European Epidemiological Forum

This session will present an overview on the value of Real-World Data (RWE) and Real-World Evidence (RWE) going beyond data and evidence themselves!
Bearing in mind the recent COVID-19 crisis, we will address the importance of open long-term collaborations between private and public stakeholders to collect and use RWD and RWE. These may benefit from the healthcare ecosystem and help build trust among the public and end-users of health advancements. We need a change of mentality that brings together innovative approaches and intensive analytics!

Evidence needs are increasing and evolving. Ideally, one may start local strategic Real-World Evidence (RWE) planning at the Drug Development Program (DDP)/end of phase 1 (launch –5 years) and should continue during all drug development phases and after launch. This enables a successful collaboration and discussion with National Health Services (NHS), which leads to a better impact on public health. RWE is crucial to better understand how drugs perform in broader patients groups.

We are nowadays asked to produce all of the clinical, epidemiological, organizational evidence that may support adopting a health value-based approach. Partnerships between Pharma companies and NHS are the only solution to face the complex present challenges in health care, which are increasing more and more.

The pandemic of Sars-CoV-2 has accelerated this process, highlighting the need for timely, valuable evidence, better data, and registries, open collaboration between all the stakeholders, flexibility, and the ability to make decisions based on RWE.

Are we ready? Do we have the right mindset? Do we have the needed know-how? Are we fast and smart enough in conducting studies? Are we focusing on real gaps? Are we able to reach patients, pharmacies, GPs, and caregivers also to understand how a new therapeutic approach can properly work? Are we capitalizing on the experiences of other countries? Are we able to partner with the Health System early on and in a collaborative way?

I don’t have all of the answers, however, I would be happy to share some experiences about:

– Partnering with NHS: the implementation research
– Innovation and operational aspects in RWE generation
– How to better listen to patients’ voice

The National Institute for Health and Care Excellence (NICE) provides national guidance and advice to improve health and social care. In January 2020 we published a Statement of Intent to increase and extend the use of data in the development and evaluation of our guidance. This explores:

• What kind of evidence does NICE currently use to develop guidance
• What broader types of data are available
• When and why should broader types of data be considered
• Practical considerations associated with data analytics

We have since defined the programme to develop a methods and standards framework for activities involving broader sources of data and applied analytics. We accelerated some aspects of this to ensure fit-for-purpose analysis during the COVID-19 pandemic. It can be summarised into five key topics, which are crucial to address to ensure best practice in conducting high quality analyses of data. These are Research Governance; Data; Analysis; Results and Dissemination. In addition to these topics, the programme will consider some cross cutting issues ranging from transparency and public trust, to the validation and evaluation of artificial intelligence [AI] in digital technology.

The presentation will give an overview of the transformational journey to increase the use of broader data and applied analytics in NICE Guidance. It will also touch on the some of the issues we are considering with Standards; which will be crucial for any organisation seeking to ensure their approach is suitable for regulatory assessment/evaluation.

In the past couple of years, development of IT systems and IT capacity have brought a huge amount of data that could be potentially used to support clinical, managerial and policy decision-making. However, so far the utilisation of RWD or RWE in the approval or reimbursement of drugs is very limited. There may be some reasons behind it notwithstanding the methodological concerns. HTA is a formal process to review structured evidence, but HTA has never been designed to evaluate neither systematic RWD nor RWE, in spite of major transformations in healthcare stem at RWE.

The objective of this presentation will be to review both the methodological and non-methodological concerns from payers and decision makers regarding the use RWE, and how can we try to overcome those limitations, with particular focus on non-methodological concerns. Equally we will try to build on some examples of submissions that have been used in the past in country-specific jurisdictions to approve/reject the usage of a new drug.

Main takeaways for the audience should be understanding how to better use the data available to support their submissions.

Regulators, health technology assessment (HTA) bodies, academics, bio-pharmaceuticals companies, payers, and patients are presently rethinking the healthcare ecosystem and facing diverse and increasing challenges at different levels. With ever increasing demands on healthcare costs and considerable focus on drug pricing across global markets, conceptual modelling within value-based agreements between drug manufacturers and payers has never been more important.

The potential for Real-World studies to provide complementary evidence to that provided by randomized controlled trials are becoming more established within formal assessment and appraisal processes across the globe. Whilst RCTs provide evidence of efficacy, Real-World Data provide information on therapeutic effectiveness in a real-world practice setting. Pharmaceutical companies need to focus on innovative and targeted therapies both due to the increased competition in the sector, and of the number of better structured and demanding patients’ groups or associations.

Payers, and HTA bodies want to make sure that the most innovative and novel medicines reach patients who need them most as quickly as possible; and that these medicines provide value for money to all parties: patients and health care systems. They will need to address the following:

• How can sponsors better demonstrate the value of their innovative medicines using RWD?
• How can they work with decision-makers to establish agreed upon standards for RWE research?
• How do recent frameworks (FDA, NICE, etc) help advance RWE research?
• How does RWE address critical issues such as cost effectiveness, budget impact and uncertainty?

What brings all stakeholders at the same level is the need for new paradigms for a more performing healthcare ecosystem that reduce the gap between its representation and its implementation. Emerging e-health models and applications can greatly contribute to it, particularly, if hand-in-hand with Real-World Data Studies. The European Epidemiological Forum will review the progress and perspectives on the value of RWD in ensuring access and reimbursement of new innovative medicines, will discuss what RWD promises, what the barriers may be and what a successful story may look like.

We live in a data-driven environment. As clinical researchers, epidemiologists and scientists, we generate, use, and share data on a daily basis.

The current drug regulatory landscape supports the use of non-conventional clinical data sources to compensate for the lack of generalisability of data from clinical trials. Recent guidelines are encouraging the use real-world data (RWD) collected outside the controlled environment of clinical trials as clinical evidence to support efficacy and safety of health products. Real world evidence (RWE) is collected in many different ways, including patient registries, mobile devices, geolocation information and wearables, and is largely technology driven.

Any data we collect needs to be used appropriately and responsibly. Two key aspects in data use that we need to consider are data transparency and data privacy. Though these may be contradictory first glance, these two principles are actually complementary.

The new EU regulations and updated ICH guidelines are pushing for public disclosure of data through many different platforms, such as publicly accessible clinical trial databases and open access biomedical publications. The aim of transparency is to promote innovation and trust in the healthcare industry.

Coupled to data sharing is maintaining data privacy of the individual. The General Data Protection Regulation was adopted to harmonise data protection across the EU, provide better protection to data subjects, and clarify the responsibilities of data controllers and processors.

Taken together, these regulations and guidelines provide researchers and scientists a solid framework to perform research that is scientifically sound, fair, and patient-centric.

This presentation will discuss the interplay between data collection, data transparency and data protection and the regulations governing them in the context of RWE generation, use, and dissemination. The relevant guidelines and regulations will be discussed and case studies will be presented.

A fully digital data collection system, including patient identification, would represent a substantial advance in how patient-reported outcomes (PRO) data are measured. Within the European Union, one way to identify patients without the involvement of healthcare professionals is to use the unique 2D matrix codes on the packaging of prescription medication.

DePRO is an observational, multi-center, cross-sectional, digital, patient-driven study conducted in Germany. Patients with a prescription for a metformin-containing medication are given a postcard by their pharmacist, which includes a download link for the my ePRO app. Participants use their own mobile device to download the my ePRO app and access the DePRO study, for which they can register using the 2D matrix code on their medication. An electronic informed consent is collected.

The PRO instruments used in the study are the summary of diabetes self-care activities scale, the diabetes treatment satisfaction questionnaire and the EQ-5D questionnaire.

Patients are also asked to complete a questionnaire with items addressing demographics, patient characteristics, disease history, complications and concomitant medications. Enrollment of the first participants started in June 2020 (recruitment period, 3 months; planned sample size, 300 patients). The design of the DePRO study represents a substantial advance in scalability using digital capturing of PRO data.

The COVID-19 pandemic provided a dramatic example of how big data can provide quick access to invaluable information and a unique opportunity for decision-makers to respond rapidly to a public health emergency while posing new challenges for the scientific community on data integrity and reliability.

Some analyses and interpretations were controversial – leading to 3 retracted papers in 3 leading medical journals; public health authorities did contribute to misinformation (e.g. use of ibuprofen) and decision-makers were not prepared.

During the workshop we will study the anatomy of a crisis that illustrates the need for specific approaches to big data and collaboration at different levels of the decision-making process.

Managed by

Christian Agboton – Sr Global Brand Medical Director at Takeda
Maurille Feudjo Tepie – Observational Research Director at Amgen
Michele Intorcia – HEOR Senior Director at Apellis Pharmaceuticals