Real-world evidence (RWE) is rapidly transforming how clinical trials are designed, evaluated, and approved. In Phastar’s latest webinar, part of our new biotech-focused series, Principal Data Scientist Tasos Mangelis provided an in-depth look at the evolving RWE landscape, highlighting the opportunities, challenges, and practical applications of real-world data (RWD) in clinical development.
The Rise of Real-World Evidence
RWE has seen exponential growth in recent years, with studies registered on ClinicalTrials.gov surging since 2016, partly due to initiatives like the 21st Century Cures Act. Regulatory bodies including the FDA, EMA, MHRA, and PMDA are increasingly embracing RWE to support approvals, post-marketing surveillance, and label expansions. [1]
RWE is not a replacement for randomized controlled trials (RCTs), but a critical complement. While RCTs offer high internal validity, they do not always reflect how treatments perform in diverse, uncontrolled, real-world environments. This is where RWE bridges the gap. [2]
From Raw Data to Actionable Insights
The session outlined key real-world data sources, including electronic health records, insurance claims, registries, and wearable technology. Rigorous steps required to transform raw healthcare data into reliable evidence. These steps include:
- Ensuring data quality and standardization
- Representing relevant patient populations
- Handling missing or inconsistent data
- Building interpretable models that clinicians can trust
Without these steps, the utility of data science tools is limited and poor data quality leads to poor outcomes, so data curation is critical.
‘’Reliable data is the foundation upon which we can securely and safely analyze and produce correct and reliable evidence.’’
Case Study Spotlight: Predicting Diabetic Complications
The PRECARD project is a real-world application of predictive medicine. The tool helps clinicians identify patients with diabetes who are at high risk of kidney disease and retinopathy, two serious complications. [3, 4]
Using a dataset of 27,000 patients across 14 years, interpretable models were developed and deployed through a user-friendly web interface. The tool generates individualized risk scores and visualizations, helping clinicians triage care more effectively, particularly in the wake of pandemic-related backlogs.
Importantly, the study revealed a significantly higher risk of complications among African-Caribbean patients. This finding underscores the value of using RWD from diverse populations to uncover disparities that might be missed in traditional clinical trials.
Broader Applications and Looking Ahead
The PRECARD model is one example of how RWE can lead to more equitable and efficient healthcare. With expertise in claims data, registries, oncology, RWD-driven dashboards, and machine learning applications, Phastar is helping to lead the way in RWE innovation.
Our next biotech webinar, titled “Harnessing Bayesian Methods: Tackling Challenges in Rare Disease and Small Population Trials,” will take place on May 27.
References
- U.S. Food and Drug Administration. Considerations for the Use of Real-World Data and Real-World Evidence to Support Regulatory Decision-Making for Drug and Biological Products. Published August 2023. Available at: https://www.fda.gov/regulatory-information/search-fda-guidance-documents/considerations-use-real-world-data-and-real-world-evidence-support-regulatory-decision-making-drug
2. Phastar. The benefits of using real-world evidence in clinical research. Retrieved May 7, 2025, from https://phastar.com/knowledge-centre/blogs/the-benefits-of-using-real-world-evidence-in-clinical-research/
3. Mangelis A, Wijewickrama P, Nirmalakumaran A, Fountoulakis N, Vas P, Webster L, Mann S, Collins J, Hopkins D, Thomas S, Ayis S, Karalliedde J. People with type 1 diabetes of African Caribbean ethnicity are at increased risk of developing sight-threatening diabetic retinopathy. Diabetes Care. 2023 May 1;46(5):1091-1097. doi:10.2337/dc22-2118.
4. Mangelis A, Fountoulakis N, Corcillo A, Collins J, Vas P, Hussain S, Hopkins D, Gnudi L, Thomas S, Ayis S, Karalliedde J. African Caribbean ethnicity is an independent predictor of significant decline in kidney function in people with type 1 diabetes. Diabetes Care. 2022 Sep 1;45(9):2095-2102. doi:10.2337/dc22-0815.
