Animal testing is one of the most important steps in getting a drug approved by the U.S. Food and Drug Administration (FDA), and it is part of a larger process designed to protect public health. Although many FDA-approved drugs cause side effects, the FDA’s role is to determine whether the benefits of a drug outweigh its risks. As science continues to advance, new technologies have begun to change certain aspects of biomedical research, leading many to question whether animal testing is still necessary. Even so, animal testing has played a major role in scientific progress by providing biological models that share similarities with humans, allowing researchers to perform invasive procedures, making it easier to control experimental variables, and using organisms with shorter life spans and faster reproduction to speed up results. However, there are also significant drawbacks, including the fact that results do not always translate perfectly to humans, ongoing ethical concerns about animal welfare, the oversimplification of complex human diseases, and the high cost and resources required to conduct animal research.<\/p>\n\n\n\n
During the animal testing process, animals are used as models that allow researchers to investigate specific aspects of biological processes. These models are selected based on how closely their biology resembles the relevant human systems being investigated. A model’s ability to mimic disease conditions as they occur in humans allows researchers to study virulence, disease progression, and potential drug treatments in ways that would be considered unethical in human subjects. Another reason animal testing has been heavily relied on is due to the degree of control researchers have over the experimental variables. Controlling constants is essential in experimental design because it helps identify the true cause of results. Animal studies allow for far greater control than studies conducted on humans. For example, Rodriguez et al. (2020) developed a high-fat diet for Iberian pigs to investigate obesity-induced chronic kidney disease. By strictly controlling the pigs’ diet, the researchers were able to induce the disease, and the findings closely resembled patterns observed in humans. In contrast, it is far more difficult to control human diets and environments, as participants are prone to making independent lifestyle choices. Researchers also would not perform this experiment on humans because it would require them to intentionally harm them, which will be discussed later. Additionally, many model organisms are selected for their rapid reproduction and short lifespans, which allow researchers to study disease progression and genetic inheritance more efficiently by compressing biological processes that would take years in humans into much shorter time frames.<\/p>\n\n\n\n
Despite these advantages, animal testing presents numerous notable limitations. The first is that the direct transition from animals to humans is not guaranteed. Many drugs that progress to human trials ultimately fail, often because the physiological, anatomical, or psychological differences between animals and humans prevent accurate prediction of human outcomes. Another major limitation concerns the ethical implications of animal experimentation. Many procedures are invasive, likely causing pain and distress, which raises questions about the morality of subjecting animals to suffering for human benefit. Nonetheless, it should be noted that “pain or distress of the animals during experiments has to be minimized, i.e., refinement” (Mukherjee et al. 2022). Additionally, numerous animal models oversimplify complex human diseases and fail to capture critical factors influencing disease progression. For example, replicating mental, emotional, or cognitive disorders in animals is challenging because they typically lack the relevant biomarkers (Monteggia et al. 2018). Finally, animal research is resource-intensive, requiring specialized facilities and trained personnel, which contributes to substantial financial costs.<\/p>\n\n\n\n
The impact of animal testing on medical and scientific progress is undeniable. An area of study facilitating invasive studies, allowing for a high degree of experimental control, and taking advantage of animals’ short lifespans and rapid reproduction, while limitations highlight the need for alternative approaches because of the ethical and financial burdens that accompany this method of study. Researchers are beginning to explore methods such as human organoids, organ-on-a-chip systems, and computational modeling to reduce reliance on animal testing. All these alternative ways will ensure continuous advancement in science, while the welfare of both human and animal subjects remains intact.<\/p>\n\n\n\n
References<\/strong><\/p>\n\n\n\n Khedkar S. (2025, December 4). Failed Sperm Flagellar Development Drives Infertility<\/em>. The Scientist, https:\/\/www.the-scientist.com\/failed-sperm-flagellar-development-drives-infertility-73821<\/p>\n\n\n\n Monteggia L. M., Heimer H., & Nestler E. J. (2018). Meeting Report: Can We Make Animal Models of Human Mental Illness?. Biological Psychiatry<\/em>, 84(7), 542-545. 10.1016\/j.biopsych.2018.02.010<\/p>\n\n\n\n Mukherjee P., Roy S., Ghosh D., & Nandi S. K. (2022). Role of animal models in biomedical research: a review. Laboratory Animal Research, 38(1), 18. 10.1186\/s42826-022-00128-1<\/p>\n\n\n\n PhD D. (2025, July 16). FDA Announces Plan to Phase Out Animal Testing. Will That Work?<\/em>. The Scientist, https:\/\/www.the-scientist.com\/fda-announces-plan-to-phase-out-animal-testing-will-that-work-73173<\/p>\n\n\n\n Rodr\u00edguez R. R., Gonz\u00e1lez-Bulnes A., Garcia-Contreras C., Elena Rodriguez-Rodriguez A., Astiz S., Vazquez-Gomez M., Luis Pesantez J., Isabel B., Salido-Ruiz E., Gonz\u00e1lez J., Donate Correa J., Luis-Lima S., & Porrini E. (2019). The Iberian pig fed with high-fat diet: a model of renal disease in obesity and metabolic syndrome. International Journal of Obesity<\/em>, 44(2), 457-465. 10.1038\/s41366-019-0434-9<\/p>\n\n\n\n <\/p>\n\n\n\n\n\n\n\n New Approach Methodologies (NAMs) are constantly changing how scientists assess the effectiveness and safety of drugs. Traditionally, animal models have been the standard for preclinical testing. However, they often fall short in accurately predicting human outcomes. Many drugs that turn out to be successful in animal testing fail in humans. Because of this, more researchers are turning to alternative methods such as organs-on-chips, 3D organoids, and computational models, to name a few. These methods provide more accurate results because they use human data and cells, but these promising technologies still have limitations in replicating the complexity of the human body.<\/p>\n\n\n\n One of the main advantages of NAMs is the use of induced pluripotent stem cells (iPSCs) in microfluidic organs-on-chips and 3D organoids. iPSCs are adult somatic cells that have been reprogrammed into a stem-cell-like state, allowing them to differentiate into various cell types. This makes patient-specific models of human tissues possible for personalized care. Organs-on-chips are small devices with channels that simulate blood flow and tissue structures, while organoids are clusters of cells that resemble miniature organs. Both systems create a more accurate environment than traditional animal models because they use human cells, enabling researchers to replicate certain functional features of these complex cells.<\/p>\n\n\n\n More specifically, the Nature article explains how researchers can generate iPSCs from patients and use them to create organoids for modeling specific diseases. This enables \u201cclinical trials in a dish,\u201d where drugs are tested directly on human-like systems before they are used on actual patients (Kwon, 2026). Similarly, organs-on-chips, like liver chips, can imitate how drugs move through human tissues and accurately predict toxicity. In one case, a liver-on-a-chip model correctly identified drugs that cause liver injury, and even detected harmful compounds that previously passed animal testing (Kwon, 2026). An article by Barua et al (2025) emphasizes that microfluidic organ-on-chip technologies combine IPSC-derived cells with controlled environments, such as fluid flow and mechanical forces, to closely mimic real human physiology. This level of control allows researchers to observe cell behavior under conditions that resemble those in the human body, improving the reliability of drug testing results.<\/p>\n\n\n\n In addition to physical models, computational approaches and generative AI are becoming increasingly important in replacing animal testing. These systems predict how drugs will behave using large datasets from human, animal, and laboratory studies. For example, computational models can assess whether a chemical causes skin sensitization, a common safety test traditionally conducted on animals. One model was developed using data from hundreds of chemicals and was able to accurately predict allergic reactions through pattern recognition (Kwon, 2026).<\/p>\n\n\n\n Generative AI systems go a step further by simulating entire biological responses. The Nature article describes a model called AnimalGAN, which was trained on data from thousands of laboratory animals. It can generate virtual test subjects and predict outcomes like liver toxicity. When used in simulated experiments, this model successfully ranked drugs based on their potential to cause liver damage (Kwon, 2026). The AIP article supports this by explaining that AI-driven platforms integrate diverse datasets to model complex biological interactions, making them powerful tools for toxicology predictions (Barua et al., 2025). These computational methods are especially valuable alternatives because they are efficient, less costly, and more ethical.<\/p>\n\n\n\n Despite the advances, NAMs still face significant biological and technical limitations. A major issue is that many models are \u201creductionist,\u201d meaning they focus on specific cell types or systems rather than the entire organism. For instance, a kidney-on-a-chip might only include one type of kidney cell, even though a real kidney contains many different cell types that interact (Kwon, 2026). This makes it difficult to fully replicate how drugs affect whole systems.<\/p>\n\n\n\n Another limitation is the difficulty in modeling interactions between different organ systems. In the human body, organs communicate through networks such as the nervous system. These interactions are highly complex and not yet fully understood by current NAMs. Processes like aging, immune responses, and hormonal regulation are hard to recreate in a laboratory setting. The Nature article notes that whole-organ interactions and tissue aging remain major challenges, so animal studies are still needed in some cases (Kwon, 2026).<\/p>\n\n\n\n Technical challenges also exist because, while AI models are powerful, they are only as good as the data they are trained on. This can lead to biases or limits in their predictive accuracy.<\/p>\n\n\n\n In summary, New Approach Methodologies are transforming drug testing by providing more human-relevant and ethically responsible alternatives to animal testing. Technologies like IPSC-derived organoids, organs-on-chips, and AI-based computational systems allow for more accurate predictions of human responses. However, their current limitations, especially in modeling whole-body processes, mean they cannot yet fully replace animal testing. With ongoing research, scientists can unlock the full potential of these methods and move toward a future where animal testing is no longer necessary.<\/p>\n\n\n\n References<\/strong><\/p>\n\n\n\n Barua R., Das D., & Biswas N. (2025). Revolutionizing drug evaluation system with organ-on-a-chip and artificial intelligence: A critical review. Biomicrofluidics, 19(6), Page1. 10.1063\/5.0268362<\/p>\n\n\n\n Kwon, D. (2026, February 25). The age of animal experiments is waning. Where will science go next?. Publication_Title, https:\/\/www.nature.com\/articles\/d41586-026-00563-3<\/p>\n\n\n\n An L., Liu Y., & Liu Y. (2025). Organ-on-a-Chip Applications in Microfluidic Platforms. Micromachines<\/em>, 16(2), 201. 10.3390\/mi16020201<\/p>\n","protected":false},"excerpt":{"rendered":" Animal testing is one of the most important steps in getting a drug approved by the U.S. Food and Drug Administration (FDA), and it is part of a larger process designed to protect public health. Although many FDA-approved drugs cause side effects, the FDA’s role is to determine whether the benefits of a drug outweigh … Continue reading Scientific Literacy 1: Background Essay<\/span><\/a><\/p>\n","protected":false},"author":31937,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":"","wds_primary_category":0},"categories":[1],"tags":[4,6,5],"_links":{"self":[{"href":"https:\/\/student.wp.odu.edu\/aedmo011\/wp-json\/wp\/v2\/posts\/51"}],"collection":[{"href":"https:\/\/student.wp.odu.edu\/aedmo011\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/student.wp.odu.edu\/aedmo011\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/student.wp.odu.edu\/aedmo011\/wp-json\/wp\/v2\/users\/31937"}],"replies":[{"embeddable":true,"href":"https:\/\/student.wp.odu.edu\/aedmo011\/wp-json\/wp\/v2\/comments?post=51"}],"version-history":[{"count":3,"href":"https:\/\/student.wp.odu.edu\/aedmo011\/wp-json\/wp\/v2\/posts\/51\/revisions"}],"predecessor-version":[{"id":54,"href":"https:\/\/student.wp.odu.edu\/aedmo011\/wp-json\/wp\/v2\/posts\/51\/revisions\/54"}],"wp:attachment":[{"href":"https:\/\/student.wp.odu.edu\/aedmo011\/wp-json\/wp\/v2\/media?parent=51"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/student.wp.odu.edu\/aedmo011\/wp-json\/wp\/v2\/categories?post=51"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/student.wp.odu.edu\/aedmo011\/wp-json\/wp\/v2\/tags?post=51"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}Scientific Literacy 2: New Approach Methodologies<\/strong><\/h1>\n\n\n\n