eal-world evidence (RWE) policy is evolving around the world, with increasing recognition that RWE offers a value proposition for all stakeholders in the research, development, and healthcare ecosystem. In the European Union, the European Health Data Space (EHDS), if optimally implemented, has the potential to advance the concept of a learning healthcare system that enables not only sharing of data but also sharing of insights. This concept provides a vision for a future when improved, more connected use of data will enhance decisions on therapies for individual patients, with feedback loops from clinical practice to research and development, and then back again, with each helping the other to make better decisions faster.

Delivering on this vision will require that all the elements and partners in the ecosystem come together to unlock the potential of real-world health data. In order for EHDS’s proposal to be feasible it will require standards and interoperability framework, governance, and rules to access, share, and use the data , and the evolution of the regulatory framework so that there is greater clarity on use cases and a shared confidence in methodologies.

One EU regulatory initiative that has been working towards increasing the capacity to generate and use RWE is the Big Data Steering Group (BDSG) set up by the European Medicines Agency (EMA) and the Heads of Medicines Agencies (HMA) in 2019. It has been tasked with implementing the vision of the European Medicines Regulatory Network to increase the use of big data (including real-world data, RWD), thus improving the regulation of medicines. In July 2022, the Steering Group published its third workplan, which sets out key actions to be delivered between 2022-2025.

Across the world, we see links between RWE policy evolution and advancement of other policy goals as the potential for RWE to supplement randomized clinical trials and provide insights into broader populations and patient experiences grows more evident. While most progress has been made in rare diseases and oncology, there are multiple future opportunities to extend these experiences to other diseases. With increased availability of healthcare data and advancements in analytics, the potential to work towards closing some of these gaps is significant, supporting precision medicine, and ultimately improving patient health outcomes.

Aside from inclusion in regulatory submissions, RWE can also facilitate medicines’ development by, for example, helping to understand the natural course of diseases, identifying existing standards of care for diseases, refining clinical trial inclusion and exclusion criteria, and providing data to support orphan designation. Artificial intelligence (AI) and machine learning (ML) will continue to bring forward additional insights to complement and inform development strategies within companies as well as regulatory discussions.

RWE can also play a key role in facilitating patient access to medicines. For example, RWE can support health technology assessments (such as for managed entry agreements or other novel payment models) as well as payer decisions. In this way, RWE can feed into a learning healthcare system that enables healthcare decisions to be refined on an ongoing and iterative manner, as more relevant data become available.

COVID-19 focused attention on developing effective research strategies to address critical questions, using the right tools for the key questions, and recognizing the respective roles of both randomized clinical trials (RCTs) and RWE, each with its role for contribution. In (but not only in) this pandemic setting, it has become clear that data generation and collection are multidimensional and distributed across many different actors; consequently, it is critical that research designs and data are scientifically based and robust, and that we continue to learn the pandemic’s lessons on collaboration to build the most complete evidence and evaluation base possible.

EMA’s own federated network of real-world data sets, DARWIN EU®, will be embedded in the EHDS and used to conduct RWD-related research that will inform regulatory decision making. As observed by a former co-chair of the BDSG, the planned launch of DARWIN EU® in 2024 will provide a unique opportunity to advance multistakeholder alignment on what constitutes fit-for-purpose RWE in a specific context. Industry has emphasized the importance of predictability and transparency around how DARWIN EU® is used to generate RWE and the importance of engagement on data sources, study design, methodologies, and analytical approach.

Building trust and confidence in RWE requires platforms for multistakeholder dialogue. Demonstration projects, workshops, and shared learning from use cases can be vehicles for advancing development of regulatory guidelines such as the EMA’s registry-based studies guideline. IMI EHDEN is building a large-scale federated network of data sources that is already facilitating observational health research in Europe and will be fully operational by 2023-2024. This network comprises hundreds of millions of European patient records that are being been mapped (in an ongoing program) using the Observational Medical Outcomes Partnership (OMOP) common data model.

Regulatory guidance for pharmacoepidemiological studies has largely emerged in the post-marketing evidence-generation setting. However, regulatory expectations and their formalization into regulatory guidance that is applicable through the product lifecycle have been evolving through policy development and experience. Building on their collaboration in the use of RWE to support regulatory decision making for COVID-19 vaccines, a collective vision for international harmonization and convergence has been outlined by ICMRA members. The ICMRA statement acknowledges the continuing importance of ICH and the recent initiation of work to develop an ICH guideline on planning and designing pharmacoepidemiology safety studies using RWE. The statement may intensify debate as to whether the time is right to develop a roadmap towards ICH guidance for RWE.