The U.S. Food and Drug Administration (FDA) has released new draft guidelines that suggest reducing or eliminating the use of non-human primates for six-month toxicity testing of certain monoclonal antibodies.
This guidance is part of the FDA's ongoing effort to make drug testing more efficient and reduce animal testing. Instead of using animals, the FDA is using human-based models such as computational toxicology, organ systems, and real-world human safety data to make regulatory decisions.
Currently, testing a monoclonal antibody often involves more than 100 non-human primates, with each animal costing about USD 50,000. However, many drugs that pass animal toxicity tests do not get FDA approval, mainly due to safety or effectiveness issues in humans.
This draft guidance is an important step in the FDA's plan to reduce animal testing for certain monoclonal antibodies. The FDA will continue working with other agencies, like the National Institutes of Health and international partners, to explore and validate alternative testing methods across different types of drugs.
Executive Statement
According to Richard Pazdur, M.D., Director of the Center for Drug Evaluation and Research, by incorporating a knowledge-based risk assessment, they can make better informed decisions about drug safety while maintaining the rigorous safety standards that patients depend on. Risk assessments may leverage advanced methodologies. This evolution in their approach reflects both scientific progress and their responsibility to use the most effective tools for drug evaluation.
According to FDA Commissioner Marty Makary, M.D., M.P.H., they are delivering on their roadmap commitment to eliminate animal testing requirements in drug evaluation and their promise to accelerate cures and meaningful treatments for Americans. Modern science has given them far more effective and humane ways of evaluating drug safety than animal testing. This reform may reduce the amount of time it takes to bring a drug to market and lower research and development costs, which can translate into lower drug prices.
