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This reflection paper discusses methodological aspects of non-interventional studies (NIS) using real world data (RWD) in order to generate real-world evidence (RWE) for regulatory purposes. A NIS is a clinical study that does not fulfil any of the conditions defining a clinical trial (CT) in Article 2.2(2) of Regulation (EU) No 536/2014 on clinical trials on medicinal products for human use, where a CT is defined as a clinical study where (a) the assignment of the subject to a particular therapeutic strategy is decided in advance and does not fall within normal clinical practice of the Member State concerned; (b) the decision to prescribe the investigational medicinal products is taken together with the decision to include the subject in the clinical study; and (c) diagnostic or monitoring procedures in addition to normal clinical practice are applied to the subjects. RWD are data that describe patient characteristics (including treatment utilisation and outcomes) in routine clinical practice. RWE is evidence derived from the analysis of RWD.

CTs are the main source of evidence to evaluate the benefits and risks of medicines in marketing authorisation procedures. As they generally use randomisation, blinding, and a controlled environment, they increase regulators’ confidence in the reliability of the evidence submitted. NIS are often used in post-authorisation safety assessment. Their use for assessing medicines efficacy is hindered by methodological limitations. These include absence of randomisation, uncontrolled conditions, non standardised treatments and uncertainties regarding data quality and completeness. Healthcare data sources accessible for medicine evaluation have evolved over the last decade. The increasing ability to capture electronic healthcare data and data from registries is now providing new opportunities to use RWD and generate RWE that reflects clinical practice. Examples where NIS using RWD have supported regulatory assessment include:

• To perform post marketing monitoring, investigate safety concerns and evaluate the effectiveness of risk minimisation measures.
• To describe patterns of drug utilisation (e.g. indication, characteristics of drug users, incidence and prevalence of use, doses, duration, and switching patterns).
• To characterise disease epidemiology (incidence, prevalence, risk factors and progression).
• To validate outcome measures, e.g. through a comparison of surrogate and clinical outcomes of disease progression.
• To support the feasibility assessments and the planning of non-interventional post authorisation safety (PASS), efficacy (PAES) and drug utilisation studies by measuring outcome incidence, treatment exposure, the duration of available follow-up and the sample size effect of different inclusion/exclusion criteria.
• To compare patient characteristics of the study population to those of the clinical practice population in the real-world.
• To understand the clinical context, by describing standards of care, variability in clinical 80 practices and unmet medical needs.

Given the large amount of information that NIS using RWD can generate for regulatory purposes, it is important to understand their limitations as well as how some of these limitations could be overcome or mitigated to increase the reliability of the evidence. This reflection paper is therefore relevant to all stakeholders involved in the planning, conduct and analysis of NIS using RWD to generate RWE for regulatory purposes, including Marketing Authorisation Holders (MAHs) and Applicants, regulatory authorities, HTA bodies, payers, academia, RWD holders and healthcare professionals’ and patients’ associations.

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