5 Key Takeaways from the FDA’s Real-World Evidence Guidance

The landscape of drug and medical device development is slowly shifting towards a data-driven, patient-focused model. This means real-world evidence (RWE) is an increasingly critical component of regulatory approvals, post-market acceptance, and reimbursement decision-making. To stay ahead, sponsors must adopt modern clinical trial platforms that expedite RWE studies, streamline processes, and minimize costs, all while complying with evolving regulatory standards.

What to Know About RWE in Non-Interventional Studies

Earlier in 2024, the FDA released new draft guidance on using RWE in non-interventional studies to support regulatory decision-making1. It provides much-needed clarity on generating evidence in observational studies to address drug efficacy, safety concerns, and labeling changes. Non-interventional studies involve patients receiving marketed drugs during routine medical practice without being assigned interventions per a study protocol.1 This new information follows the FDA’s draft guidance released in August and December 2023 on using RWE in clinical studies for drugs, biologics, and medical devices, respectively.2–4 RWE is rapidly becoming an essential component of regulatory submissions, and it’s fantastic to see the FDA taking steps to guide sponsors on best practices.

Below are the key takeaways from the FDA’s 2024 guidance on RWE in non-interventional studies:

1. Reliability of Real-World Data: No Excuses, Just Results

Data Sources: While not all real-world evidence (RWE) is derived from real-world data (RWD), the FDA highlights the importance of high-quality and reliable RWD when it is used to generate RWE. This is particularly relevant for non-interventional studies that rely on existing data sources. In such cases,  robust data collection methods, appropriate data validation, and precise documentation are crucial to support regulatory decision-making. Reliable data is accurate, complete, and traceable. Data should be provided for key study variables such as exposures, outcomes, and covariates with an adequate number of study participants represented. The data collected should be relevant, suitable for the research question, known as “fitness for use,” and geared toward the target patient population.1–3. 

For example: In a study assessing the impact of a hypertension medication, RWD is sourced from patient health apps. To ensure the data’s reliability, researchers verify that the app consistently records blood pressure readings and medication intake times. They also cross-check these data with patients’ electronic health records for accuracy.

2. Robust Protocols: Get It Right the First Time

Study Designs: Robust protocols will clearly articulate the research question and justify the chosen design, whether it is non-interventional or involves other types of RWE studies, such as pragmatic trials. The FDA guidance emphasizes the importance of choosing an appropriate study design for generating reliable evidence and ensuring high-quality data sources to produce reliable and valid evidence. Study protocols should also include the following information:1,5

• Study design with a causal diagram to identify the proposed causal relationship
• Source and study population
• Eligibility criteria
• Conceptual and operational definitions for key variables of interest
• Relevant covariates, such as concomitant treatments and bias mitigation strategies
• The index date for each study arm
• Start and end of follow-up periods

For example: A pragmatic trial is designed to assess the long-term effectiveness of a new asthma medication. In addition to clearly stating their research question, the researchers incorporate all essential elements into the study protocol (see list above). 

3. Preventing Bias: Don’t Let Your Study Fall Apart

Bias Mitigation Plans: The design and conduct of the study should ensure that an actual treatment effect can be distinguished from other potential influences on the outcomes. Protocols should include detailed descriptions of critical study elements and strategies to identify confounding factors and other sources of biases to ensure the integrity of the study findings. The protocol and analysis plan need to include a detailed approach for mitigating bias due to concomitant medications and other covariates.

For example: In a study evaluating the effectiveness of a new heart drug, the protocol includes a plan to mitigate bias from other medications. Researchers match patients on key covariates like age, gender, and comorbidities. They also use statistical methods like propensity score matching to control for the use of beta-blockers and other heart medications that could affect the study’s outcomes.

4. Comprehensive Statistical Analysis Plans: Leave No Stone Unturned

Analysis Plan: The analytical methods for handling non-interventional study data are crucial. Castor’s platform offers the analytical power you need to meet—and exceed—the FDA’s expectations, ensuring your findings are robust and reproducible. A comprehensive statistical analysis plan should also address the following aspects of the study1:

• Feasibility, sample size, and statistical power
• Method for evaluating the treatment effect
• Method for handling missing data
• Method for handling multiplicity
• Subgroup analyses rationale
• Planned sensitivity analyses
• Overadjustment of causal variables
• Addressing early evidence of outcomes
• Unequal outcomes across study groups

For example: In a study examining the impact of a new dietary supplement on weight loss, the analysis plan includes each of the aspects outlined above. 

5. Regulatory Alignment: Be Proactive, Not Reactive

FDA Engagement: Observational study designs need to align with the evolving regulatory requirements. Sponsors should adopt best practices for designing and conducting these studies. Early engagement with the FDA is highly encouraged to ensure that a non-interventional study appropriately addresses the research question for the intended indication. Meet with the FDA early in the conception and study design process.

For example: A pharmaceutical company is developing a new drug for chronic pain management. Before initiating a large-scale observational study, they meet with the FDA to discuss their study design. During this early engagement, they review the regulatory requirements and confirm that their data sources and methods align with current FDA expectations. This proactive approach facilitates a study that is well-positioned to provide meaningful evidence for the drug’s effectiveness in the intended patient population.

How Castor Supports RWE in Clinical Studies

• Seamless RWE Study Deployment

Castor’s clinical trial platform is designed to align with the FDA’s recent draft guidance on RWE. Our technology enables rapid scaling of RWE studies, capturing extensive datasets across the globe. With video-enabled informed consent and a customized recruitment landing page, Castor facilitates efficient participant recruitment from diverse locations, mirroring the FDA’s emphasis on broadening patient inclusion in observational research.

• Enhancing Participant Engagement

We prioritize participant experience by offering an intuitive web ePRO and mobile app interface. This approach not only aligns with the FDA’s patient-focused model but also ensures secure data capture while enhancing user engagement and comprehension, crucial elements in the FDA’s guidance for generating reliable RWE.

• Optimizing Data Integration and Collection

Our open API allows for seamless integration with various real-world data sources, supporting the FDA’s call for robust data collection methods. Castor’s platform offers flexibility in trial design with customizable forms and workflows, enabling researchers to adapt to real-world complexities such as unscheduled events and mid-study changes. This adaptability is key to maintaining the integrity of RWE, as outlined by the FDA.

• Facilitating Higher Quality Data Returns

Castor simplifies data collection for sites with a user-friendly platform that’s highly rated for ease of use, thereby improving site satisfaction and promoting higher quality data returns. Our Single Sign-On (SSO) feature further eases site burden, aligning with the FDA’s guidance for precise documentation and traceability of data.

Conclusion

As RWE becomes integral to regulatory submissions, the FDA’s guidance is pivotal in shaping best practices and expediting innovation. We are moving into an era of patient-centric, data-driven clinical trials, and the recent guidance will enable sponsors to realize that vision and offer drugs, biologics, and medical devices that best serve patients. 

The FDA’s new guidance sheds light on how RWE will influence the evolving regulatory landscape. Castor’s innovative platform is designed to adapt to the FDA’s evolving guidelines, ensuring that our clients are not just compliant, but also at the forefront of clinical research innovation. By leveraging our robust technology and expertise, sponsors can confidently conduct RWE studies that are not only efficient but also aligned with the FDA’s vision of a data-driven future in healthcare.

Learn More About Castor’s RWE offering

References

1. Real-World Evidence: Considerations Regarding Non-Interventional Studies for Drug and Biological Products. U.S. FDA Guidance Document. Published March 2024. 
2. Considerations for the Use of Real-World Data and Real-World Evidence to Support Regulatory Decision-Making for Drug and Biological Products. U.S. FDA Guidance for Industry. Published August 2023. 
3. Draft: Use of Real-World Evidence to Support Regulatory Decision-Making for Medical Devices. FDA Guidance for Industry. Published December 2023. 
4. Examples of Real-World Evidence (RWE) Used in Medical Device Regulatory Decisions. U.S. FDA, Center for Devices and Radiological Health. 
5. Schneider, M. FDA Offers Guidance on Observational Studies as RWE. RAPS.org. Published March 21, 2024. Accessed May 29, 2024.