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Real World Evidence Blog

Real World Evidence in Pharma: 5 minutes with ... Clare Hague

This aritcle first appeared on The Evidence Base on 26 November 2021

In this ‘RWE in pharma’ interview series, we [The Evidence Base] are putting various pharma experts in the spotlight and asking them to share their insight on how their industry has traditionally employed real-world evidence (RWE), how they envision this changing over the next few years and what their predictions of the impacts of the highly anticipated US FDA RWE Framework may be.

This instalment features Clare Hague, EMEA Therapeutic Area Market Access Leader at Janssen (Beerse, Belgium).

Please could you introduce yourself, your organization(s) and tell us more about your role?

I’m Clare Hague. I work for Janssen, the Pharmaceutical Companies of Johnson & Johnson (Beerse, Belgium). We focus on improving the lives of patients by developing innovative treatments for the following areas of medicine: cardiovascular and metabolism, immunology, infectious diseases and vaccines, neuroscience, oncology and pulmonary hypertension.

The purpose of my role, as the Therapy Area Market Access Leader for Hematology, is to ensure timely patient access to our treatments throughout the Europe, Middle East and Africa (EMEA) Region. This is done through forging strong and trusted partnerships with our global, regional and local cross-functional colleagues, alongside external stakeholders, such as patients, regulators, health technology assessment (HTA) agencies, payers, prescribers and policy makers. Our common goal is to improve the outcomes that matter most to patients. Collaboration allows us to generate high-quality research studies that meet the evidence requirements of HTA agencies and payers, which helps to secure speedy patient access to our treatments.

What are the main ways real-world data (RWD) and RWE have traditionally been – and are currently – used by pharma?

We use RWD/E in a number of different ways, some of which are listed below:

  • to describe the epidemiology of disease and better define the unmet need for new therapies
  • to help explore the feasibility of undertaking, and improve the efficiency of, clinical trials
  • to generate synthetic control arm cohorts to estimate relative efficacy and safety to contextualize this type of data from single arm (non-comparative) studies
  • to generate the necessary data to inform financial and outcomes-based managed entry agreements (MEAs)[1]

RWD/E has evolved with advances in science, leading to the development of personalized medicines and a focus on developing effective treatment options for rare diseases.[2] This has resulted in pharma needing to invest in RWD/E in cohort and other studies to supplement their more traditional evidence packages.[3] We are also observing an increase in the number of new treatments where regulatory approval has been granted on the basis of data from single arm studies.[4] In this scenario, where it is not appropriate or feasible to perform randomized controlled trials (RCTs), pharma must either generate de novo RWD/E or leverage existing RWD/E. This is to estimate the relative efficacy of a new treatment and to meet the evidence needs of both regulatory and HTA agencies.

There is a clear distinction between RWD/E, as the FDA states: “Real-world data (RWD) are data relating to patient health status and/or the delivery of health care routinely collected from a variety of sources. Real-world evidence (RWE) is the clinical evidence about the usage and potential benefits, or risks of a medical product derived from analysis of RWD”.[5]

We are also making a crucial transition towards value-based healthcare, where healthcare is less about quantity and more about the quality of care delivered (outcome-focused) for a given financial investment. RWD/E plays an important role in the measurement of cost and clinical/patient and payer-relevant outcomes to support value-based healthcare.[6]

Do you think trust in RWE is increasing? What steps need to be taken to build this?

Trust in the conclusions drawn from RWE is increasing,[4] but may improve further if steps are taken to ensure the following points.

On a study level:

  • Data variables are clearly defined and standardized
  • Quality checks are in place to ensure completeness and accuracy
  • Clinically relevant and patient relevant data are captured to ensure observed differences or variability between patients and hospitals can be explained to aid interpretation
  • Appropriate analytic techniques are employed to test given hypotheses


On a health system level:

  • Further investment in data infrastructures is needed to improve the usability of RWE. A great amount of data are captured, but the fragmented nature of data sets across different hospitals and countries means the potential value of information is often not fully exploited
  • Quality assurance systems play a critical role in engendering trust
  • The feedback loop needs to be completed; if staff members are spending time capturing data, they need to see how these data are helping to improve knowledge and understanding of:
    • Patient care and outcomes
    • Healthcare efficiencies
    • Health services research

It is important that assurances are made – and explanations are given – about how RWD from patients are used to alleviate concerns from patients about confidentiality and intended use.

Growth in the successful formation of private–public partnerships that help accelerate the answering of key research questions may also improve trust.

How do you see pharma’s use of RWD/E changing over the next 5 years?

I envisage heightened levels of interest and investment in RWD/E over the next 5 years, coinciding with scientific advances, increased use of technology (digital, wearable devices, etc.), greater regulator acceptance of RWD/E, HTA agencies, payers, patients and prescribers, and the evolution of certain diseases that are limited to being studied using RWD/E. I also see patients playing a much greater role in deciding the treatments best for them and facilitating the capture of RWD/E through wearable technology.

Over the next 5 years, I anticipate database owners and hospitals seeing greater value in moving towards federated data networks across Europe. This is where RWD/E data from databases and hospitals in different countries are pooled using a common data model (OMOP), thus enabling faster and more efficient RWE studies.[7] Speed is an attractive advantage of RWD/E over conventional RCT data. Janssen has been the European Federation of Pharmaceutical Industries and Associations (Brussels, Belgium) leading partner on European Health Data Evidence Network (EHDEN) and the company is also pioneering their own federated data network called the Haematological Outcomes Network in Europe (HONEUR). The aim is to improve knowledge and understanding of hematological malignancies and improve outcomes for patients across Europe.[8],[9]

How do you think the COVID-19 pandemic has affected this trajectory and view of the value and usability of RWE/RWD?

RWD/E has played a critical role in better understanding the impact, and management, of the COVID-19 pandemic. The pandemic has illustrated the value of RWD/E in mapping out the trajectory of disease spread and patient outcomes. It has also helped to accelerate knowledge and understanding of the most effective management strategies for patients with COVID-19 in intensive care. Learning from experiences in different countries has also been enabled through RWD/E.[10]

What global implications do you think the US FDA RWE Framework – due to be published later this year – will have on pharma’s use of RWE?

The FDA’s RWE Program will focus on exploring the potential of RWD/E to support regulatory decisions about product effectiveness. Specifically, the FDA’s RWE Program will evaluate the potential use of RWE to support changes to labeling about drug product effectiveness. These changes include adding or modifying an indication, such as changes to dose and administration; adding a new population; comparative effectiveness or safety information. As such, this represents a significant shift in how the FDA has historically considered the role of RWE.[1]

The framework will include consideration of the following:[1]

  1. Whether the RWD are fit for use
  2. Whether the trial or study design used to generate RWE can provide adequate scientific evidence to help answer the regulatory question
  3. Whether the study conduct meets FDA regulatory requirements (e.g., for study monitoring and data collection)

Elevating the role that RWE plays in enhancing traditional regulatory data will probably result in a renewed focus on further building RWE capabilities and increasing investment in RWE studies. Pharma companies will need to plan ahead to ensure they design RWE studies thoroughly to support their products and have the relevant in-house expertise to oversee the studies, in collaboration with external data partners. When collaborating, pharma will want to identify appropriate high-quality data sources to enable robust and effective studies. This can be achieved either through partnering with external data providers or through developing bespoke registries.

This aritcle first appeared on The Evidence Base on 26 November 2021



[1] RWE Navigator. Impact of RWE on medicines re-assessment by HTA agencies. Last accessed 13 October 2021

[2] Miksad RA, Samant MK, Sarkar S et al. Small but mighty: the use of real-world evidence to inform precision medicine. Clin. Pharmacol. Ther. 106(1), 87–90 (2019).

[3] Katkade VB, Sanders KN, Zou KH. Real world data: an opportunity to supplement existing evidence for the use of long-established medicines in health care decision making. J. Multidiscip. Healthc. 11, 295–304 (2018).

[4] Patel D, Grimson F, Mihaylova E et al. Use of external comparators for health technology assessment submissions based on single-arm trials. Value. Health. 24(8), 1118–1125 (2021).

[5] Real-World Data: Assessing Electronic Health Records and Medical Claims Data To Support Regulatory Decision-Making for Drug and Biological Products. US Food and Drug Administration, MA, USA, 2021.

[6] Roberts MH, Ferguson GT. Real-world evidence: bridging gaps in evidence to guide payer decisions. Pharmacoecon. Open. 5(1), 3–11 (2021).

[7] IQVIA. OHDSI/OMOP Services: empowering common data standards for faster, reliable analytics. Last accessed 13 October 2021

[9] HONEUR. What is HONEUR. Last accessed 13 October 2021

[10] Naidoo P, Bouharati C, Rambiritch V et al. Real-world evidence and product development: opportunities, challenges and risk mitigation. Wien. Klin. Wochenschr. 133(15–16), 840–846 (2021).