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# Draft Guide on Using AI for Drug Development
- URL: https://www.fdaweb.com/draft-guide-on-using-ai-for-drug-development/
- Published: 2025-01-06T12:00:00.000Z
- Updated: 2026-09-14T14:50:09.000Z
- Author: David McFarland
- Tags: Drugs, #legacy-id-D5158428

FDA has issued a [draft guidance](https://www.fda.gov/regulatory-information/search-fda-guidance-documents/considerations-use-artificial-intelligence-support-regulatory-decision-making-drug-and-biological?ref=fdaweb.com) entitled “Considerations for the Use of Artificial Intelligence (AI) to Support Regulatory Decision-Making for Drug and Biological Products.” An [agency release](https://www.fda.gov/news-events/press-announcements/fda-proposes-framework-advance-credibility-ai-models-used-drug-and-biological-product-submissions?ref=fdaweb.com) says FDA has substantial experience in reviewing regulatory submissions with AI components, and they continue to exponentially increase. “AI can be used in various ways to produce data or information regarding the safety, effectiveness, or quality of a drug or biological product,” it says. For example, AI approaches can be used to predict patient outcomes, improve understanding of predictors of disease progression and process and analyze large datasets (e.g., real-world data sources or data from digital health technologies).”

The document provides a risk-based credibility assessment framework that may be used for establishing and evaluating the credibility of an AI model for a particular context of use (COU). The agency says the approach is consistent with how reviewers have been reviewing applications for drug and biological products with AI components. It encourages sponsors to have early engagement with the agency about an AI credibility assessment or the use of AI in human and animal drug development.

![](https://ssl.gstatic.com/ui/v1/icons/mail/images/cleardot.gif)

The guidance says that “credibility evidence is any evidence that could support the credibility of an AI model output for a specific COU.” A COU defines the specific role and scope of an AI model used to address a question of interest.

FDA notes that it does not endorse the use of any specific AI approach or technique. AI refers to a machine-based system that can “make predictions, recommendations, or decisions influencing real or virtual environments,” the guidance says. “AI systems (**1**) use machine- and human-based inputs to perceive real and virtual environments, (**2**) abstract such perceptions into models through analysis in an automated manner, and (**3**) use model inference to formulate options for information or action.

The guidance also says that the most common AI component used in drug product life cycles is machine learning, which refers to a “set of techniques that can be used to train AI algorithms to improve performance at a task based on data.”