Artificial Intelligence (AI) refers to machine-based systems capable of making predictions, recommendations, or decisions that influence real or virtual environments, based on human-defined objectives. These systems utilize both machine and human inputs to perceive and analyse real or virtual environments, create models, and formulate options for information or action through automated analysis. Machine Learning (ML) is a subset of AI techniques used to train algorithms to improve performance at a task based on data.
The Center for Biologics Evaluation and Research (CBER) has engaged in public workshops and discussions organized by the FDA and other national and international organizations to understand the applications of AI/ML in biologics. This participation aims to inform the development of a regulatory framework that ensures the safe and responsible use of AI/ML while promoting innovation.
FDA’s effort to address the full potential of AI/ML involves a coordinated approach across its centers and components. Various FDA entities are collaborating to understand, review, and implement different aspects of AI/ML internally and externally. This coordinated effort aims to maximize the benefits of AI/ML technologies while ensuring their safety and effectiveness in regulatory processes.1
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References
- Research, C. F. B. E. A. (2024, March 20). Artificial Intelligence and Machine Learning (AI/ML) for biological and other products regulated by CBER. U.S. Food And Drug Administration. https://www.fda.gov/vaccines-blood-biologics/artificial-intelligence-and-machine-learning-aiml-biological-and-other-products-regulated-cber
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