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中文Significant
- Update Date：2025-04-16
- Units：Laboratory Animal Center
U.S. FDA Plans to Phase Out Animal Testing Requirements for Monoclonal Antibodies and Other New Drugs
On April 10, 2025, the U.S. Food and Drug Administration (FDA) announced a groundbreaking initiative aimed at promoting public health. The agency plans to replace animal testing in the development of monoclonal antibody therapies and other drugs with more effective and human-relevant methods. These new approaches aim to improve drug safety, accelerate evaluation processes, reduce reliance on animal testing, lower research and development costs, and ultimately reduce drug prices.
The FDA's requirements for animal testing will be reduced, refined, or replaced through various methods, including AI-based toxicology and cellular computer models, as well as organoid-based toxicity tests conducted in laboratory settings. These approaches are referred to as Novel Alternative Methods (NAMs). This plan will be immediately implemented in Investigational New Drug (IND) applications, encouraging the inclusion of NAMs data, as outlined in a newly published roadmap.
To determine efficacy, the FDA will also begin using real-world safety data from other countries that have comparable regulatory standards and have already conducted human studies on the relevant drugs.
The FDA is working closely with the National Institutes of Health (NIH), the National Toxicology Program (NTP), and the Department of Veterans Affairs (VA) to accelerate the validation and adoption of these innovative approaches through the Interagency Coordinating Committee on the Validation of Alternative Methods (ICCVAM). The FDA and its federal partners will host public workshops to discuss the roadmap and gather stakeholder feedback on its implementation.
Over the coming year, the FDA plans to launch a pilot program—developed through close consultation—that will allow selected monoclonal antibody developers to use primarily non-animal-based testing strategies. The results of this pilot study will inform broader, phased policy changes and updates to regulatory guidance.
Original Article: FDA Announces Plan to Phase Out Animal Testing Requirement for Monoclonal Antibodies and Other Drugs
Related Link: Roadmap to Reducing Animal Testing in Preclinical Safety Studies
retrieved fromNon-Animal Alternative Testing Methods Information Network
The FDA's requirements for animal testing will be reduced, refined, or replaced through various methods, including AI-based toxicology and cellular computer models, as well as organoid-based toxicity tests conducted in laboratory settings. These approaches are referred to as Novel Alternative Methods (NAMs). This plan will be immediately implemented in Investigational New Drug (IND) applications, encouraging the inclusion of NAMs data, as outlined in a newly published roadmap.
To determine efficacy, the FDA will also begin using real-world safety data from other countries that have comparable regulatory standards and have already conducted human studies on the relevant drugs.
The FDA is working closely with the National Institutes of Health (NIH), the National Toxicology Program (NTP), and the Department of Veterans Affairs (VA) to accelerate the validation and adoption of these innovative approaches through the Interagency Coordinating Committee on the Validation of Alternative Methods (ICCVAM). The FDA and its federal partners will host public workshops to discuss the roadmap and gather stakeholder feedback on its implementation.
Over the coming year, the FDA plans to launch a pilot program—developed through close consultation—that will allow selected monoclonal antibody developers to use primarily non-animal-based testing strategies. The results of this pilot study will inform broader, phased policy changes and updates to regulatory guidance.
Original Article: FDA Announces Plan to Phase Out Animal Testing Requirement for Monoclonal Antibodies and Other Drugs
Related Link: Roadmap to Reducing Animal Testing in Preclinical Safety Studies
retrieved fromNon-Animal Alternative Testing Methods Information Network
