Comment from Anonymous

I support the FDA’s effort to reduce unnecessary animal testing while maintaining rigorous standards for patient safety. Scientific progress has created opportunities to answer many regulatory questions using evidence that is more directly relevant to human biology, and I encourage the FDA to continue modernizing its approach as these methods evolve. Animal testing has contributed to important medical advances, but it should no longer be the default when scientifically valid, human-relevant evidence can answer the same regulatory question. Technologies such as patient-derived tumor organoids, organ-on-a-chip systems, computational modeling, and artificial intelligence are expanding researchers’ ability to predict human responses. While these methods cannot yet replace every animal study, they should be fully considered whenever scientifically appropriate. Animal models remain valuable in some situations, but differences in genetics, metabolism, immune function, and tumor biology limit how reliably they predict human outcomes. Many oncology drugs that appear promising in animals ultimately fail during human clinical trials because they are either ineffective or present unexpected safety concerns. These limitations highlight the importance of evaluating the totality of available scientific evidence rather than relying primarily on animal studies. The draft guidance appropriately encourages a Weight of Evidence approach, but it would benefit from clearer expectations regarding how different forms of evidence will be evaluated. Greater transparency would improve consistency for sponsors, reviewers, and researchers while encouraging continued investment in validated New Approach Methodologies. Recent advances in human-relevant research are particularly encouraging. Patient-derived organoids preserve many of the biological characteristics of an individual’s tumor, allowing researchers to evaluate treatment responses using human tissue. Organ-on-a-chip technologies recreate interactions between human tissues that may not be accurately represented in animal models. Computational modeling and AI-assisted analysis can rapidly evaluate large datasets, identify safety signals, and help predict drug behavior before clinical trials. Individually, these methods have limitations, but together they can answer many scientific questions more effectively than relying on any single approach. For these reasons, I encourage the FDA to strengthen this guidance by: • Clearly defining what constitutes a sufficient Weight of Evidence package and how different forms of evidence will be evaluated. • Explicitly recognizing validated human-relevant methods—including human clinical data, published research, prior safety findings, patient-derived organoids, organ-on-a-chip systems, computational models, and other New Approach Methodologies—as evidence that should receive meaningful consideration. • Allowing sponsors to strengthen a Weight of Evidence package with additional human-relevant evidence before requiring new animal studies whenever scientific uncertainties remain. • Requiring a written scientific justification for any new animal study, explaining the specific unanswered regulatory question, why existing evidence is insufficient, why the selected animal model is biologically appropriate, and how the study will improve regulatory decision-making. • Measuring and publicly reporting the impact of this guidance, including reductions in animal use, increased acceptance of validated New Approach Methodologies, and outcomes that demonstrate whether these approaches continue to protect patient safety while reducing unnecessary animal studies. Scientific innovation and animal welfare are not competing goals. As human-relevant technologies continue to improve, regulatory decisions should increasingly rely on the methods that provide the most predictive evidence for human health, reserving animal studies for situations where they are scientifically necessary. This approach supports better science, continued public confidence, and more ethical drug development.