(Remarks as prepared for delivery)

Thank you Minister Oh.  I want to extend my great appreciation to you for hosting this symposium on such an important and timely topic.  

The FDA relies on the most current science and scientific developments to inform the decisions we make to ensure the safety of the products we regulate and to protect the health of the public.  Digital technology, computing, and data science play an increasingly important role in our work because of the ever-expanding impact of these areas of science on every aspect of health and health care.  

Artificial intelligence (AI), including machine learning (ML), is the latest vehicle for these extraordinary advances, and is already having a profound impact on medical product innovation, including, of course, products the FDA is tasked with reviewing. And, as our discussions through these meetings underscore, it is an impact that will only expand.

To effectively do our jobs as protectors of public health means we need to embrace the groundbreaking science used by the industries we regulate.  With AI, the potential reach of this impact is even greater, since one of the key benefits of AI, particularly generative AI, is its ability to create and support new and important insights gleaned from the vast amount of data generated during the delivery of health care and in the everyday lives of people. 

The remarkable growth in our ability to digitize even the most routine work, combined with the availability of electronic health records, claims data, and wearable sensors is enabling the collection of more complex and relevant data with far less effort and cost.  And these data offer enormous potential for us to expand our ability to find answers to some of the most challenging medical and health questions we face.   

In the field of nutrition, these technologies will be revolutionary, enabling insights that were simply impossible because of the multidimensionality and scale of the intersection of nutrients and health outcomes.  So, it is particularly important that we are able to use these new technologies to acquire, analyze, and interpret data to generate evidence related to those industries and the health of individuals and the public we serve. 

Some in the nonscientific community may be surprised by the seemingly sudden amount of attention on AI.  But for scientists and regulators, this issue is not new—we’ve been seeing it coming for a long time.  At the FDA, we’ve been working for years to anticipate and prepare for the challenges of AI, and also harness its potential.  

Indeed, artificial intelligence and machine learning are already beginning to play a critical role in supporting innovations in various aspect of biomedical research, drug and biologic discovery, therapeutic development, and pharmaceutical testing and manufacturing.  

To give you a small idea of the impact that AI is already having on medical products across the span of drugs, biologics and devices, consider that the FDA has received over 300 submissions for drugs and biological products with AI components, and more than 700 submissions for AI-enabled devices.  These submissions have included aspects related to drug discovery and repurposing, enhancing clinical trial design elements, dose optimization, endpoint/biomarker assessment, postmarketing surveillance, and a growing diversity of medical devices that leverage AI that are meant to improve clinical workflows and patient experiences or outcomes. In other words, they are having an impact on the entire medical product development and healthcare delivery systems.

Consequently, AI is already a powerful tool in the FDA’s arsenal, but there is the possibility of much more potent benefit, with the potential to provide support to and strengthen nearly every area of our vast oversight authorities, helping us facilitate speedier delivery of new treatments to patients.  

We’re already benefitting in several ways, including better understanding of the heterogeneity of disease progression, patients' therapy responses, and recognizing patterns indicative of conditions, all of which can be used to support precision medicine and clinical and public health decision tool development.  And I want to stress again that the area of nutrition and food safety is on the verge of a revolutionary improvement due to the combination of digitization, AI and computing power.  

The FDA is also exploring the use of AI technologies to facilitate our internal operations and regulatory processes, which could benefit both Agency experts and the public by streamlining workflows and facilitating high quality, novel medical products reaching the patients that need them.  And we’re producing data, information and evidence to support regulatory decision making by refining, reducing, or replacing animal-based pharmacokinetic, pharmacodynamic, and toxicologic studies.  

At its most basic, AI can strengthen our operational systems and bring increased value, productivity, opportunity, and efficiency to our work, helping us process and analyze complex data, including data from medical imaging or digital health technologies, for example.  We can free up staff from repetitive tasks and enable them instead to focus on more meaningful activities to weigh the evidence and arrive at better decisions and on explaining those decisions to the public.  

These changes are happening across the FDA.  For example, the Agency recently reviewed and granted a new artificial intelligence algorithm that supports earlier detection and management of hypertrophic cardiomyopathy (HCM).  This granting created a new regulation for cardiovascular machine learning-based notification software and will help provide quicker identification of possible suspected HCM cases allowing for earlier patient treatment. 

Another area of work is being done by the FDA’s National Center for Toxicological Research (or NCTR), which is supporting our Center for Drug Evaluation and Research (CDER) with AI models for drug safety review and the IND Smart Template System.  And an NCTR study is applying an AI model for document screening, classification, and processing to enhance pharmacovigilance. 

Still another important use of AI is being applied by our Office of Minority Health & Health Equity (OMHHE), which is engaged in examining ethnic and racial disparities in critical care delivery to heart-failure patients using AI and real-world data (RWD).  AI has enormous potential to make RWD more accessible and increase the ability to use a much broader spectrum of clinical evidence for regulatory, clinical and public health decision-making.

In short, the AI landscape is expanding every day.  And we still have a lot to learn.  But I want to underscore that as we move forward in the development of policies in our own regulatory systems, it’s important for each of our agencies to embrace essential principles of convergence and harmonization of regulatory expectations among nations and across areas of medical product innovation.

Consensus standards support and encourage global access to innovation, help increase competition among product developers, and reduce burdens on manufacturers by harmonizing expectations across jurisdictions.  The harmonization process brings many benefits, including fostering efficiency, consistency, and standardization of best practices, reducing redundancy, and connecting stakeholders who share common interests to advance them.  Together, this helps ensure efficient access to markets, and supports the ultimate goal -- faster access for patients to innovative, safe, and effective products.

Although we are not yet ready for true harmonization, as we move forward in the development of AI technologies, it will be essential for all regulators and international bodies in which they are represented to work to pursue alignment of expectations and establish harmonized and consensus standards in this rapidly developing area, while continuing to implement these standards at home.  As we race to catch up with this rapidly accelerating technology, we also need to be preparing for the entrance of quantum computing, which will exponentially increase all these capabilities. 

We look forward to working with all of you as we travel this road, embracing these challenges and continuing to apply regulatory principles rooted in science and using the most appropriate technology available and learning together as an international community with a clear focus on a longer and better life for the people we serve.  

Thank you.