Important changes are occurring in the way pharmaceutical companies test and assign value to their existing drugs and those in the pipeline. With these changes come new challenges.

The old metrics, which the Regulatory Bodies, as FDA and EMA established and used for half a century to determine whether a drug can come to market, focused on safety and efficacy, as demonstrated in tightly regulated, randomized clinical trials.

Randomized Controlled Trials (RCTs), although recognized as the ‘gold standard’ for establishing efficacy, operate in an idealized environment and can only measure efficacy in limited populations. As such, they cannot provide a true indication of effectiveness - an area on which more and more knowledge is being sought.

According to a recent survey by the European Commission, an increasing number of countries revisit the relative efficacy and effectiveness of a new treatment in comparison to standard therapy as part of their decision making processes for reimbursement and pricing. This process takes place in addition to the EMEA assessment, and aims at evaluating the added value offered by a new treatment. With a number of countries now moving into reference pricing for new treatments without added medical value, this additional effectiveness assessment has a major impact on a new drug’s success in the market.

When health authorities were asked what data they use for effectiveness, most responded with an admission to basing it on RCTs, despite knowing that randomized clinical trial data does not represent effectiveness. Some institutions accept modeling approaches as a bridge from efficacy to effectiveness.

Real-life data can be obtained from sources that cannot be included in an RCT, and provide additional insights into areas such as epidemiology, or cross-data from a more naturalistic environment. Compliance, adherence and cost insights can also be obtained. This new real-world evidence (RWE) standard means that Pharma has to design messages about the old safety and efficacy standards, but they also need to consider how to build relationships with physicians, insurance company executives and consumers about this new approach. It requires a new way of speaking about economic outcomes, data mining and population studies.

In conclusion:

1) RCTs have many advantages and remain the gold standard

2) Decision makers looking to make coverage and payment decisions may rely on multiple   

    sources of real world data, as well

3) Benefits of Real World Data generation:

•     Effectiveness vs. efficacy
•     Multiple interventions
•     Long-term benefits and harms
•     Diverse population
•     Broader range of outcomes
•     Resource use
•     Dosing, compliance, adherence
•     When RCT not possible
•     Confirmatory of RCTs
•     Urgent, life-threatening situation
•     Interim evidence in absence of RCT

Real life effectiveness data can be collected in a number of ways, most commonly from:

• Databases: These include cross-sectional and longitudinal databases which essentially provide retrospective data but increasingly offer the opportunity to have prospective add-ins, e.g. on quality of life.

  Patient and population surveys: Primarily for epidemiological information.

• Patient chart reviews: Used to reflect particular insights in patient management.

• Observational data from cohort studies: What most people would understand by real life studies.

• Pragmatic clinical trials: Whether these are strictly “real-life” studies is open to debate. In a way they are simple experimental trials, which raise questions regarding the extent to which they reflect what is happening in real life. Efforts are however made to mimic a real life situation as much as possible.

• Registries: The use of registries - both large and small - is increasing. These involve registering and subsequently analyzing all patients treated at a particular centre for a particular condition on a continuous basis.