Jaclyn Bosco- VP & Global Head, Epidemiology, Real World Solutions, IQVIA; Marni Hall- VP & Global Head, Regulatory Science & Strategy, Real World Solutions, IQVIA.
The importance of using real world evidence (RWE) for efficacy has gained significant momentum over the past few years as regulators are increasingly calling for the use of real-world data (RWD) and RWE. Regulatory bodies across the world, including the U.S. Food and Drug Administration (FDA) and the European Medicines Agency (EMA), have released guidance to clarify their expectations for the use of RWD and RWE for regulatory decision-making.
RWE can be used as supportive evidence to complement findings from randomized clinical trials (RCTs), and there has been a growing number of positive decisions where RWE, used during the drug development phase, contributed to the substantial evidence. There are many ways RWE and RWD can enhance and supplement clinical development. A few examples of how RWE and RWD enhances and optimizes clinical trials include RWD-driven protocol feasibility and optimization, data-driven site selection and patient enrollment, more patient-centric/decentralized approaches, leveraging non-identified imaging or genomic data to identify the right patient population, use disease registries for patient recruitment, or innovative extension studies to gather long-term outcomes in new ways. RWE can also be used to provide additional information and context for better decision-making.
RWE Approaches to Support Regulatory Decisions
RWE has been used to support drug approvals using an external comparator to a single-arm trial (SAT), in which the use cases have primarily related to therapeutic products for rare disease or oncology settings. This is especially the case where there is a high unmet need and it is unethical or not feasible to assign a parallel control arm, and effect size is large (FDA, 2018). For instance, in 2017, the FDA approved an immunotherapy drug which used RWE from a retrospective analysis of patients with the disease to complement data from a multicenter phase 2 trial. In 2018, the EMA approved a new CAR-T cell therapy which utilized RWE as a comparator arm to confirm data gathered in a SAT. In February 2023, the FDA released a new draft guidance for externally controlled trials, which, in part, addresses the potential role of RWE in these studies.
Pragmatic trials are another real-world approach that randomizes patients to the treatment of interest or to standard of care and then follows them under real world conditions to evaluate effectiveness in broader populations than are typically included in RCTs. As an example, in 2021, the FDA approved a label expansion for a bi-annual schizophrenia treatment, which used a pragmatic trial design. Regardless of the RWE approach, the FDA has outlined an RWE framework with three criteria (a) are the RWD fit for study purpose, (b) is the trial or study design likely to provide adequate and well-controlled scientific evidence to answer or help answer the regulatory questions, and (c) does the study conduct meet FDA regulatory requirements?
Determining When RWE is Fit-For-Purpose
Identifying quality data sources that will meet regulatory requirements can be challenging. In the FDA’s draft guidance on data standards, there is a strong emphasis on data quality from the point of collect and curation to research analyses. Due to the wide variety of RWD sources, challenges arise due to inconsistent data formats and standards and governance requirements depending on the country or region of origin. There may also be missing data or differing use of vocabulary or coding systems that can make standardization difficult.
When using RWD there are important considerations for selecting the optimal data source and determining whether the data are fit-for-purpose by applying a rigorous evaluation of the appropriateness to use a given database. The reliability and relevance to the research questions must be established. When selecting the optimal database, researchers using RWD need to ask questions about the data provenance – where did it come from, who recorded it, why was it recorded, who is represented, how many years does it cover, is there a lag between data recording and data availability?
It is also important to understand whether the data are accessible and if so, what the process is to access the data and ethics approval, and whether there are any restrictions for third party access. Finally, the curation process of the data can be learned by obtaining a data dictionary that includes coding systems and understanding what verification and validation checks are performed are essential. In terms of determining the fitness of the data, there are frameworks such as the Structured Process to Identify Fit-for Purpose Data (SPIFD) that can be applied as it is a systematic process to identify fit-for-purpose data (Gatto et al., 2022).
What This Means Moving Forward
The opportunities to advance disease research and drug development are growing with the global increase in expanded use of RWE by regulatory bodies. The rich repository of RWD available coupled with rapidly evolving technologies, and novel study designs, enables more innovative ways to consider evidence generation for regulatory decision-making. The fitness of RWD for the specific study question must be evaluated and there is a need to distinguish when RWE is intended to be used for substantial evidence or supportive evidence. The requirements for substantial evidence are no different than they have been before, and the fit-for-purpose data feasibility assessments need to be transparent regarding data provenance, access, curation, and linkage as well as communicating and discussing with regulators early and often are essential. The use of RWD and RWE can enhance drug development and enable advancements in treatment options for patients.
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