What is Real-world data?
Real-world data, or RWD, is de-identified patient health information collected in ‘real’ settings, such as physician’s offices or other places where patients access care. The data are de-identified and accessible through various sources, like electronic health records, insurance claim databases, health monitoring devices, patient registries and directly from patients themselves.
While data from traditional clinical trials can help us understand the safety and efficacy of a medicine within the trial’s population and parameters, RWD can offer insights into how a medicine is used in the “real-world,” where those parameters don’t exist and variables can come into play. More broadly, RWD can also help build a deeper understanding of a particular disease and patient outcomes, all of which can help inform research of future potential treatments.
What is it not?
RWD is not data collected from randomized controlled clinical trials, which typically represent a specific population of people. While clinical trial data is critical – the gold standard – to understanding the safety and efficacy of an investigational medicine, it comes from a highly controlled setting. When trials conclude and medicines are approved for use, they’re used by patients and healthcare practitioners in settings that can be quite different from clinical trials.
Unlike clinical data, RWD is typically gathered from databases showing how drugs are prescribed and used outside of the clinical trial setting. The sheer volume of the large data sets can help complement clinical trial results and provide additional insights about use beyond what a trial was designed to answer or other information that emerge as medicines are more frequently used over time.
How can it be useful?
We are really just starting to tap into the potential of RWD and it’s already been used in a variety of ways to benefit patients. RWD allows us to take aggregate feedback from patients and existing data through collaborations with other companies to inform and adapt our clinical trial designs and protocols to better suit patient needs. Not only does RWD help inform clinical trial design but also allows us to accelerate and inform patient recruitment to ensure the right people are getting into the right trials to get the most relevant results. Beyond clinical trials, what’s even more useful, is truly understanding how our medicines are working in the real-world because at the end of the day a patient’s everyday life is likely nothing like a controlled clinical environment.
We have come a long way in how we use data. Only a few years ago, most of the analyses researchers conducted to assess results against study objectives were done retrospectively. Imagine the difference for patients if we make these correlations in real-time. Through the Food and Drug Administration’s (FDA) support of RWD as a tool for assessment, we’ve already seen great strides in the pace at which therapies are approved and ultimately reach our patients.
While RWD has many potential benefits, there are also limitations. It cannot be used on its own to demonstrate efficacy and safety, or prove causality. Analyzation can only take a deeper dive into associations and causality; and not all companies use the same tools and methodology in collecting data, which can lead to uncertainty with both the analysis and making decisions based on the outcomes.
Past, Present, Future
Ultimately, collaboration makes all of this possible. It is only through partnership that the value of RWD is realized and that the collection, collation and analysis of RWD can take place.
Even with its limitations, the benefits of RWD are undeniable and the future implications of its use seem unlimited. New emerging technologies that could potentially enhance its use and application are emerging faster than ever. We’re focused on working with our partners and opening up channels to realize the full potential of RWD with one common goal: bringing people the treatments they need faster.