Viatris Inc.

Real-world data (RWD) to generate real-world evidence (RWE) can be a useful tool to help us in designing medicines that better address the needs of patients and healthcare professionals. Ensuring that data, generally big data, can be discoverable is key before further harnessing.

The Heads of Medicines Agencies (HMA) and European Medicines Agency (EMA) have recently developed for feedback, “Good Practice Guide for the Use of the Metadata Catalogue of Real-World Data Sources.” This is an essential guide via the European Health Data Space (EHDS), which “supports individuals to take control of their own health data, supports the use of health data for better healthcare delivery, better research, innovation and policy making, and enables the European Union to make full use of the potential offered by a safe and secure exchange, use and reuse of health data.” The first step of data discoverability in the entire RWD ecosystem incorporates several aspects which may be reiterated, including the definition of a sustainable process, the workflow of the entire process, and collaboration and partnership across stakeholders. 

From the perspective of value-added medicines (VAMs), specifically, RWD can be ripe for VAMs, for repurposing, reformulating, or combining established treatments, which are what we define under the concept of VAMs. Such medicines are based on known molecules that address healthcare needs and deliver relevant improvements for patients, healthcare professionals, and/or payers. 

“A metadata catalog, developed in a systematic and comprehensive manner, can be extremely useful, especially for VAMs, besides innovative medicines, since fit-for-purpose and high-quality data are critical.”

In practice, in terms of studies vs. rapid-cycle RWD analytic queries, data feasibilities are critical to better understand the specifics before embarking on tailored approaches through analytic plans, such as the assessment of the suitability of data sources for queries or in terms of assessments. They should be performed and periodically updated by the data holders who participate in the metadata catalog. The data holders should make the methods and the results of the assessment publicly available for assessment and replication of queries or studies. This is also so they may also be verified and validated in a systematic way. 

In order to take concrete actions so that RWD may be discovered in a timely manner, below are a few suggestions: 

● First, detail the elements of the catalog, especially the search key terms and functions;

● Next, strengthen the testing capabilities and options; and

● Finally, provide international perspectives since data sources may be specialized but may not be well-connected or interoperable.   

In summary, a metadata catalog, developed in a systematic and comprehensive manner, can be extremely useful, especially for VAMs, besides innovative medicines, since fit-for-purpose and high-quality data are critical. Therefore, search, query, test, and validation all need to be well-considered.

Kelly H. Zou, Ph.D., PStat® is Head of Global Medical Analytics and Real World Evidence, Viatris Inc. She is an elected Fellow of the American Statistical Association and an Accredited Professional Statistician. Previously at Pfizer Inc, she was Vice President and Head of Medical Analytics & Insights; Senior Director of Real World Evidence, Group Lead of Methods & Algorithms and Analytic Science Lead; Senior Director of Statistics. She was Associate Professor of Radiology at Harvard Medical School, as well as Director of Biostatistics at its affiliated teaching hospitals. She was Associate Director of Rates at Barclays Capital. She received both MA and PhD degrees in Statistics from the University of Rochester. She completed her Postdoctoral Fellowship at Harvard. Her research interests include health policy, real world evidence, signal detection, and artificial intelligence, with over 150 professional articles and 5 books. She was featured as an Outstanding Woman in Data Analytics by Forbes, an Inspirational Women in Statistics & Data Science by Wiley, and an Accomplished Woman in Statistics and Data Science by the American Statistical Association. She was the winner of the Chief Data and Analytics Officers’ Forum’s Future Thinking Award and Reuters Events Pharma USA’s Most Valuable Data & Insights Initiative Team Award.