The State of Regulatory Success: Insights from a PTRS Survey

The above findings suggest that organizations rely on local regulatory representatives and regulatory intelligence subscriptions to ensure compliance with regulatory requirements. Subscriptions to regulatory intelligence data offer updates to regulatory requirements, insights to policy and competitors, and other notification services. In comparison, no one adopted digital and ML-enabled solutions for periodic assessment. There is an alignment that organizations are looking for more efficient and expedient solutions to leverage digital solutions for regulatory alignment.

This diversity in strategies, from leveraging local operating companies (LOCs) to central teams, databases, and cutting-edge digital solutions, underscores that very organization needs to consider its company strategy, globalization priority, and portfolio mix to enable regulatory intelligence best.

For 36% of respondents, some systems are connected within their organizations, but there is still a significant amount of data transcription and manual re-entry of information. 27% of respondents have defined data standards and established a governance framework with data cleansing. The complexities in the regulatory organization across data sources to get to a completely digital landscape while advancing significantly continue to evolve. The additional challenge that organizations address include standard naming conventions and consistency in data collection. New data standards are being introduced, and the industry is embracing this change systematically. 9% of respondents reported having a comprehensive approach for onboarding data standards like IDMP and XEVMPD. This group represents organizations that have made significant strides in data governance, emphasizing compliance with regulatory standards.

For organizations looking to improve their data governance, the critical focus areas should include connecting systems more effectively, implementing robust data standards, and prioritizing data quality initiatives. These efforts can help enhance regulatory compliance, reduce errors, and optimize operational efficiency in regulatory affairs.

Data governance plays a foundational role in sustaining PTRS at scale. Without common definitions, traceability, and quality controls, even well-designed assessment models struggle to deliver reliable insights. This is particularly true when assessing probability of technical and regulatory success across diverse therapeutic areas and markets.

Organizations that invest in governance frameworks typically define ownership, data stewardship, and validation rules upfront. Over time, this enables more efficient reassessment cycles and supports longitudinal learning across programs. Importantly, governance does not imply rigidity. Well-designed frameworks allow controlled flexibility to accommodate product-specific nuances.

As PTRS becomes embedded into portfolio governance, data quality increasingly determines confidence in decision outcomes rather than the sophistication of scoring models alone.

A majority of respondents (45%) did not perceive any challenges with adopting PRS in their organization, indicating that effective governance and methodology to gather the necessary information to evaluate a product portfolio are well understood and managed. However, 27% of the respondents highlighted the challenge of aligning LOC and different groups to the data governance process, possibly due to the challenge of accessing information. 18% of the respondents reported that gathering data to assess risk on a periodic basis takes time, which complements the prior response because organizations may have data accessibility issues. Only 9% of the respondents reported that this is a new area they have not yet initiated. Although a significant portion of organizations are prepared for PTRS, there are still notable challenges. Organizations should establish a governance process for communicating the approach and process to the various stakeholders that should be followed and subsequently clarify data that will contribute to the assessment, including regulatory and competitive intelligence, purchased data on trends and insights, as well as function-specific data from manufacturing, epidemiology, clinical, safety, and other functions.

Establishing a process toward data capture and assessment of the variables and their contribution to determine the probability of technical success and regulatory success separately needs to be defined and communicated across functional areas.

Taken together, the survey findings suggest that PTRS is widely recognized but unevenly operationalized. While methodologies may differ, organizations face common challenges related to data access, alignment, and governance across PTRS drug development lifecycles.

Improving PTRS maturity does not require radical transformation. Incremental improvements in process clarity, assessment cadence, and cross-functional transparency can meaningfully strengthen decision-making. Over time, these changes compound, supporting more predictable outcomes in both development and regulatory engagement.

As regulatory complexity increases, structured approaches to probability of regulatory success will likely become more central to portfolio strategy rather than a supporting activity.