In early March 2021, the United States Food and Drug Administration (FDA) unveiled its Data Modernization Action Plan (DMAP), an addition to the agency’s Technology Modernization Action Plan (TMAP).
While the previously published TMAP focuses on technology modernization as a whole and lays the groundwork for the FDA’s strategy for data and data management, the DMAP narrows that focus to “the stewardship, security, quality control, analysis, and real-time use of data to accelerate the path to better therapeutic and diagnostic options for people and animals, better secure the food supply chain, and provide state-of-the-art tools to enhance and promote public health.”
Despite society’s shift to digital technologies (especially over the last year!), FDA says its data systems “are still largely geared to a non-digital, document-based information paradigm” and that electronic documents, such as PDFs, “are not the same as digital data.”
The DMAP will be focused on three components: driver projects, consistent and repeatable data practices, and fostering a talent network both within the agency and with external partners.
When it comes to driver projects, Janet Woodcock, MD, acting director of the FDA, explains that “The DMAP is anchored on driver projects that contribute to the FDA’s public health responsibilities in the near term while also building critical capabilities for the future.” The agency is hopeful that by focusing on identifying solutions and developing capabilities, it will be able to avoid “the pitfalls of focusing on data collection first and only then looking for questions the data can answer.”
As far as consistent and repeatable data practices, Woodcock notes that “reducing time to perform repeatable tasks such as identifying the right data for a given problem … will greatly reduce cycle time and better leverage precious analysis resources.” The FDA is hoping to simplify data acquisition and reduce cycle time; enable better data quality and governance; accelerate model development and use; and provide security and scalability for enterprise use of data.
Lastly, the FDA understands that it needs to create and sustain a strong talent network and that its talent strategy needs to consider compensation, in-demand data science skills and cross-training of experts to increase talent capacity.
FDA plans to begin work on the plan by creating a cross-agency DMAP steering committee, planning resource needs, and conducting discovery sessions to identify best practices for the initiative. FDA will also begin to identify specific driver projects to move forward with, gather feedback on the plan, and launch programs in connection with the actions outlined in the plan. The FDA data plan will leverage the foundations laid by TMAP: a modern, cloud-forward technical infrastructure; a product-oriented approach, and enhanced collaboration. The two action plans will go hand in hand to realize the full potential and value of data and technology for the FDA and its stakeholders.