Opportunities to advance RWE in Europe: Assessing today’s landscape and priorities for future guidance
Ashley Jaksa, M.P.H.
Vice President of Science, Aetion
Nicolas Deltour, M.Sc.
Vice President of Real-World Solutions, Aetion
Real-world evidence (RWE) has emerged as an important tool for global regulators, health technology assessment (HTA) bodies, and biopharma organizations alike as they’ve sought innovative ways to inform and accelerate decision-making.
In Europe, standard-setting organizations like the European Medicines Agency (EMA) and the National Institute for Health and Care Excellence (NICE) have taken strides to increase their use of RWE. However, acceptance varies by country, and there is work to be done to drive RWE adoption and use across biopharma, regulators, HTAs, and clinicians.
Here, Aetion’s Ashley Jaksa, M.P.H., Vice President of Science, and Nicolas Deltour, M.Sc., Vice President of Real-World Solutions, draw upon years of experience working with RWE and biopharma to offer insights on the RWE landscape in Europe, how platforms can support stakeholders in running credible analyses, and what more is needed from regulators and HTA bodies to advance RWE.
Read more from their conversation, first published in Health Europa.
Q: How are biopharma, regulatory, and HTA organizations using RWE in their processes?
Nicolas Deltour (ND): At the pharma level, real-world data (RWD) has been widely used over the last decade to support safety monitoring and surveillance, especially for post-authorisation safety studies. But pharma companies have also increasingly used RWD to support development, for example, to inform clinical trial protocols. Biopharma also uses RWD and artificial intelligence (AI) to support hypothesis generation for drug repurposing studies, and to assess the safety and effectiveness of new drugs compared to those already on the market to understand value.
Ashley Jaksa (AJ): RWE, as a concept, is not new for regulators and HTAs. HTA organizations are accustomed to using observational studies and utilization data to enhance cost effectiveness models, while regulators use observational data for safety and surveillance, as well as to approve treatments for rare diseases that may not be well suited for randomized controlled trials (RCTs). In addition, since 2006 the EMA has coordinated the European Network of Centres for Pharmacoepidemiology and Pharmacovigilance (ENCePP®)—of which Aetion is a member—to advance and develop practices for good pharmacoepidemiologic research.
Now, with accelerated approval processes and increased uncertainty at the time of launch, regulators and HTA agencies are navigating how RWE can provide supplemental data to inform decision-making. We also now have the technology and the methodology to produce rapid, valid RWE to answer causal questions, which we traditionally believed could only be answered with data from RCTs.
ND: I agree. Today we also have a massive amount of data available—from electronic health records (EHRs), claims, patient registries, social media, and wearable devices—which are generated on a daily basis. These data, combined with robust methodologies associated with technologies like AI and machine learning, lead to efficient RWE generation that can support decision-making for all stakeholders.
Q: How do European regulators and HTA bodies use RWE to inform decision-making, and how does this differ by country?
AJ: While most countries are in nascent stages of RWE adoption, some are open to innovating faster than others. In the United Kingdom, NICE is working to determine how to leverage RWE, and issued a statement of intent to work on RWE guidances. The Medicines and Healthcare products Regulatory Agency (MHRA) stated plans to issue guidances on RWE. Other countries are more cautious; for example, Germany is focused only on registry data to inform decision-making, not claims or EHRs.
ND: Between the UK and Germany, there are others like France’s Haute Autorité de Santé, which recently issued an updated guidance that includes the need for RWD in evaluations. The EMA is also aware of the added value of RWE. It has deployed a strategy through 2025, which includes a Big Data Task Force to establish a platform of expertise, tools, and data to facilitate the generation of RWE.
Q: What should regulators and HTAs in Europe prioritize in future guidances to advance the use of RWE?
AJ: What we need most is collaboration on RWE methodology and standards between HTAs, regulators, technology organizations, academics, data providers, and others. Many groups have published position pieces to offer recommendations on small aspects of RWE, but we don’t have comprehensive guidance on each one of those aspects.
For example, most people agree that a data set used in an RWE study must be fit for the purpose of answering a specific research question. But how do you define or measure aspects of fitness for purpose? Several organizations have offered definitions, but there is no consensus on which approach is correct.
While we’re still in the early stages of RWE adoption, we need to make rapid progress on guidance development. Without comprehensive guidance on what “good” RWE looks like, we’re going to continue to see varying quality of studies.
ND: Another priority should be to develop guidance that supports regulatory staff in reviewing RWE studies. Such a template could support both regulators and biopharma in providing dosing information. It would also be helpful to develop and harmonize a way to define outcomes in RWD studies. If we had a clear view in Europe of which kinds of outcomes we can use to study disease-area-specific data, we could increase confidence in RWE results.
Q: What are the benefits of an RWE platform for biopharma, regulators, and HTAs?
AJ: The biggest benefit is transparency, both in the data they’re evaluating and in the trust in the processes that transparency facilitates. Another benefit is that platforms, especially Aetion’s, provide the appropriate guardrails to help ensure good science and valid studies.
ND: One of the key benefits of a platform is that it ensures the proper methods are used to run a study, and that it is run transparently. For a regulator or HTA, platforms enable users to reproduce studies—and pressure test them through sensitivity analyses—to ensure the reliability of results.
Q: How has COVID-19 changed the RWD landscape? How will this impact RWE generation and use?
ND: RWD are valuable in assessing patients’ COVID-19-positive status, risk factors, and comorbidities. We have lots of data on COVID-19, and, going forward, RWE can play a key role in providing external control arms to clinical trials. For example, researchers can use historical data to develop comparator arms for vaccine studies.
AJ: While COVID-19 has accelerated the need to quickly analyze the copious amounts of data that we do have, challenges with data access remain. This is largely because we lack clear standards around high quality RWE and how to generate it. With this pandemic, we’ve seen the door open, so to speak, for RWE to support decision-making. But we need to continue to work on data access and quality science to ensure that RWE can deliver on its promise.
Q: What are the implications of increased RWE adoption on health care providers and patients?
ND: Using RWD to generate RWE can speed up and support benefit-risk and value assessments of drugs throughout the product lifecycle. Ultimately, this brings innovative treatments to patients faster.
AJ: RWE enables us to study a wider variety of patients, including those who use drugs on a day-to-day basis rather than limiting research to those involved in clinical trials. RWE also allows us the opportunity to personalize medicine, and it will help make decisions easier for doctors and patients, because they’ll have more information about how a treatment works in real clinical practice.
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