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In the Healthcare and Life Sciences industry, real-world evidence (RWE) refers to medical evidence generated from data collected outside of a clinical trial such as medical records, images, and claims. In recent years, RWE has garnered lots of attention for its ability to shed novel insights on the impact, safety, and effectiveness of new treatments. In fact, during the early days of the pandemic, RWE was critical in accelerating the roll-out of the vaccine.

Encouraged by the promise of RWE, organizations across the health ecosystem are investing heavily in RWE programs. Yet, most still struggle with technology challenges that are impeding their efforts to deliver the full benefits of real-world data. Recognizing these challenges, Databricks and Fierce Pharma surveyed over 100 biopharma executives to better understand:

  • What's driving investments in RWE programs
  • The top factors inhibiting and contributing to RWE program success
  • How to build the ideal data architecture to unlock business outcomes

This blog, along with the full research report, aims to provide pharmaceutical executives, real-world evidence teams, and the broader ecosystem of data professionals with insights on how they can build the right technology foundation and data strategy to drive the most value out of their RWE programs. Let's dive into a high-level summary of some of our findings!

Real-world evidence investments show no signs of slowing down

The debate about the value of RWE is over. Nearly all surveyed executives say their organization is investing in RWE programs 79% reporting that their organization is either extremely or very committed to their investments.

We followed up by asking executives about the motivating drivers behind their investments. Many perspectives were shared like accelerating speed-to-market and label expansion. As part of the survey, Harini Gopalakrishnan, Executive Director at Syneos Health, shared "the fact that the regulatory agencies are more open to considering real-world data is the biggest reason why a company might want to invest." The full report provides deeper insights on investment drivers, areas of business investing the heaviest, and the types of real-world data being adopted.

RWE investments are up, but are they paying off?

One of the key findings from the survey is that RWE programs are largely successful. In fact, 9 out of 10 pharma execs say that their RWE investments are delivering measurable business outcomes. But when we dug deeper, it was clear that the gap between best-in-class and moderately successful programs was huge. In fact, only 9% of companies consider their RWE programs to be extremely successful.

Findings suggest that the business argument for RWE has been won, but companies continue to face technical barriers to building world-class RWE programs.
Findings suggest that the business argument for RWE has been won, but companies continue to face technical barriers to building world-class RWE programs.

The findings suggest that the business argument for RWE has been won, but companies continue to face technical barriers to building world-class RWE programs.

Barriers to RWE success: it all starts with the data

So what's causing these roadblocks? The study uncovered that most challenges stem from the fact that RWE is generated from many different sources of data. Traditionally, companies have relied on different platforms to manage these diverse data sets leading to data silos and hurdles to building integrated evidence plans, ultimately preventing teams from making use of their real-world data. The detailed findings on the top challenges can be found in the full report.

So what does it take to be successful with RWE?

We asked executives the factors that contribute to successful programs—some focused on the people side (e.g. strong leadership support for RWE programs, internal RWE expertise), but the most dominant theme was the need for the right technical capabilities to execute their vision.

Based on this feedback, the discussion with the execs boiled down to a single question: If you could build the ideal data platform for RWE, what would you prioritize? These are the top 5 responses: one platform for all data, a unified set of tooling for all analytics and AI; the ability to easily share data, stronger governance and security; and open data standards (the full list available in the report).

These insights begin to shed light on what it takes to move from a moderately successful RWE program to best-in-class. To help organizations along that journey, we believe the Databricks Lakehouse closes the gap by uniquely addressing each of these required capabilities:

Top RWE platform needs
Top RWE platform needs

Built on Delta Lake, the Databricks Lakehouse Platform enables healthcare and life sciences organizations to store all of their real-world data - such as structured medical records and unstructured images - in the cloud for integrated evidence generation. The data is stored in an open format, free from data lock-in, and is easy to share with partners through Delta Sharing.

The Databricks Lakehouse provides a full set of analytics and machine learning capabilities in a single, collaborative environment so all personas from bioinformaticist to researcher to analyst can work together to explore real-world data. Finally, Unity Catalog along with HIPAA-based security, underpins these capabilities with data governance and security. Organizations like Sanofi are maximizing the value of their RWE programs with the Lakehouse, helping bring new life-changing treatments to patients in need.

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