The FDA has announced the strengthening of a law signed in 2022 to reduce animal testing by creating a formal policy to require the use of AI models, lab-grown human tissues or organelles, and international safety data, if available, to replace traditional animal testing. The “shift” aims to “improve accuracy, reduce costs, and accelerate the development of new therapies”.
In late, 2022, President Biden signed a law formalizing the principle of 3 Rs – Replace, Reduce, Refine – for use of animal testing in support of new drugs. The law required the use of alternate non-animal methods such as computational models (“Replace”), minimizing the number of animals used in research (“Reduce”), and refining the procedures used to minimize pain and suffering in animals used for testing (“Refine”). This week, the FDA expanded on that law by creating specific instructions for reducing the reliance on animal testing—especially in the creation and evaluation of monoclonal antibody therapies.
Instead of traditional animal testing, the FDA will now encourage the use of advanced technologies such as artificial intelligence-driven toxicity prediction models and laboratory-grown human cell systems known as organoids. These methods, often referred to as New Approach Methodologies (NAMs), are expected to provide more accurate insights into how drugs behave in the human body. The initiative takes immediate effect for investigational new drug (IND) applications, where developers are now urged to include NAMs data in their submissions. A detailed roadmap outlining the implementation process was released alongside the announcement.
As part of this regulatory framework, the FDA will also begin incorporating international real-world data from countries with comparable drug safety standards. This shift addresses long-standing concerns about duplicative testing, where drug developers were often required to repeat animal studies for drugs already widely used abroad in humans.
The benefits of this new approach are far-reaching. By integrating sophisticated computer simulations, scientists can model how monoclonal antibodies interact with human systems at the molecular level, forecasting potential side effects without the need for animal trials. Similarly, lab-grown human organoids—miniature, functional replicas of organs like the liver, heart, or immune system—can offer early indicators of toxic responses that may not show up in animal models.
The FDA plans to revise its regulatory guidelines to recognize data from these non-animal methods, potentially allowing companies to bypass some traditional studies if their submissions demonstrate sufficient safety. This could significantly streamline the approval process, making it easier for pharmaceutical developers to bring new therapies to market faster.
Over the next year, the agency will also launch a pilot program allowing selected monoclonal antibody developers to use primarily non-animal testing approaches under FDA guidance. Results from this program will shape broader policy reforms and future guidelines. The policy aims to speed up the approval process, cut development costs, and, hopefully, lower drug prices while enhancing drug safety with the use of more human-relevant scientific methods.
