Throughout the development, regulatory review, and clinical use of medical products, a wide and increasingly diverse amount of data contribute to the scientific body of evidence around each drug, biologic therapy or device. The traditional cornerstone for each product is the randomized controlled trial (RCT), which is considered the gold standard for developing evidence to support the Food and Drug Administration’s determination that a medical product is safe and effective for its intended use. However, RCTs are increasingly time and resource intensive and do not readily assess long-term outcomes, the product’s effectiveness in different practice settings, the manner in which the approved product is used by prescribers and their patients, or the benefits and risks to populations not adequately represented nor observed in the trial.
Real world data and evidence (RWD and RWE, respectively) hold great potential for filling these gaps in knowledge. Data from electronic health records, payer claims, and patient registry databases, for example, can be harnessed to further refine clinical practice guidelines and treatment decisions. Evidence derived from such data could be utilized to better characterize a product’s clinical outcomes in more diverse, real-world patient populations. Pursuing these more robust and systematic applications for RWD and RWE will require collaborative action to improve data collection, analytical methods, and shared data infrastructure.
Working together with researchers and clinicians in the Duke community and leading experts from across the healthcare landscape, Duke-Margolis aims to improve the development and application of RWD and RWE to improve patient care through the following major projects:
Adding Real-World Evidence to a Totality of Evidence Approach for Evaluating Marketed Product Effectiveness
Understanding the Need for Non-Interventional Studies Using Secondary Data to Generate Real-World Evidence for Regulatory Decision Making, and Demonstrating Their Credibility
Incorporating Evidence from Clinical Experience in Regulatory Decision-Making: A Pragmatic Approach to Randomization in the Clinical Setting