Pharmacovigilance deep dive: risk minimisation measures

Here IQVIA’s Dr Sophie Jouaville discusses the importance of risk minimisation measures, how their effectiveness can be assessed and why transparent reporting of these effectiveness studies is crucial.

concept of risk mitigation - hand turning a dial labelled risk from high to low

To ensure the safety of medicines post-regulatory approval, a risk management plan (RMP) is established. This provides information on a medicine’s safety profile, describing the activities of the marketing authorisation holder to further characterise its safety profile during pharmacovigilance activities and explaining the measures that will be taken to prevent or minimise risks in patients – these are known as risk minimisation measures (RMMs). 

An RMP is submitted as part of the dossier of all new drug applications and is evaluated by regulatory authorities before authorisation is given. Such as plan may also be requested by regulatory authorities for authorised products without one in place should concerns arise about a risk affecting the benefit-risk balance.

This article explores just one aspect of the RMP, that of RMMs, and how their effectiveness is measured with Dr Sophie Jouaville, an associate principal at IQVIA working on the design and oversight of non-interventional real-world evidence (RWE) safety and health economics and outcomes research (HEOR) studies.

What are risk minimisation methods?

woman pouring blue and white capsules from a brown glass bottle to take medication

Jouaville: According to Module XVI of the European Medicines Agency’s (EMA)’s Good Vigilance Practice (GVP), risk minimisation methods, or RMMs, are “interventions intended to prevent or reduce the occurrence of adverse reactions associated with the exposure to a medicine, or to reduce their severity or impact on the patient should adverse reactions occur.”

RMMs aim to optimise the safe and effective use of medical products in clinical practice by improving their risk-benefit balance. This can be achieved by reducing the burden of adverse reactions or by optimising benefits through patient selection (eg, contraindications, recommendations of use, warnings, concomitant medicine[s], or certain test parameters) and treatment management (eg, specific dosing regimen, relevant testing, patient follow-up).

There are two types of RMMs: routine ones related to elements such as the summary of product characteristics, labelling, pack size, package leaflet, or legal supply status of the product, while additional measures may include educational tools for healthcare providers (HCPs) or patients, controlled access or pregnancy prevention programmes, among others.

How is the efficacy of RMMs assessed?

Jouaville: Most RMM effectiveness studies are formatted as surveys or drug utilisation studies (DUS). Surveys principally assess the primary knowledge and self‐reported behaviour of the target population against the RMM content, while DUS use secondary data from electronic records or medical chart reviews to estimate the adherence to prescribing behaviour and practices outlined in the RMM content.

A key point to consider when designing RMM effectiveness studies is which type(s) of data to leverage based on the context and objectives of RMM effectiveness evaluation. Specifically generated primary data, secondary data originally collected for other purposes, or a combination of both may be used to comprehensively evaluate effectiveness.

The call for transparency in the presentation of study sampling methodology should not be limited to RMM effectiveness studies. Any study aiming to generalise its research finding to the whole population should consider the representativeness of its sample”

The representativeness of the study population for the entire population should also be assessed (GVP 4 Module XVI Addendum II). Given the heterogeneity of the target population in the real-world context, a solid knowledge of the target audience of RMMs in each country is necessary to guide the sampling strategy, including how the medicine is prescribed and dispensed. To draw conclusions on a sampling methodology’s efficacy in generating a representative sample, it is paramount that all elements of methodology are clearly stated and scientifically rigorous. The sampling strategy must be supported by sound and properly cited sources whose conclusions must be presented as supportive elements in the study documents.

What are some of the key concerns and challenges with RMM effectiveness studies?

Jouaville: Our recent review, which evaluated the sampling methodologies used in RMM effectiveness studies, showed that a minority of these studies provided supporting evidence to inform the theoretical framework for the sampling methodology. The following four elements of sampling methodology were found to be under-documented in RMM effectiveness studies:

  • Supporting documentation for country/region selection
  • Supporting documentation for specialty/sites selection
  • Description of the sampling frame used to source the sample
  • Comparison of characteristics of sample versus source population.

Researchers should clearly explain how they will proceed and document the evidence on which their sampling strategy will be based. Simply writing in a protocol that “the study sample will be representative of the RMM target population” is insufficient. Transparency as to the assumptions as well as the tools used to draw the sample (eg, sampling frame) will help the assessor effectively evaluate the representativeness of the final study.

What are the key guidelines for RMMs and their evaluation?

Jouaville: The EMA has two guidelines on RMMs:

As does the US Food and Drug Administration (FDA):

These guidelines have been updated recently. However, the importance of rigorous documentation of the sampling strategy has also been underlined in recent guidelines related to another research field, patient preference studies.2,3 This is reflective of a growing awareness across research fields.

Any additional comments?

Jouaville: The call for transparency in the presentation of study sampling methodology should not be limited to RMM effectiveness studies. Any study aiming to generalise its research finding to the whole population should consider the representativeness of its sample. Transparency in documenting the evidence to substantiate the sampling strategy is essential in assessing the relevancy and generalisability of the study. This would be applicable to, for example, studies evaluating the impact of regulatory intervention on the use of a prescribed medicine, as well as studies aimed at measuring the value of current clinical care of patients or patient preferences.

Sophie Jouaville, PhD, is an associate principal at IQVIA, where she works on the design and oversight of non-interventional real-world evidence (RWE) safety and health economics and outcomes research (HEOR) studies. She has worked with regulatory agencies and pharmaceutical companies for over 10 years. Before that she has been an independent scientific advisor. She holds a MSc in Public Health and a PhD in Biophysics and Molecular Biology. She also has been conducting fundamental research as an academic in several universities, with her last academic position held at Harvard Medical School.

About the author

Hannah Balfour is the Science Writer for European Pharmaceutical Review.


  1. Risk management plan [Internet]. Netherlands Medicines Evaluation Board (CBG-MEB) 2022 [cited June 2022]. Available from:
  2. European Network for Health Technology Assessment EMA. PREFER Patient Preferences. CHMP & EUnetHTA parallel Scientific Advice: Qualification of a Framework and “Points to consider” for method selection along with five methods for performing patient preference studies to inform regulatory and HTAbody medical product decision-making; November 2021. Available from:…
  3. US Food and Drug Administration. Patient-Focused Drug Development: Collecting Comprehensive and Representative Input Guidance for Industry, Food and Drug Administration Staff, and Other Stakeholders; June 2020. Available from: