Health authorities such as the FDA and EMA are looking to data to improve regulatory processes. Initiatives such as the Identification of Medicinal Products (IDMP) are being designed to help health authorities gain quicker and broader access to product information primarily to improve patient safety. These types of initiatives are prompting R&D teams in pharmaceutical companies to assess their internal practices and capabilities to support the new requirements.
However, sometimes emerging health authority requirements get delayed due to competing priorities, complex implementations, and a complex stakeholder landscape. As the projects stop and start or redefine themselves, life sciences organizations find it difficult to respond to changing timelines or progress internal capabilities projects that support the new requirements. The constantly shifting communications and timelines can halt progress and result in significant rework. Therefore, it is relevant to raise the question:
How can life sciences teams make progress toward their goals in such a dynamic environment?
A more agile approach to enterprise regulatory data
New requirements are compelling life sciences organizations toward a three-pronged approach that enables them to realize greater business value from their efforts.
- a master data management approach to their regulatory information that is used throughout the enterprise
- a shift away from document-centric models toward more data centric systems and processes for managing information
- a data governance approach that ensures quality of the data wherever it is used
By focusing on the internal business case, organizations can make progress toward their goals, even as health authority initiatives stall, shift direction, or change scope. Increasing control of data offers numerous internal business benefits that organizations can enjoy as they position themselves to address emerging requirements from health authorities.
Preparing the organization to gain greater value from data-centric processes
As life science organizations prepare for these types of projects, they must ensure that they are flexible enough to monitor, track and interpret announcements from authorities. This typically requires a dedicated SME team who can digest information and integrate it into their planning and practices.
They must also focus on data quality. As they move from document to data centric processes, valuable data that was traditionally hidden away in documents will be available in a structured format that enables, for instance analytics. This new access will also support new uses of data sets in other functions across the organization. This progress can be made regardless of regulator activities.
Management must understand and support the recurring value being created through this type of project. Their support is critical to success and requires dedicated awareness sessions and training for stakeholders across the organization.
Benefits of data governance in the agile use of regulatory data
As teams work toward a more agile approach to supporting IDMP, they will have built a platform where quality data is more readily available, and they will be well-positioned for emerging health authority requirements. This approach creates a strong foundation to support a multitude of current initiatives such as SPOR, ePI, DADI, UNICOM, eCTD 4.0, and CTIS.
NNIT has a wealth of experience helping life sciences organizations gain greater value from their regulatory data. We can help you too. Please contact us to learn more about our winning solutions and how we can help your organization prepare for emerging health authority requirements.
Contact us to learn more about NNIT's data governance approach to RIMS.
