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Debra E. Irwin, PhD, MSPH, Amanda Kong, DrPH, and Natalie Schibell, MPH
Delivering Defensible Evidence in a Complex Regulatory and Scientific Landscape
As the role of real-world evidence (RWE) expands across regulatory, health technology assessment (HTA), and payer decision-making settings, expectations for methodological rigor have intensified. The complexity of the current environment reflects multiple factors, including stricter regulatory standards for RWE submissions, growing scrutiny of real-world data (RWD) quality and relevance, the variability of available data sources, and the increasing need for transparent and reproducible methods. Regulatory bodies such as the Food and Drug Administration (FDA), European Medicines Agency (EMA), and Pharmaceuticals and Medical Device Agency (PMDA)—as well as HTA agencies globally (e.g. National Institute for Health and Care Excellence (NICE)—have reinforced that for RWE to inform regulatory or reimbursement decisions, it must be scientifically valid, fully documented, and independently reproducible. High-quality decision-grade real-world RWE does not lie solely in the research's chosen data source, but also in the strength of the study design, analytical execution, and reproducibility.
Aetion Evidence Platform® (AEP) was designed to help life sciences organizations meet these evolving, rigorous standards for regulatory-grade evidence. AEP powers a suite of applications that operationalize epidemiologic best practices, including causal inference methods within a structured analytic environment that prioritizes transparency, consistency, and reproducibility. These capabilities support the generation of evidence for regulatory submissions, post-marketing requirements, and payer engagement.
A Foundation in Epidemiologic Best Practices
The use of RWE to support regulatory decisions related to product effectiveness and safety requires that RWE study designs, methods, and data sources are fit-for-purpose. The SPIFD2 framework (Structured Process to Identify Fit-for-Purpose Study Design and Data), developed by Gatto et al. (2023), provides a rigorous, step-by-step approach for designing decision-grade comparative epidemiologic studies.
Authored by Aetion scientists, SPIFD2 integrates two earlier frameworks—SPACE (Structured Preapproval and Postapproval Comparative Study Design Framework) and SPIFD (Structured Process to Identify Fit-for-Purpose Data)—to streamline study planning and clarify its alignment with regulatory expectations. To support reproducibility, it emphasizes transparency in study design decisions and incorporates structured documentation practices, such as the pre-existing STaRT-RWE (Structured Template and Reporting Tool for Real-World Evidence) tables.
Key steps in the SPIFD2 framework include:
- State the research aims, research questions, and study objectives
- Describe the hypothetical target trial (HTT)
- Describe the RWD study emulation of the HTT
- Identify fit-for-purpose RWD sources
- Document final real-world operationalization, rationale, validity concerns, and approaches to address the concerns.
Once a fit-for-purpose study has been designed and a protocol written, protocol implementation can proceed within AEP using Aetion® Substantiate. Substantiate supports protocol-driven workflows by operationalizing the specified epidemiologic methods, including active comparator study designs, control of potential confounding variables, and alignment of exposure and outcome timing within a governed analytic environment. The study protocol defines the scientific approach; Substantiate ensures consistent, transparent execution.
Enforcing Protocol Discipline and Scientific Reproducibility
Aetion embeds methodological safeguards directly into our RWE analytics platform to meet regulatory and HTA expectations for scientific validity, transparency, and reproducibility. These safeguards include protocol-driven workflows, standardized application of epidemiologic methods, transparent construction of exposures and outcomes, tamper-proof audit trails of all analytic decisions, and diagnostic outputs that facilitate internal and external review.
Substantiate plays a central role in this structure. Through Substantiate, researchers apply predefined scientific methods specified in the study protocol, such as active comparator designs, control of confounding using propensity score matching and inverse probability weighting, and temporal alignment of exposures and outcomes. Each analytic step is governed, documented, and auditable, ensuring adherence to regulatory-grade scientific standards.
An enterprise-wide, structured execution environment strengthens the credibility of RWE generated through AEP, enabling life sciences organizations to deliver decision-grade evidence suitable for regulatory submissions, HTA reviews, and payer engagement.
From “Interesting” to “Decision-grade” RWE and What Sets Aetion Apart
While many platforms offer analytic flexibility, few provide the structured workflows to conduct protocol-driven studies to meet regulatory and HTA standards.
Table 1: Pillars of Decision-Grade RWE with Aetion
Structured and flexible, AEP was built to provide researchers with a tool to conduct rigorous, regulatory-grade studies with complete documentation and transparency.
Building the Future of RWE on a Scientific Foundation
As regulatory expectations evolve, sponsors prioritizing scientifically rigorous RWE generation will be better positioned to secure approvals, demonstrate value, and maintain stakeholder trust. Aetion equips scientific and regulatory stakeholders with the tools to meet that challenge. AEP integrates methodologically enforced workflows, implementations using causal inference methods, and transparent structured documentation to uphold scientific integrity from study design through results generation.
In an environment where trust drives access and speed matters more than ever, Aetion enables life sciences teams to deliver timely and trusted RWE.
Ready to elevate your RWE with Aetion’s proven framework?
Contact us to schedule a scientific consultation and explore how Aetion can support your evidence-generation program or next submission.