{"id":17335,"date":"2025-09-15T14:43:17","date_gmt":"2025-09-15T14:43:17","guid":{"rendered":"https:\/\/ubc.com\/?post_type=insights&p=17335"},"modified":"2025-09-15T14:58:53","modified_gmt":"2025-09-15T14:58:53","slug":"the-critical-role-of-database-feasibility-assessments","status":"publish","type":"insights","link":"https:\/\/ubc.com\/insights\/the-critical-role-of-database-feasibility-assessments\/","title":{"rendered":"Is Your Real-World Data ‘Fit-for-Purpose’? The Critical Role of Feasibility Assessments"},"content":{"rendered":"\n

Real-world data (RWD) are becoming an increasingly important resource for drug development and post-market surveillance. These population-based data sources that capture patient health status and healthcare in real-world settings often generate real-world evidence (RWE) that provide valuable insights into safety, effectiveness, and utilization of a marketed product. Additionally, RWD can enhance the pre-approval clinical trial process through targeted patient recruitment and identification of external control arms. Regulatory bodies are now accepting more RWD and RWE as part of their decision-making process, as highlighted in a recent U.S. Food and Drug Administration (FDA) statement: \u201cFDA is committed to realizing the full potential of fit-for-purpose RWD to generate RWE that will advance the development of therapeutic products and strengthen regulatory oversight of medical products across their lifecycle.\u201d1<\/sup> <\/p>\n\n\n\n

With the proliferation of available and increasingly diverse types of RWD, a critical challenge faces researchers at the onset of designing a database study: selecting the right data sources to support the research. This article provides approaches to help ensure that database feasibility assessments \u2014 conducted in advance of research to evaluate key study and logistical criteria \u2014 are successful in identifying the most relevant data sources appropriate for the evaluation of study objectives. <\/p>\n\n\n\n

Identification of RWD sources with potential to satisfy evaluation criteria<\/strong> <\/p>\n\n\n\n

Identifying a wide range of potential data sources is a crucial first step in the feasibility assessment process. Some common RWD sources include electronic medical records (EMR), patient registries, medical and pharmacy claims, and patient-generated data, such as those gathered from surveys. One of the best approaches for this first step is to review relevant published literature that present results from database or registry studies with similar objectives to the current study of interest.   <\/p>\n\n\n\n

Secondly, the use of online database search tools offers an efficient way to selectively identify healthcare databases that match key study criteria like geography or population demographics. These online tools include B.R.I.D.G.E. TO DATA<\/a>\u00ae<\/sup>, an online database profiling global population healthcare databases for use in epidemiology and health outcomes, and the HMA-EMA Catalogues<\/a> of RWD sources and studies. These repositories collect metadata from RWD sources and studies with the potential to help researchers identify suitable data to address specific research questions.  <\/p>\n\n\n\n

Importantly, researchers should consider RWD that offer unique, less traditional types of data elements not consistently found in conventional RWD sources. For instance, in the US, data from commercial patient support programs sponsored by pharmaceutical companies to improve patient access to, and overall experience with, a marketed drug may provide unique data elements for a study that is evaluating treatment patterns and non-compliance to a newly marketed product.  <\/p>\n\n\n\n

Establishing key criteria for selecting the appropriate data sources <\/strong> <\/p>\n\n\n\n

An essential consideration for conducting successful database feasibility assessments is prioritizing the most important criteria for database evaluation and ultimate database selection. Publicly available documents have been issued by the FDA and the European Medicines Agency (EMA) that contain guidance to support high-quality RWE generation, with the goal of  continuing to strengthen the use of RWD and associated RWE for regulatory decision-making.  Two recently released documents by regulators that provide valuable insights into critical characteristics of RWD to be considered in regulatory submissions include: Journey towards a roadmap for regulatory guidance on real-world evidence<\/em> (EMA, February 2025)2<\/sup> and Real-world data: Assessing electronic health records and medical claims data To support regulatory decision-making for drug and biological products (FDA, July 2024).<\/em>3<\/sup> <\/em> <\/p>\n\n\n\n

Some of this guidance is specific to the type of RWD, such as FDA\u2019s recommendation that sponsors using EMRs should evaluate the completeness, accuracy, and plausibility of the data, including verifying data against the source.4<\/sup> It is important to provide evidence to regulators that a selected database is appropriate for addressing the specific study question of interest. In general, the following evaluation categories should be used to assess \u2018fit-for-purpose\u2019 for selecting data sources to use in conducting the study of interest:  <\/p>\n\n\n\n