External comparator studies leveraging real-world data (RWD) offer a promising avenue for supporting various regulatory objectives and evidence generation needs. While pursuing a RWD-derived external comparator study presents a unique set of challenges, particularly in regard to the robust justifications required to achieve regulatory acceptability, the rewards can be substantial. Successful implementation starts with a rigorous feasibility assessment, ensuring that the approach is not only scientifically sound but also strategically aligned with regulatory expectations. The process of determining the viability of an external comparator study is inherently multidisciplinary, requiring a cross-functional team executing assessments in three critical areas: regulatory, scientific, and data quality. By adopting this proactive approach, sponsors can mitigate risks and enhance the potential for regulatory success.

Challenges in conducting feasibility assessments

When conducting feasibility assessments for an external comparator, challenges with data custodian responsiveness and transparent reporting on data validity, quality assurance, and management often arise. Overcoming these challenges requires a systematic approach led by a strong cross-functional team. This includes experts in RWD strategy to ensure data compliance and governance; regulatory strategy to ensure adherence to FDA standards; epidemiology/biostatistics to implement appropriate study design and analytic methods; and data management to ensure data access feasibility, patient privacy and compliance. Given that RWD partners and sites are agnostic with regard to how their data can be used, a strong real-world team can facilitate identification of data partnerships that best work to achieve the sponsors' objectives. Through seamless collaboration with an experienced team, sponsors can confidently explore the viability of an external comparator approach to meet regulatory objectives.

Regulatory Feasibility: Understanding the clinical and regulatory landscape

Conducting regulatory feasibility assessment upfront saves downstream time and resources on data feasibility by identifying potential roadblocks early and allowing for adjustments to the clinical development program that better inform data source selection and curation. Regulatory feasibility assessment of an external comparator study relies on an in-depth understanding of the clinical and regulatory landscape in order to map key characteristics of the asset to regulatory standards and precedent set by historical analogs. For example, understanding the totality of evidence accepted by regulators in previous applications incorporating an external comparator approach helps inform additional confirmatory evidence streams for inclusion, such as literature reviews or safety data.

A critical output of regulatory feasibility assessment is regulatory justification: Why is a randomized controlled trial (RCT) not feasible? Is the primary endpoint able to be objectively measured in a real-world setting? Characterizing key program and asset features, such as the unmet needs or rarity of the disease, enables sponsors to demonstrate alignment with what regulators typically view as the ideal use case for an RWD-derived external comparator. This awareness of regulatory precedent serves to better anticipate regulator feedback and identify opportunities for innovative strategies.

Data Feasibility: Assessing RWD sources to characterize fit-for-purpose

Equipped with a clear understanding of the regulatory landscape, sponsors can then make a more informed decision on the suitability of RWD sources through data feasibility. Data feasibility assessment is a process for assessing whether a RWD source is fit for purpose by characterizing accessibility, availability, completeness, and suitability of a data source to address key research questions. A rigorous data feasibility process allows sponsors to more effectively justify to the FDA that it’s feasible to construct the comparator using RWD sources and why relevant data sources were selected or excluded from the study, as well as to demonstrate that these were not selected to favor particular study findings.

Data feasibility can also help sponsors make evidence-based decisions on how to adapt or modify their approach. For example, if a fit-for-purpose secondary data source is not identified, the sponsor may want to consider pivoting to primary data collection directly from patients and physicians.

While feasibility assessment is a widely adopted exercise, there are ways to maximize the utility of the results and reduce uncertainty. It is helpful to consider not just the availability and completeness of key study variables, but also how the variables are collected and at what frequency. A data feasibility assessment should be conducted with the end in mind, meaning it should provide a clear picture of patient counts and variable capture as well as provide necessary inputs for regulatory justification. This approach will help balance the burden on data partners and sites with the usefulness of responses and ultimately serve to mitigate risk to the external comparator program.

Engaging proactively with regulators

The feasibility assessment process, often in parallel with study design, culminates in regulatory interaction to achieve buy-in on an external comparator approach. The regulator interaction process, as part of a comprehensive regulatory strategy, should aim to obtain clear and useful feedback on questions to validate a regulatory objective. While it is important to ask the right questions, it is just as critical to provide adequate justification, data, and context for regulators to effectively opine on the questions they are being asked. This includes proactively anticipating questions that regulators might have, including why an RCT cannot be conducted, the potential for establishing exchangeability between cohorts, and the sufficiency of proposed design and methods. Robust regulatory justification gathered during the feasibility process will inform more efficient, transparent, and useful conversations with regulators on key study design and evidence strategy questions.

Identifying the most qualified team and partner for evidence generation

Feasibility assessment is a powerful and essential real-world study planning tool which informs the impact of RWE on the program strategy. Conducting a feasibility assessment extends beyond ticking a box; it plays a pivotal role in informing whether a RWD-derived external comparator approach is the most suitable method for addressing a specific research question and regulatory objective. In some cases, feasibility may reveal that an external comparator is not appropriate or the modifications to the initially proposed approach can enhance the validity and relevance of study outcomes.

Given the distinct considerations and complexities associated with implementing external comparators, feasibility assessment requires global reach to connect data partners and a flexible, tailored approach to accommodate diverse stakeholder needs. In the space where research and regulation intersect, IQVIA is uniquely positioned to support these needs throughout both feasibility assessment and study implementation. IQVIA provides comprehensive support for making informed, data-driven decisions regarding study design and regulatory strategy when navigating the intricate and evolving RWE landscape.