White Paper

Unlocking New Insights By Connecting Patient-Level Clinical Trial Data To Real World Data

Source: Medidata AI
GettyImages-1081869356 data

Clinical development teams are under continual pressure to create faster and safer interventions for increasingly complex diseases. Historically, regulators have relied solely on clinical trials to prove effectiveness and safety. Although clinical trials provide robust views of outcomes specified within study protocols, they are not always representative of the broader populations that exist in the real world.1 This means that the results of a clinical trial may vary across patient populations seen in routine clinical practice.2 Recent investigations into novel conditions such as Vaping Associated Pulmonary Injury or the intense speed of COVID-19 vaccine emergency use authorizations (EUA) have highlighted the need to bridge key evidence gaps in our existing clinical processes.3

Sponsors have started to bridge evidence gaps by connecting real world data (RWD) sources like electronic medical records (EMR), insurance claims, wearable devices, and genomics to clinical trials in order to understand real world outcomes. In response to this growing trend, regulators have passed key legislation and issued guidance to support RWD usage in regulatory decision making.4 Now, sponsors have a clearer path forward in using linked RWD and clinical trial data (CTD) at the patient-level to aid in regulatory decision making. These once disparate data sources can be combined to more holistically describe a patient’s healthcare journey. With innovative data linkage technologies like tokenization, researchers are beginning to gain a deeper understanding of patients’ diseases, treatments, and outcomes to close critical evidence gaps. Data linkage unlocks a new frontier in evidence generation where sponsors can finally monitor long-term safety, track patients lost to follow up (LTFU), improve commercial forecasting, and better demonstrate treatment effectiveness.


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