol is adding significant burden to patients and caregivers. Patient-reported data, such as data from glucose monitoring devices, can be used to provide greater insight into patterns and trends, data gaps, and whether patients are wearing their devices effectively. From there, sponsors might identify strategies to improve patient compliance in research.

Trial tokenization is another approach that enables long-term monitoring and safety and effectiveness follow-up. Kamauu explained its potential impact: “Patients involved in a trial for a specified time period provide consent, and then sponsors can virtually follow up with those patients to determine long-term outcomes. We’ve already started to see success for this but since it’s a new methodology, it will still be a number of years before these studies are finished.”

But ultimately, taking a data-driven approach is only one part of the equation for shortening a drug’s time to market and executing a successful trial. Sponsors must leverage RWD/RWE insights to optimize trial execution by reducing patient and site burden, informing study coordinators, and strengthening patient engagement.

What Regulators Are Expecting

Regulators like the FDA and EMA expect RWD and RWE to be fit-for-purpose with a high level of rigor. Both organizations have shared guidance documents and informal communications to detail their expectations on how RWE should be evaluated and used to gain regulatory support. From a regulatory perspective, fit-for-purpose often comes down to how reliable the data is, whether the endpoints are comparable, and if RWD patients are truly representative of the trial’s patient population. Regulators will assess whether data is relevant to a study question, where it originates from, and whether it is traceable.

Sponsors must work closely with regulators to understand expectations, including what conditions need to be met and what statistical methods should be used. By taking the time to work together and understand review expectations, teams will be better positioned to avoid black box warnings and post-marketing commitment studies.

The Hurdles To Widespread RWD/RWE Usage

The biggest obstacles are time, risk, and proper training. According to Mandziuk, “Folks working in the RWD space are very comfortable [with these data sources and methodologies]. However, when it comes to tokenization or regulatory pathways, there is often an underestimation of the level of effort required. There are new requirements around privacy and trial implementation. There needs to be cross-functional, educational sessions to ensure that everyone across an organization has the same baseline understanding despite different experiences.”

Historically, clinical teams have been highly siloed, but the incorporation of RWD requires synergy, cohesion, and shared governance across stakeholders. If teams are going to successfully apply RWD to clinical development, they will need greater cross-functional understanding of GCP requirements and expectations. With continued collaboration, engagement with new and disparate data sources, and the application of emerging RWD and RWE methodologies, sponsors can strengthen team alignment, improve timeline reliability, and increase the likelihood of trial success.