Leveraging RWE for post-pandemic healthcare: leveraging real-world data to accelerate drug development

The Covid-19 pandemic has impacted nearly every industry, with healthcare arguably experiencing the most dramatic change. Before the pandemic, most of us had never imagined having a routine doctor's visit via telemedicine, or having an entirely new vaccine developed, tested, and authorized for emergency use in less than a year. The urgency of the pandemic has forced medical scientists and researchers to get creative and quickly develop new treatments.

How the pandemic is changing the possibilities for RWE

The value of real-world evidence (RWE) and real-world data (RWD) quickly became apparent and is critical to understanding the safety and effectiveness of vaccines. The U.S. Food and Drug Administration (FDA) issued RWE guidance documents in response to the pandemic and funded and launched projects to support Covid-19 research through RWE and Platform Research. As a result, the vaccine development process that typically takes 10-15 years is compressed to less than one year, allowing patients to quickly obtain an FDA-approved vaccine that meets rigorous testing standards.

Almost overnight, RWE went from a “must-have” addition to clinical trials to a core element of the drug development process. This pandemic-induced change is here to stay: Last year, 82% of FDA submissions included RWE, and the agency approved 15% more drugs based on RWE submissions in 2024 than the previous year. The FDA has provided pharmaceutical companies with a checklist to follow when incorporating RWE and updated its website with more information and guidance, signaling RWE's permanent role as a key innovation driver.

As RWE continues to influence the future of drug development, pharmaceutical companies will inevitably encounter obstacles. But with the right approach, these difficulties can be overcome, unlocking key insights and delivering better treatments to patients faster.

Challenges of working with RWE

Despite the promise, pharmaceutical companies still face three systemic barriers to realizing the full potential of RWE.

1. Data ingestion and coordination issues. Acquiring data sources is not just a huge financial investment; It also requires a significant investment of time. After pharmaceutical companies purchase these data sources, they need to spend a lot of time preparing this data for analysis. Data from disparate sources (with different schemas) can create coordination challenges, slowing time to insight and delaying the drug development process.
2. Privacy restrictions and inconsistent local data access rules. Pharmaceutical companies often purchase data under strict usage restrictions that are limited to certain geographies, indications, or time periods. Often, they must manually ensure that data is used correctly within these constraints, which can significantly slow down cross-site analysis and hinder global collaboration.
3. Traceability challenges. Despite regulatory requirements, ensuring traceability from data source to analysis remains an ongoing challenge. To meet this standard, pharmaceutical companies need appropriate pipelines to support reproducibility, and all analyzes should be performed in a validated toolset rather than in a local notebook on a developer's laptop. When the drug development process is not traceable, pharmaceutical companies are more vulnerable to regulatory risks and face slower approvals.

Maximizing the impact of RWE requires the right tools and methods

As RWE becomes increasingly important in drug development, pharmaceutical leaders must invest in interoperable platforms that enhance reproducibility and provide teams with real-time insights. One approach they might take is to transition from static PDF-based RWE reports to more interactive, model-enabled tools and platforms.

What does this look like in practice? Pharma stakeholders can use interactive dashboards to instantly update analytics, rather than having to wait for developers to rerun code to see slightly different analytics. Additionally, because all analysis is done by the system (rather than by individual developers working in local notebooks), it has the added benefit of built-in quality control, governance, and reproducibility.

This benefits pharmaceutical companies in the following ways:

• Improve what-if agility Ultimately, decision-making is accelerated by enabling clinicians to test niche subpopulations in the field.
• enhance trust Let stakeholders quickly and easily understand how to conduct analysis.
• Provide a single source of truth Sources of conflict that slow progress are reduced in the form of dashboards that everyone can see.
• Simplify compliance By providing regulators with data (rather than documents) available for review—including everything from visualizations to underlying code—all in one place.

Final Thoughts on Leveraging RWE for Post-Pandemic Healthcare

To have the best chance of success with RWE, pharmaceutical companies should “begin with the end in mind.” This means designing the study with the assumption that RWE will indeed be included in the submissions and incorporating this into the statistical analysis plan from the outset.

It’s also important to inventory and prepare the data sources needed to support this, and start building the right technology stack early. Finally, pharmaceutical companies should communicate with regulatory agencies as early as possible to obtain guidance on their approach. The pandemic may be five years old, but the speed, agility and impact it has unleashed through RWE must define the next decade of drug development.

Photo: ChatGPT

This article appeared in Medical City Influencers program. Anyone can share their thoughts on healthcare business and innovation on MedCity News through MedCity Influencers. Click here to learn how.