April 19, 2022

Regulatory Insights: Potentials, use cases and regulatory side of Real World Evidence in Germany

“Evidence generated by high quality observational research is fundamental to understanding the safety and effectiveness of medicines in everyday use by patients and doctors.”

Global Regulatory Workshop on COVID-19 RWE and Observational Studies, July 2020.

Heartbeat Medical Team
Heartbeat Medical Team

The role of RWE

RWE was defined by the 2007 ISPOR Real-World Data Task Force as any “data used for decision-making that are not collected in conventional RCTs”1  and data sources can include prospective or retrospective RWE from patients, caregivers or healthcare workers collected via practical controlled trials, registries, administrative data, health surveys and electronic health records. 

RWE can play a role in both pre- and post-marketing authorisation approval. In the preapproval setting RWE can enhance the effectiveness of RCTs via the identification of patients from specific subpopulations such as their background epidemiology which could potentially lead to shorter and more effective trial periods.

In the post-approval setting RWE has a role in analysing patient outcomes in real world settings to generate further insight on safety and effectiveness of innovative products, as well as increasing understanding of real-life treatment pathways, treatment sequences, length of required treatment and the resources required plus specific disease processes.

Current Legal Framework in the EU – there is none

At present, there is no established legal framework in the EU on the use of RWE in regulatory or clinical decision making with limited guidance available 2. Article 8(3)(i) of Directive 2001/81/EC states that the applicant for a marketing authorisation should provide “the results of pharmaceutical tests, pre-clinical tests and clinical trials.” RWE or non-interventional/observational studies are not explicitly mentioned, however have fallen under this umbrella category with regards to its legality.

A Multi-Stakeholder EU Learning Network on RWE - efforts and perspectives

The Heads of Medicines Agency (HMA) and EMA have indicated that to develop use of Big Data in health, iterative approaches are required with relevant stakeholders. 

Such approaches support: 

  • data standardisation
  • improved data quality
  • the promotion of data sharing and access

Subsequently robust data processing and analyses are possible to produce RWE that has regulatory acceptability 3


Ten recommendations were issued to develop this effort which included the delivery of a sustainable, cross-border data sharing platform to access and analyse healthcare data from across the EU via  the Data Analysis and Real World Interrogation Network (DARWIN) 3.  An EU Big Data “stakeholder implementation forum” is also proposed to build a resource of key messages and communication materials on regulation and Big Data 4.

The DARWIN initiative will deliver RWE from across Europe on diseases, populations and the uses and performance of medicines. This will enable EMA and national competent authorities in  the European medicines regulatory network to use these data whenever needed throughout the lifecycle of a medicinal product.

DARWIN EU will support regulatory decision-making by: 

  • establishing and expanding a catalogue of observational data sources for use in medicines regulation.
  • providing a source of high-quality, validated real world data on the uses, safety and efficacy of medicines.
  • addressing specific questions by carrying out high-quality, non-interventional studies, including developing scientific protocols, interrogating relevant data sources and interpreting and reporting.

Organisations such as the European Centre for Disease Prevention and Control, Health technology assessment bodies and payers may make use of DARWIN EU in the longer term, full operations are expected to be in place by 2024 5

The UK’s Medicines and Healthcare products Regulatory Agency (MHRA) issued guidance on RTCs generating RWE that will be used to support regulatory decisions in recognition of the breadth of information that can be generated. The MHRA created a new licensing pathway for innovative medicinal products as of January 2021.The scheme consists of an “adaptive authorisation pathway,” incorporating RWE, continuous risk/benefit assessment, novel clinical trial design, and various regulatory flexibilities. This is a move by the regulator in seeking to align with the industry and promote new ways of facilitating innovation. 

The MHRA has stated that there are no obstacles for the use of RWE to gain initial, speedy approval of new products. They emphasise the importance of robust data, but welcome RWE to support trials and studies for approval 6

The need for uniformity, infrastructure and legislation

RWE has been touted as having the potential to solve problems inherent to getting a drug to market, despite issues around poor data quality and data security concerns. Using RWD may be a better means of proving the value of a new medicine to payers resulting in quicker approval, more valuable discussions and the development of flexible reimbursement agreements meaning that patients can access novel drugs at a sustainable price in a timely manner. As a result, the demonstration to stakeholders of the real life value of novel drug outcomes is key to improved patient access and manufacturer success.

There are a number of requirements in order to ensure that RWE is utilised across Europe to maximise its potential. For instance, ensuring that IT systems and existing data interfaces are advanced enough, optimising existing patient registries and developing centres of excellence for collaboration and/or endorsement. Furthermore, understanding the current legislative frameworks (data ownership, sharing, release and confidentiality) will be required to ensure that any RWE is used in the correct manner for the ultimate benefit of those who matter most – patients 9.

New pathways of reimbursement decisions can be illustrated by the case Roche/Genentech – They are currently developing “Personalized Reimbursement Models”. The goal is to create a system of data collection at the national level about some types of cancer. The data collected are of different types, such as RWD, epidemiologic and clinical data. The integration of all these data permits a deeper understanding of the drug efficacy. 

In particular, RWD was extracted from the systems currently used in the clinical setting to prescribe chemotherapy. Consequently, for the first time in France, a drug (Tecentriq) had a personalised reimbursement scheme to treat non-small cell lung cancer. In case of insufficient benefit for the patient, the competent health authority does not reimburse the treatment, which is fully financed by the industry. However, details regarding these types of contracts between Roche and the Centre for European Policy Studies (CEPS) remain confidential 8.

Real World Evidence

Learn more about the potential of Real World Evidence for drug approval and reimbursement.