Use of Real-World Evidence to Support Regulatory Decision-Making for Medical Devices
Today we’re looking at the medical device industry! Did you know on December 18, 2025, the Food and Drug Administration (FDA) released an updated guidance clarifying how they evaluate real-world data (RWD) to determine whether it’s of sufficient quality for generating real-word evidence (RWE) in their regulatory decision-making for medical devices? This document supersedes the previous guidance issued August 31, 2017, and encourages discussion with the FDA for alternative approaches to RWD use, let’s dive in!
Real-world data (RWD) are data relating to patient health status and/or the delivery of health care routinely collected from a variety of sources such as electronic health records (EHRs), medical claims data, data from product and disease registries, and data gathered from other sources such as digital health technologies (DHTs) that can inform on health status. Real-world evidence (RWE) is the clinical evidence regarding the usage and potential benefits or risks of a medical product derived from RWD analysis [1] . It’s important to understand RWD as it provides valid scientific evidence to determine device safety and effectiveness. RWD can help inform the benefit-risk profile of devices throughout their lifecycle, and RWE can be generated from various RWD sources.
Key updates include more detailed standards for data quality, transparency in data origination, and robust methods for mitigating bias. The guidance also expands the definition of acceptable data sources (as long as they meet validation standards), encompassing EHRs, patient registries, and certain types of patient-generated data. Additionally, the FDA emphasizes the importance of ongoing stakeholder engagement and encourages early interaction with the Agency to ensure RWE study designs align with regulatory expectations.
The previous 2017 guidance document established foundational principles for using RWE but left some ambiguity around operational requirements and data acceptability. The 2025 update addresses these gaps outlining a few method expectations and introduces a risk-based approach to data assessment. The update covers various regulatory submissions including but not limited to: Investigational Device Exemptions (IDEs), 510(k)s, Premarket Approval (PMA), Humanitarian Device Exemptions (HDEs), De Novos, and post-approval study PMA supplements. It integrates advances in digital health technology, recognizing the growing role of interoperable data platforms and real-time monitoring in evidence generation. The guidance, however, does not address non-clinical data or systematic literature reviews nor does it provide specific criteria for RWD source suitability.
Outlined in the guidance is the application of IDE requirements to clinical studies using RWD (based on the context of its use and hypothetical examples) as well as RWD from devices authorized under Emergency Use Authorization (EUA) to support regulatory decision-making. Sponsors must conduct assessments to determine the relevance and reliability of RWD sources, study design, and analytic components. Data should be accurate, complete, of high quality to credibly address the research questions, and Good Clinical Practice (GCP) should be followed to ensure data credibility and subject protection.
Some key factors for RWD relevance and reliability include but are not limited to:
Sufficient detail to evaluate the study question.
Linkages between data sources should be scientifically valid and protect individual privacy.
Outdated data may not reflect current clinical practices, so timeliness of data is crucial.
A representative study sample of the intended population should be selected.
Data should be collected consistently and methodically to ensure reliability.
Quality control processes and data monitoring must be in place.
Completeness and accuracy of data across sites and over time must be assessed.
Sponsors should document adherence to data collection and verification procedures.
Careful planning is essential for studies using RWD to ensure data relevance and reliability. The study design should be tailored to the specific research questions and regulatory purpose. Various study designs can also be used including observational studies and randomized controlled trials. Sponsors must document their design choices and rationale to support the study’s validity; they should provide comprehensive documentation to support the use of RWD in regulatory submissions.
While the expanded use of RWE introduces flexibility, there are some risks and regulatory items to consider. Variability in data sources and collection methods can introduce bias or gaps in evidence, if this isn’t addressed, it may undermine the decision-making process. The guidance’s call for transparency and robust validation is essential but places the burden of proof on the sponsors. Additionally, increased reliance on digital platforms heightens cybersecurity and privacy risks, which requires comprehensive safeguards for patient data. Regulators and industry must collaborate to ensure that innovation doesn’t outpace the evaluation of safety and effectiveness.
Various scenarios were outlined where RWE has been used in regulatory decision making. Stakeholders are encouraged to engage early with regulators and invest in data infrastructure to advance patient care. Overall, by clarifying expectations and expanding the scope of acceptable data, the FDA is fostering a more adaptive and responsive regulatory environment. Success will depend on the industry’s ability to meet these elevated standards for data quality and transparency while addressing risks.
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