The forces shaping regulatory expectations in genomics-driven pharma

Regulatory expectations in genomics-driven drug development are evolving alongside scientific practice, clinical implementation, and policy. While formal guidance provides an important reference point, many of the expectations that influence regulatory review take shape earlier, through how data are generated, how patients are engaged, and how therapies are deployed in real-world settings.

For pharma teams operating at the intersection of genomics, rare disease, and advanced therapeutics, understanding these forces has become a core part of regulatory strategy. The signals shaping regulatory expectations increasingly emerge from practice rather than from guidance documents alone.

Genomic data practices are setting new expectations for evidence quality

Large-scale human genomics has become foundational to target selection, patient stratification, and translational confidence. As these approaches mature, regulators are encountering submissions supported by increasingly complex datasets that combine genetic, clinical, and experimental data.

In an episode of The Genetics Podcast recorded live at ASHG 2025, Dr. Slavé Petrovski (VP of AstraZeneca’s Center for Genomics Research) discussed how population-scale genomic datasets are being operationalized across discovery and clinical development. He described the growing importance of integrating multimodal data in ways that preserve interpretability and enable reuse across studies.

These practices are influencing regulatory expectations around data provenance, cohort definition, and analytical transparency. As genomics becomes embedded earlier in development, regulators expect clearer documentation of how genetic evidence supports clinical claims.

Human genetics is influencing translational decision-making thresholds

Genetics now plays a central role in determining which programs advance and which risks are considered acceptable. Strong human genetic evidence can increase confidence in mechanism, inform dose and population selection, and shape risk-benefit assessment.

Heiko Runz, VP of Neuroscience at insitro, described in another podcast episode how linking biobank-scale human genetics with experimental models strengthens translational confidence. His discussion highlighted how genetic evidence can anchor development decisions in human biology rather than relying solely on preclinical models.

As these approaches become more common, regulatory expectations are evolving around what constitutes sufficient biological rationale, particularly in complex neurological and rare disease programs.

Population-scale implementation is redefining follow-up expectations

Regulatory thinking around long-term follow-up and durability is increasingly informed by how therapies are implemented in practice. Programs that reach patients early and at scale generate new forms of longitudinal data that influence regulatory perspectives.

In a recent episode of The Genetics Podcast featuring Lisa Gurry, Chief Business Officer at GeneDx, the conversation focused on newborn genomic screening and population-scale follow-up initiatives. She described how early screening programs generate longitudinal datasets that support diagnosis, treatment decisions, and health system integration.

These implementation models are shaping expectations around real-world performance, safety monitoring, and durability, particularly for early-intervention therapies where long-term outcomes matter.

Policy dynamics influence regulatory behavior and review priorities

Regulatory expectations are also shaped by policy context. Leadership transitions, incentive programs, and political priorities influence how agencies interpret evidence, manage risk, and allocate review resources.

In a podcast episode featuring Max Bronstein, founder and CEO of Aviva Strategies, the discussion focused on policy dynamics affecting the FDA. He described how agency capacity, institutional knowledge, and incentive structures shape regulatory behavior, even when formal guidance remains unchanged.

For pharma teams, awareness of these dynamics supports more informed regulatory planning and engagement.

Implications for pharma development and regulatory planning

Regulatory expectations are increasingly shaped by how programs behave over time, not only by what is presented at the point of submission. Scientific rigor, operational design, and policy awareness all contribute to how regulators interpret evidence, assess risk, and determine the level of confidence required to move a program forward. Together, these shifts suggest that regulatory risk is no longer confined to submission readiness. It accumulates or is mitigated much earlier, through program design choices that affect traceability, reuse of evidence, and long-term credibility.

Programs that align with emerging expectations tend to share several characteristics:

• Genomic evidence is integrated early and documented in a way that supports reuse and reinterpretation as programs evolve
• Translational decisions are anchored in human data that strengthen biological rationale across development stages
• Long-term follow-up is planned alongside clinical development, rather than introduced reactively after approval
• Policy signals and regulatory context are monitored and incorporated into development and engagement strategies

These elements can affect how efficiently teams respond to regulator questions and how resilient a program remains as regulatory priorities shift. 

Looking ahead, regulatory expectations and advances in genomics will continue to evolve through practice. Pharma teams that treat these signals as part of active regulatory intelligence, rather than background noise, are better positioned to anticipate questions, preserve optionality, and maintain momentum as expectations continue to shift.

For additional perspectives on how regulatory signals are emerging in practice, explore Top five regulatory signals sponsors can act on now. For a deeper analysis of how these dynamics are shaping advanced therapies, download The FDA and precision medicine in 2025 or read Lessons from recent FDA actions in precision medicine.