The use of real-world data (RWD) is already common in post-launch observational studies. Data extracted from health records, medical claims, billing databases, medical registries, patient-generated data, mobile devices and other sources are an established way to enhance understanding of drugs that are already on the market.
As our experience grows, so do the opportunities we see to extend the use of RWD to answer both safety and effectiveness questions. Not only in observational studies, but also in randomised trial settings (pragmatic trials). But the question is how to transform RWD into a key source of evidence in a drug development programme?
Advances in the use of RWD sources further fuel the potential for real world research. Notable among these is the mining of structured and unstructured data in electronic medical records. Combined with natural language processing, mapping and integration with other RWD sources, this creates unprecedented opportunities. Registry-based trials and trials within cohort approaches are driving the feasibility, affordability and validity of large programmes with increasingly international reach.
As RWD will progressively need to include Patient Reported Outcomes (PROs), the future of clinical research will be increasingly characterised by blending clinical data and PROs, including the use of smart applications and other digital media.
This step-change from real-world data to real-world evidence involves more than including RWD earlier in drug development. Besides ensuring the best data for a particular study, turning RWD into RWE involves having a thorough understanding of the methodology and the data science required. Our methodological expertise ensures the correct design choices are made at the outset. This, combined with our operational expertise, delivers the required evidence.
