FDA on Artificial Intelligence Across the Product Lifecycle

How Will It Affect You?

The FDA has released a paper through its medical product centers to reaffirm its commitment to the responsible and ethical development, deployment, use, and maintenance of Artificial Intelligence (AI) in medical products, aligning with its mission to ensure the safety and efficacy of medical products for patient use. The paper emphasizes the FDA’s dedication to innovation, the development of standards, and aims for convergence across the Agency.

FDA is also exploring the use of AI technologies to facilitate its internal operations and regulatory processes, which could benefit both agency experts and the public by streamlining workflows and facilitating high quality, novel medical products more quickly reaching the patients who need them.

The timing of this announcement is not lost on us. Axendia will soon publish a market research report focused on the current and future state of generative AI (Gen AI) in life sciences. Spoiler alert: 79% of survey respondents indicated current frameworks do not support the adoption of Gen AI in life sciences.

In the paper, FDA defines AI as a machine-based system that can, for a given set of human-defined objectives, make predictions, recommendations, or decisions influencing real or virtual environments. ​

The FDA is actively working to revolutionize healthcare by supporting the development and regulation of AI in medical products, aligning with its mission to protect and promote public health. This involves a collaborative effort across various FDA centers to ensure public safety while encouraging ethical innovation in AI. The deployment and maintenance of AI technologies in healthcare require a carefully managed, iterative process from ideation to real-world application. This includes everything from data acquisition and model development to deployment and ongoing monitoring. To effectively manage these processes, a risk-based regulatory framework is essential, incorporating principles, standards, best practices, and advanced regulatory science tools tailored to specific medical products.

Areas of Focus

Image Source: FDA

The areas of focus regarding the development and use of AI across the medical product life cycle are as follows: ​

  • Foster Collaboration to Safeguard Public Health. ​​ To safeguard public health in the context of AI in medical products, the strategy includes engaging with diverse stakeholders to address key AI concerns like transparency and bias; encouraging educational programs for all involved parties for safe AI use; and enhancing international collaboration on AI standards and practices.
  • Advance the Development of Regulatory Approaches That Support Innovation. The strategy aims to foster innovation in regulatory approaches for AI by closely monitoring trends to identify knowledge gaps and opportunities, thereby ensuring clear guidelines for AI in medical products. It supports the development of methods for evaluating AI algorithms, addressing bias, and ensuring their robustness. Additionally, it builds on existing initiatives for AI regulation in medical products, issuing guidance on AI use in development, marketing, life cycle management, and regulatory decision-making.
  • Promote the Development of Standards, Guidelines, Best Practices, and Tools for the Medical Product Life Cycle. The focus is on enhancing standards, guidelines, best practices, and tools for AI in the medical product life cycle. This includes refining criteria for safe and ethical AI use, promoting best practices for monitoring AI product safety and performance, ensuring data for AI training and testing is representative and fit for purpose, and developing a quality assurance framework for AI tools in the medical product life cycle.
  • Support Research Related to the Evaluation and Monitoring of AI Performance. The approach includes backing research for the evaluation and monitoring of AI performance, emphasizing demonstration projects that focus on identifying and mitigating bias, addressing health inequities to ensure equity and data representativeness, and maintaining ongoing monitoring of AI tools in medical product development to adhere to standards and ensure consistent performance and reliability. ​

These areas of focus aim to promote responsible and ethical development, deployment, use, and maintenance of medical products that incorporate or are developed with AI, while ensuring patient access to safe and effective medical products and facilitating innovation.

Moving forward, the FDA will keep engaging with both U.S. and global stakeholders, tailoring regulatory approaches to protect patients, healthcare workers, and ensure cybersecurity, while promoting innovation in the rapidly evolving field of AI.

Per FDA, the paper titled Artificial Intelligence and Medical Products: How CBER, CDER, CDRH, and OCP are Working Together,” is meant to complement the “Artificial Intelligence and Machine Learning Software as Medical Device Action Plan,” published in January 2021.

Catching up with Califf

In a recent “Catching up with Califf” post on the same topic, Robert M. Califf, M.D., Commissioner of Food and Drugs wrote, “At the FDA, we’ve been working for years to anticipate and prepare for the challenges of Artificial Intelligence (AI), and also to harness its potential. 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 seen it coming for a long time, and I’d like to catch up with you today on this exciting topic.”

The Commissioner acknowledged AI is significantly impacting the development of safer and more effective medical products and nutritious food. Since 1995, the FDA has reviewed over 300 submissions for drugs and biological products and more than 700 for AI-enabled devices, covering drug discovery, clinical trial design, dose optimization, and post market surveillance, among others. These submissions also include a variety of medical devices using AI to enhance clinical workflows and patient outcomes, alongside advanced predictive algorithms. Additionally, the fields of nutrition and food safety are poised for major advancements through the integration of digitization, AI, and increased computing power.

Dr. Califf is also of the opinion at its most basic, AI can strengthen the Agency’s operational systems and bring increased productivity, opportunity, and efficiency to its work, helping personnel process and analyze complex data faster, including data from medical imaging or digital health technologies.  Per Dr. Califf, “We can free up staff by automating repetitive administrative functions and enable them to focus on more complex meaningful activities to weigh the evidence and arrive at better decisions. Our workforce should also have more time to explain those decisions to the public and learned intermediaries in the biomedical and clinical world.”

To discuss how this could affect you, click on this link to schedule an Analyst Inquiry on this topic.

The opinions and analysis expressed in this post reflect the judgment of Axendia at the time of publication and are subject to change without notice. Information contained in this post is current as of publication date. Information cited is not warranted by Axendia but has been obtained through a valid research methodology. This post is not intended to endorse any company or product and should not be attributed as such.

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