Real‐World Data for Regulatory Decision Making: Challenges and Possible Solutions for Europe

Are Novel, Nonrandomized Analytic Methods Fit for Decision Making? The Need for Prospective, Controlled, and Transparent Validation

“…Alas, data, even of good quality, do not necessarily translate into credible evidence in the absence of adequate (statistical) methods to extract, analyze, and interpret them. 2,9 Addressing this obvious bottleneck, a range of relatively novel methodologies have been proposed or refined over the past decade to enable the analysis of RWD or to combine RWD with RCT data. Unsurprisingly, proponents of these methodologies argue that they can address potential biases and deliver robust evidence.…”

“…As the ecosystem for e‐health develops, so will data quantity. Issues of data quality, including missing data, and differences in terminologies and data formats will be more challenging to resolve . However, the need for quality assurance and control procedures has been recognized and a range of initiatives are aiming to bring RWD quality to a level of regulatory acceptability.…”

“…Issues of data quality, including missing data, and differences in terminologies and data formats will be more challenging to resolve. 2 However, the need for quality assurance and control procedures has been recognized and a range of initiatives are aiming to bring RWD quality to a level of regulatory acceptability. Collaborations among stakeholders and opportunities for data processing and quality improvement are constantly growing.…”

Examining the Use of Real‐World Evidence in the Regulatory Process

“…The US Food and Drug Administration (FDA) defines data relating to patient health status and the delivery of healthcare (such as electronic health records (EHRs), claims and billing activities, product and disease registries, and patient‐generated data) as real‐world data (RWD), and the analysis of these data regarding usage and effectiveness are termed real‐world evidence (RWE) . The European Medicines Agency (EMA) similarly defines RWD as defined as “routinely collected data relating to a patient's health status or the delivery of health care from a variety of sources other than traditional clinical trials” and expressed interest in using RWD for regulatory decision making . RWE presents great potential to accelerate therapy development and to monitor the successes and failures or both newly approved and existing therapies .…”

Can We Rely on Results From IQVIA Medical Research Data UK Converted to the Observational Medical Outcome Partnership Common Data Model?

“…Naturally, working with more than one dataset with different data structures, variables, and coding practices is a challenge and this is particularly relevant in the European landscape, rich with RWD but of heterogeneous nature . Moreover, addressing the same research question in separate studies on different datasets will encounter many of the same challenges, resulting in duplication of efforts to address them with consequences on time and resources needed.…”