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Enabling more efficient and seamless regulatory review processes
Identifying, developing, and deploying technology products that allow the Agency to operate at the accelerating pace of medical product development and regulation.
The Food and Drug Administration (FDA) is responsible for protecting the public health by ensuring the safety, efficacy, and security of human and veterinary drugs, biological products, and medical devices; and by ensuring the safety of our nation's food supply, cosmetics, and products that emit radiation. FDA also has responsibility for regulating the manufacturing, marketing, and distribution of tobacco products. FDA advances the public health by helping to speed innovations that make medical products safer and more effective. Overall, FDA is responsible for the oversight of more than $2.6 trillion in consumption of food, medical products, and tobacco. FDA-regulated products account for about 20 cents of every dollar spent by U.S. consumers.
How can the FDA keep up with the accelerating pace of medical product development and regulation?
To fulfill its public health mission, FDA must identify, develop, and deploy technology products that allow the Agency to operate at the accelerating pace of medical product development and regulation. In the next decade, we anticipate a 10x rise in regulatory review activities as well as increasing complexity of scientific decision-making and reliance of primary data sources. We cannot just add more people. We need to make our regulatory review processes more efficient and seamless; and improve knowledge management so that lessons learned are rapidly integrated into future decisions.
FDA’s new Technology Modernization Action Plan (TMAP) lays out the near-term roadmap for bolstering the Agency’s technical infrastructure to enable future data modernization. The TMAP also details plans for fostering an innovation culture of “learning by doing” that involves the establishment of a product development capability to evaluate ideas and novel technologies for the FDA environment through data-intensive demonstration projects. To advance this work, FDA has established a new, forward-looking program called CoInnovate@FDA. Designed to be an incubator of new ideas and a means of building future technical and organization capacity for smart data, CoInnovate@FDA connects work from across FDA and the broader data ecosystem. CoInnovate plans to incubate several new projects while also serving as a platform to highlight ongoing work across the agency.
As part of this effort, the Office of the Commissioner is seeking two Presidential Innovation Fellows to join our existing PIF team to work on the following challenges:
Unlocking the Value of Data: FDA is embarking on a bold transformation to shift to being a data-centric organization. This requires a strategy that puts data and analysis front and center in regulatory decision-making and everyday business processes. Data modernization will also force the agency to move beyond internal silos and look more broadly at its external data ecosystem to build meaningful collaborations. How can FDA foster a data-driven culture and challenge persistent silo thinking? How can we establish better data management and governance? What might an organization structure and service model look like for a new data organization? How can we fill data skills gaps and build a data science workforce? Can we identify and implement the best fitting technologies? How can we reduce the time to identify, ingest, integrate, and curate data so we spend more time on analysis and less on basic data wrangling activities? How can we build a “platform” approach to data science so that data scientists can move to cross-domain problems with ease and fluidity?
Scaling AI: As FDA progresses on our data modernization journey, we will develop the ability to scale AI from one-off pilot projects to a robust enterprise capability. To achieve this, we must build an AI ready infrastructure and workforce, shore up our critical data assets to quality and ‘fit for purpose’ data, and close the gap on our technical, data, and AI debt. How can we develop a clear enterprise vision for AI at FDA? How can we strategically scale our AI investments? What is the structure and governance needed to responsibly move from pilots to scale? How can we deploy multi-disciplinary data teams to solve top priority problems?
Leveraging External Expertise & Collaboration: FDA tackles some of America’s hardest public health problems and makes regulatory decisions with important consequences for our nation’s future. The challenges we face are worthy of mobilizing the best minds within government and across the private sector. That is why we are expanding our external collaboration and engagement efforts with the healthcare and technology industry. How can we deploy multi-disciplinary, cross-sector teams to solve our most vexing problems? How can we reboot FDA’s innovation culture by infusing startup principles and practices? How can we develop a diverse, high-performing talent pipeline to build the tech and data organization of the future?
Becoming a Product-Centric Organization: FDA is launching a new initiative to move from project-based IT delivery to one focused on continuous product innovation. A product mindset enables rapid iteration and innovation by focusing on changing requirements, product outcomes, and the strategic differentiation for a product or service. We will accomplish this shift by implementing Product Management approaches across our broad and diverse portfolio. How can FDA start the cultural shift required to embrace the Product Mindset? What does ‘product’ mean in an FDA context and how can we reshape the customer and user experience? What might an organization structure and service model look like for a new product organization? How can we create a product management workforce at FDA?
Using Real World Evidence to Accelerate Safe & Effective Cures: Real-world data (RWD) and real-world evidence (RWE) are playing an increasingly important role in health care decisions. FDA uses RWD and RWE to monitor safety and effectiveness, and to make regulatory decisions. The health care community is using these data to support clinical trial designs, support coverage decisions, and to develop decision support tools for use in clinical practice. How can FDA help improve the development and application of RWD to improve patient care? How can FDA leverage RWD during public health emergencies like COVID-19? How can the rapid development of coding standards help enable interoperability? How can RWD be used for external control arms in new spaces?