Real World Evidence in Clinical Trials

RWE describes clinical evidence about the usage and potential benefits or risks of a medical product or practice. RWE is derived from the transformation, analysis, and interpretation of real-world data (RWD) for use in clinical, policy, payer, or other decisions.

RWE drives the differentiation of value against standard of care, comparable products on the market and new entrants. 

Early in the clinical trial planning process, RWE helps identify the appropriate patient populations, and utilizes RWD sources to support inclusion/exclusion criteria.

RWE empowers innovative trials. By combining site-based data with electronic health records and registry data, phase II/III hybrid trials can be conducted. RWE also enhances data from single-arm trials by utilizing external/historic controls. Furthermore, it allows for the creation of external control arms to validate more rigorous comparison to patients in active treatment arms. 

RWE is useful for drug approval because it allows for informed decision making at the right time and assists companies in meeting the expectations of regulators. By utilizing RWD, it enhances the pathway to regulatory approval, from integrated product development planning, through health authority engagement to regulatory submission. And it demonstrates value through evidence-based health economic evaluation and outcomes research.

Real world evidence (RWE) has become increasingly valuable in early-phase clinical trial planning, offering insights that can enhance study design, patient selection, and overall trial efficiency. In the early phases of clinical research, RWE can provide a more comprehensive understanding of the target patient population, disease progression, and current treatment patterns. This information, derived from sources such as electronic health records, claims databases, and patient registries, can help researchers identify potential challenges and opportunities before the trial begins. For instance, RWE can reveal common comorbidities or concomitant medications in the target population, allowing researchers to refine inclusion/exclusion criteria and anticipate potential safety concerns.

Furthermore, RWE can inform the selection of appropriate endpoints and outcome measures that are most relevant to patients and clinicians in real-world settings. It can also guide the identification of potential trial sites by providing information on patient distribution and treatment patterns across different geographic areas. This can lead to more efficient site selection and potentially faster patient recruitment. Additionally, RWE can help in estimating event rates and variability in the target population, which is crucial for sample size calculations and power analyses in early-phase trials. By leveraging RWE in these ways, researchers can design more targeted, efficient, and patient-centric early-phase clinical trials, potentially reducing costs and accelerating the drug development process.