Every year, and in countries around the world, significant time and resources are devoted to the noble cause of developing drugs to treat and cure human disease. With rare exception, drug interventions cannot reach commercialization without safety and efficacy having first been demonstrated in animal models. The intention of regulations, which require the use of animal models in such contexts, is to ensure that only safe and effective drugs end up being used by patients. Similarly, it is standard practice for researchers to employ animal models in their attempts to understand the way diseases present and progress in humans. Unfortunately, there exist serious theoretical and empirical concerns regarding the standard practice of using non-human animals to model human response to perturbations, such as drugs and disease. These concerns are important because conducting disease research and drug development in a manner that is not supported by science will have suboptimal implications for the humans who rely on that research, which encompass the entire population. Based on complexity science, modern evolutionary biology, and empirical evidence, we demonstrate that animal models have failed as predictors of human response. That is, animal models do not and cannot have acceptably high predictive value for human response to drugs and disease. By this we mean that animal modeling, as a methodology, is for all practical purposes not predictive of human response to drugs and disease; and hence it should be abandoned in favor of human-based research and testing, such as personalized medicine, a new field that takes into account the unique genetic make-up of each individual patient.
Greek, R., & Kramer, L. A. (2019). The scientific problems with using non-human animals to predict human response to drugs and disease. In Animal Experimentation: Working Towards a Paradigm Change (pp. 391-416). Brill.