What is Real World Evidence and why does it matter?

Austerity measures and related drug price cuts have put unprecedented pressure on the pharmaceutical industry. Manufacturers are being asked to provide information related not only to safety, appropriate use, and effectiveness but also clinical and economic value.

Although randomized clinical trials (RCTs) remain the gold standard of clinical tests, factors such as the heterogeneity in the response to the drug in real life, lack of adherence to treatment, or the use of medicines in patients different from those involved in the process of investigation prior to the authorization, limit the generalizability of results from randomized clinical trials.

Real World  Data have been fueled by new data technologies that leverage the valuable information contained in electronic medical records and personal information repositories.

This document is a review of those Real World Data sources and of the benefits that nowadays Pharmaceuticals and Life Sciences companies can derive from them.

Defining Real World Evidence

Probably, the most quoted definition of Real World Data comes from the area of pharmaco-economics. The ISPOR (International Society For Pharmacoeconomics and Outcomes Research) defines Real World Data as:

Data used for decision making that are not collected in conventional randomized controlled trials (RCTs)

In the sector, we often use the terms Real World Data and Real World Evidence almost  indistinctly. They are not exact synonyms yet. Data refers to factual information, whereas “evidence” implies the organization of the information to inform a conclusion or judgment. Data are raw materials.

For the FDA, whereas Real World Data is data collected from sources outside of traditional clinical trials, Real World Evidence is the evidence derived from aggregation and analysis of RWD elements. As a result, in between data and evidence, we place the necessary analytical processes that allow us to convert data into evidence.

An early case study of Real World Data: Beta blockers 

Years before the  birth of the term “Real World Data”, results from observational data lent vital support for the use of beta-blockers in patients who suffer a heart attacks. In the 1990s, the Cooperative Cardiovascular Project examined more than 200,000 patients who had suffered a heart attack (myocardial infarction). The project found substantial reductions in mortality among patients receiving beta blockers.

The Cooperative Cardiovascular Project significantly bolstered previous evidence from randomized clinical trials and helped accelerate the use of beta blockers in patients with heart attack as a standard practice.


Benefits of the Real World Data for the pharma industry and life sciences organizations

Investment in studies that demonstrate the real value of drugs can have many benefits for the pharma industry. Real World Data is the right tool to streamline the use of resources,  to listen to the authentic voice of patients and to facilitate collaboration between the pharmaceutical industry and the public sector.

In practice, the funding of Real World Data projects comes primarily from pharmaceutical companies. Government funding is significantly lower.

1. From effectiveness to efficiency

Decision makers in the health sector look for more information in the "real world" to evaluate the results on which to base their decisions.

The pharmaceutical industry is forced to provide evidence related not only to security, proper use, and effectiveness, but also to the clinical and economic value of their medicines. That is, to accept the distribution of a particular drug, the purchasing managers require evidence of cost-effectiveness, which is often accompanied by evidence of organizational, social and ethical implications of the contribution of the product.

2. Comparison of multiple alternative interventions

Real World Data allow you to compare many alternative research or clinical strategies (e.g., older vs. newer drugs) to inform optimal treatment options beyond the use of placebo as a comparator.

3. Wider range of patients

Most patients treated in health services are not eligible for randomized clinical trials because they are at an advanced age or suffer from comorbidities. As a result, the information derived from their attention is not recorded. Thanks to the Real World Data we have access to clinical outcomes in a diverse population that reflects the range and distribution of patients observed in clinical practice.

4. Long-term risks and benefits

Estimates of the evolving risk–benefit profile of a new intervention, including long-term (and rare) clinical benefits and harms.

In a 2009 study, they compared the effects of early and delayed treatment with budesonide, 13 years after the start of it by using Real World Data.

5. Voice of the patient. Patients reported outcomes

For pharmaceutical and life sciences companies, it is vital to listen and understand the feedback that their current and potential customers express through all kinds of channels and touch points. That is why brands are extending their Voice of the Patient initiatives to a new territory of unsolicited and unstructured content: comments on surveys, call center verbatims, Twitter, etc.

Our own text technology


  • MeaningCloud (meningcloud.com) is a semantic platform developed by sngular to analyze the feedback from patients at any touch point (email, call-center, surveys, social media). It manages their experience at all points of contact with the company.

  • TrendMiner (http://sngular.team/en/-/cases/trendminer) is a pharmaco-vigilance tool developed by s|ngular along with the research team LABDA of the Carlos III University in Madrid. It allows analyzing social networks and discussion forums about drugs, symptoms, conditions and diseases to extract valuable insights.

Adherence studies

Information on how a product is dosed and applied in clinical practice and on levels of compliance and adherence to therapy.

Randomized Clinical Trials vs. Real World Data

Test type: The results of many RCTs are not generalizable to a larger population while a rigorous observational study can be useful in certain situations, whenever possible biases have been adequately addressed.

Primary focus: RCTs of medicines focus on efficacy, safety, and quality as endpoints. RW studies consider a more contextualized parameter, which may be described as ‘effectiveness’.

Patient Population:  While RCTs illustrate the efficacy, safety, and quality of an intervention, their general exclusion criteria may produce studies in a narrow segment of the population only, leading to results with limited external validity.

Cost:  Large RCTs can cost many millions. RW data collection requires a much lower level of funding.


Source: Guidance Demonstrating Value with Real World Data: A practical guide. bit.ly/2csKZap