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The Journey from Hesitancy to a Reliance on Real World Data

As recently as just a few years ago, drug developers across the globe were hesitant of using world evidence (RWE) when pre-forming the clinical analysis of an investigator product. The gold standard of investigative analysis to determine the efficacy and safety of a new investigational drug remained the randomised clinical trial. Karen Ooms at Quanticate explores the rise in the use of real RWE in the pharmaceutical industry in recent years and argues that the concept of harnessing data from real-life patients has finally come of age.

Extract:

‘The Journey from Hesitancy to a Reliance on Real World Data’

As recently as just a few years ago, drug developers across the globe were hesitant of using RWE when pre-forming the clinical analysis of an investigator product. The gold standard of investigative analysis to determine the efficacy and safety of a new investigational drug remained the randomised clinical trial.

However, many statistical consultants have for a long time argued the merit of using real world data (RWD) to help create more efficient trial designs and provide, potentially, even more reliable data to inform clinical trials.

The debate is ongoing. However, the COVID-19 pandemic has forced a new-found reliance on RWD. Sponsors and their CRO partners are seriously considering harnessing RWD to help the world overcome COVID variants and ensure new vaccinations for these variants get to market quickly and safely in the continuing fight against the global pandemic.

With this in mind, has the use of RWD and RWE finally come of age?

The drawbacks of clinical trials

While randomised clinical trials are a crucial feature of any drug development process, providing valuable information about both the performance and safety of an innovative drug candidate, they do present drawbacks. These limit their utility with regards to developing a full understanding of the real-life performance of new therapies.

For instance, they have narrow inclusion criteria, which often means that patients under concomitant treatments, with comorbidities or organ dysfunctions, or over a certain age limit are left out of studies. This is designed to reduce confounding factors and to produce data that is applicable to the average patient. However, in the real world, many of the patients taking the therapy will have other conditions that require treatment with other medications. Not including these means that it is impossible to gain a full picture of how the treatment will work.

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