On May 10, the FDA released two discussion papers on the use of artificial intelligence and machine learning (AI/ML) in drug development and manufacturing. In a statement introducing the papers, Patrizia Cavazzoni, M.D., Director of the FDA Center for Drug Evaluation and Research, highlighted the potential of AI/ML to transform how stakeholders develop, manufacture, use, and evaluate therapies. “Ultimately, AI/ML can help bring safe, effective, and high-quality treatments to patients faster,” she wrote. “For example, AI/ML could be used to scan the medical literature for relevant findings and predict which individuals may respond better to treatments and which are more at risk for side effects. Conversational agents or chatbots, which are based on ‘generative’ AI, have the potential to answer people’s questions about participating in clinical trials or reporting adverse events. Digital or computerized ‘twins’ of patients can be used to model a medical intervention and provide biofeedback before patients receive the intervention.”

However, significant ethical and security challenges remain. The first paper, “Using Artificial Intelligence and Machine Learning in the Development of Drug and Biological Products,” addresses these concerns as well as challenges related to algorithms that have a degree of opacity, or algorithms that may have internal operations that are not visible to users or other interested parties, which can lead to amplification of errors or preexisting biases in the data.

The discussion paper was developed as a collaboration between the FDA’s Center for Drug Evaluation and Research (CDER), the Center for Biologics Evaluation and Research, and the Center for Devices and Radiological Health, including its Digital Health Center of Excellence. It aims to spur a discussion with interested parties in the medical products development community, such as pharmaceutical companies, ethicists, academia, patients and patient groups, and global counterpart regulatory and other authorities, on using AI/ML in drug and biologic development, and the development of medical devices to use with these treatments.

The paper includes an overview of the current and potential future uses for AI/ML in therapeutic development, discusses the possible concerns and risks associated with these innovations and ways to address them, and emphasizes adopting a risk-based approach to evaluate and manage AI/ML in facilitating innovations and protecting public health. As a follow-up to the paper, the FDA is planning a workshop to discuss how the community can work together to realize the potential of AI/ML for product development.

A Framework for Regulatory Advanced Manufacturing Evaluation

To further address the use of AI in drug manufacturing, CDER issued a second discussion paper, Artificial Intelligence in Drug Manufacturing, as part of the Framework for Regulatory Advanced Manufacturing Evaluation (FRAME) Initiative. The agency is planning a second workshop for stakeholders to discuss the questions related to the AI in drug manufacturing discussion paper.

“Our agency’s efforts in AI/ML extend beyond these initiatives,” stated Dr. Cavazzoni. “We consult product developers, engage patients, and promote regulatory science in this area, among other activities. As a public health regulatory agency, we hope to encourage the safe development of these technologies that are poised to help Americans gain quicker and more reliable access to important treatments.”

Image: Patrizia Cavazzoni, M.D.