Built for Scientific Rigor: How Datavant Delivers Methodologically Defensible Real-World Evidence

This post was originally published on the Aetion blog and has been republished here on the Datavant blog.

By Debra E. Irwin, PhD, MSPH, Amanda Kong, DrPH, and Natalie Schibell, MPH, formerly of Aetion.

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 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 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.

Datavant’s real-world evidence platform was designed to help life sciences organizations meet these evolving, rigorous standards for regulatory-grade evidence. The platform 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 Datavant 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 real-world data (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 and protocol have been developed, the protocol can be implemented in the platform through protocol-driven workflows. These workflows operationalize 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. While the study protocol defines the scientific approach, our RWE platform enables consistent and transparent execution.

Enforcing Protocol Discipline and Scientific Reproducibility

Datavant 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.

With the help of the platform, 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 on the platform, 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 Datavant 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 Datavant 

Structured and flexible, our RWE platform 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. Datavant equips scientific and regulatory stakeholders with the tools to meet that challenge. Through the platform, users can integrate 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, Datavant enables life sciences teams to deliver timely and trusted real-world evidence.

Ready to elevate your RWE with Datavant’s proven framework?

Contact us to schedule a scientific consultation and explore how Datavant can support your evidence-generation program or next submission.