What’s holding back Real-World Evidence and how to fix it

By Prof. Dr Thomas Wilke, expert trainer of the Generating RWE for Optimising Market/Patient Access course.

Real-World Evidence (RWE) has become a cornerstone of modern drug development and access strategy. Regulators, HTA bodies, and payers now expect real-world data to complement randomised controlled trials (RCTs) — providing insights into how treatments perform across diverse, everyday populations.

However, transforming real-world data (RWD) into credible, decision-relevant evidence remains challenging. Across industry functions — from Market Access to Medical and HEOR — teams frequently encounter the same obstacles: fragmented data, methodological bias, long timelines, and inconsistent global approaches.
 

1. Accessing and Combining the Right Data

Even in data-rich healthcare systems, relevant RWD is often dispersed across claims databases, electronic medical records (EMRs), and registries. Each source provides value, but also has limitations:

• Claims data offer broad coverage and cost information but limited clinical detail.
• EMRs capture clinical granularity but typically reflect a single site or network.
• Registries track disease-specific outcomes but for narrow patient groups.

No single source tells the full story.

The solution: Careful database selection and, in some cases, linked data studies, combining claims, EMR, and other data.
 

2. Minimising Bias and Strengthening Validity 

Bias remains the most frequent reason why RWE results face scepticism, specifically comparative studies. Differences in patient characteristics, confounding factors, or incomplete data can undermine study credibility.

Modern approaches such as trial emulation frameworks are changing that. By designing RWE studies that mirror randomised trial principles — with defined inclusion criteria, index dates, and censoring rules — researchers can substantially improve internal validity while maintaining external validity. Techniques like propensity score matching, inverse probability weighting (IPW), and regression adjustment further balance patient groups and enhance comparability.

The future of RWE lies not just in access to data but in methodological transparency, ensuring results are both scientifically robust and reproducible.
 

3. Aligning Global Consistency with Local Relevance

Pharma companies face a growing tension between global evidence plans and country-specific HTA expectations. Agencies such as NICE, HAS, and G-BA may request different comparators, populations, or endpoints, creating duplication and inefficiency.

A coordinated evidence-generation framework, supported by shared platforms and aligned analytic standards, helps teams deliver RWE that is globally coherent yet locally defensible — a key success factor under Europe’s new Joint Clinical Assessment (JCA) process.
 

4. Reducing Timelines and Staying Current

RWE timelines can stretch as data collection, cleaning, and validation take months or years, often outpacing evolving standards of care.

Forward planning and dynamic data access are essential. Using pre-approved database partnerships and ongoing “living” evidence programmes allows organisations to refresh analyses continuously rather than start from scratch each time.
 

RWE is now central to demonstrating real-world value, optimising access, and informing lifecycle strategy.

By addressing data, bias, and operational challenges head-on, organisations can transform RWE into a competitive advantage.