Trial designs using real‐world data: The changing landscape of the regulatory approval process

Abstract

Purpose: There is a need to develop hybrid trial methodology combining the best parts of traditional randomized controlled trials (RCTs) and observational study designs to produce real-world evidence (RWE) that provides adequate scientific evidence for regulatory decision-making. Methods: This review explores how hybrid study designs that include features of RCTs and studies with real-world data (RWD) can combine the advantages of both to generate RWE that is fit for regulatory purposes. Results: Some hybrid designs include randomization and use pragmatic outcomes; other designs use single-arm trial data supplemented with external comparators derived from RWD or leverage novel data collection approaches to capture longterm outcomes in a real-world setting. Some of these approaches have already been successfully used in regulatory decisions, raising the possibility that studies using RWD could increasingly be used to augment or replace traditional RCTs for the demonstration of drug effectiveness in certain contexts. These changes come against a background of long reliance on RCTs for regulatory decision-making, which are labor-intensive, costly, and produce data that can have limited applicability in real-world clinical practice. Conclusions: While RWE from observational studies is well accepted for satisfying postapproval safety monitoring requirements, it has not commonly been used to demonstrate drug effectiveness for regulatory purposes. However, this position is changing as regulatory opinions, guidance frameworks, and RWD methodologies are evolving, with growing recognition of the value of using RWE that is acceptable for regulatory decision-making.

Bridging the Gap Between RCTs and RWE Through Endpoint Selection

“…It is at this juncture that the healthcare industry is now recognising the potential of RWD as a source of clinically meaningful evidence for consideration by key industry decision-makers, including when embedded within traditional RCT assessments [ 5 , 6 ]. The value of RWE is attributed to the fact that data collection is undertaken for routine care and practice, making RWD creation essentially free of charge with the added benefit of being representative of typical patients, events and outcomes.…”

<p>Harnessing Real-World Data for Regulatory Use and Applying Innovative Applications</p>

“…20 From a regulatory perspective, RWE may now be used to support label expansion (including new indications, dosages, and patient sub-populations), to assess the feasibility of Phase IV studies, to provide evidence for products in an expedited approval pathway, to provide a historical control arm for clinical studies, and in pragmatic trials. 5 Indeed, there is a growing list of drug approvals and labelling changes that have utilized RWE and data from nontraditional study designs in their regulatory submissions. 21 For example, an expansion in the indication of palbociclib was supported by RWD from EHR and insurance claims.…”

“…4 RWE may be generated from different study designs or analyses, including randomized (non-controlled) trials, large simple trials, pragmatic trials (ie, trials that incorporate elements of routine clinical practice), and prospective or retrospective observational studies. 5 RWE can be derived from a variety of sources. Therefore, its use provides an opportunity to combine diverse datasets to provide a broader understanding than might be available through RCTs.…”

How to choose a time zero for patients in external control arms

“…Initial regulatory approval of novel oncology compounds could be based on such a single-arm trial [1,2]. However, to provide additional context to regulators, the sponsor has decided to construct an external control arm for the trial, using data retrospectively collected from an electronic health records system [3,4]. The sponsor will compare overall survival for patients in the external control arm to overall survival for patients in the single-arm trial, after reweighting to account for differences in patient characteristics.…”