Strengths and Limitations of Animal Models in Biomedical Research

Desira Sloan

Biology 293 (Cell Biology)

Dr. Christina Steel

March 1, 2026

The U.S. Food and Drug Administration (FDA) recently announced that it wants to reduce the use of animal models. This shows a big change in how scientists study medicine. Animal studies have been used for over 100 years. They help researchers understand how the body works, how diseases happen, and if new drugs are safe. At the same time, new technologies like “organ-on-a-chip” and computer models show that animals are not always perfect for predicting human results. To understand why the FDA is moving away from animal testing, it is important to look at both the strengths and weaknesses of animal models.

One strength of animal models is that they let scientists study the whole body. Animals have organs and systems like the heart, lungs, brain, and immune system that work together. This allows researchers to see how a medicine or disease affects the body as a whole. For example, mice are used to study cancer and the immune system because scientists can observe both at the same time (Mak, Evaniew, & Ghert, 2014). Cell cultures alone cannot show these complex effects.

Another strength is that scientists can change animals’ genes. Mice can be genetically modified, so a certain gene is removed or added. This helps researchers study what genes do and how they cause disease. Genetically modified mice have helped scientists learn more about diseases like cystic fibrosis and cancer (Capecchi, 2005).

A third strength is that animal models are used to test drug safety. Before new medicines are given to people, the FDA usually requires tests in at least two animal species. These tests can show if a drug harms organs, causes cancer, or affects unborn babies (Olson et al., 2000). Animal tests have helped prevent dangerous drugs from reaching humans.

A fourth strength is that animals show how drugs move through the body. Researchers can study absorption, distribution, metabolism, and excretion (ADME) in animals. This helps find safe doses and possible side effects. For example, studying liver metabolism in animals helps predict how drugs will be processed in humans (Martignoni, Groothuis, & de Kanter, 2006).

Even with these strengths, animal models have weaknesses. One problem is that animals do not always predict human results. Many drugs that work in mice do not work in humans. For example, treatments that helped rodents after strokes did not help people (van der Worp et al., 2010). Differences in genes, immune systems, and diseases make results from animals less reliable.

A second weakness is that animals’ bodies and metabolism can differ from those of humans. Enzymes that process drugs, like cytochrome P450, are different in animals. This can make a drug seem safe in animals but dangerous in humans—or safe in humans but harmful in animals (Martignoni et al., 2006).

Third, animals do not always fully mimic human diseases. Lab animals are usually young, have similar genes, and live in controlled environments. Humans are more diverse in age, health, and genetics. For example, mouse models of Alzheimer’s disease only show part of the disease seen in humans (Mak et al., 2014).

A fourth weakness is ethics. Animal studies can cause pain, stress, or long-term confinement. Society expects scientists to follow the “3Rs”: Replacement, Reduction, and Refinement. These rules try to reduce the number of animals used and avoid suffering. Many people think we should use alternatives when possible.

Other issues include high costs, long study times, and differences between studies that make results hard to repeat. Some experiments are small or done in slightly different ways, which can make findings less reliable (van der Worp et al., 2010).

In conclusion, animal models have been very important in science. They allow scientists to study the whole body, change genes, test drug safety, and see how drugs move in the body. But animals are not perfect. Humans and animals differ, diseases are not fully replicated, ethical concerns exist, and results are not always reliable. This is why the FDA is looking for alternatives. Using new technologies along with animal studies can make research safer, more ethical, and more accurate.

Scientific Literacy 2: New Approach Methodologies

Desira Sloan

Biology 293 (Cell Biology)

Dr. Christina Steel

April 5, 2026

New Approach Methodologies (NAMs) are revolutionizing scientific research, particularly in efforts to reduce animal testing. Animals have been the primary subjects of drug and disease studies, even though their physiological differences from humans often yield unreliable results. Scientists are now developing advanced, human biology-centric methods, including organs on chips, 3D organoids, and computational models. While these innovations hold significant meaning for the future, they currently face limitations that prevent the complete elimination of animal testing.

Organs-on-chips and 3D organoids use special cells called induced pluripotent stem cells (iPSCs), which are adult human cells that scientists reprogram so they can turn into many types of cells. This then allows researchers to grow human tissues, like liver or heart cells, in a lab to study how drugs affect them. Organ-on-chips go a step further by placing these cells into tiny devices that mimic real body conditions, such as blood flow and/or movement. This makes them more accurate for studying how drugs are processed in the human body, like in a liver-on-a-chip system (Kwon, 2026).

Organoids are small, 3D groups of cells that grow and organize themselves to act like mini organs. They copy important features of real tissues, including how cells interact with each other. Since organoids and organ-on-chip models are made from human cells, they are often more accurate than animal models. This is important because about 86% of drugs fail in human clinical trials even after working in animals (Kwon, 2026). Using human-based models can help improve the chances of success.

Computational models and artificial intelligence (AI) are another key part of new approach methods (NAMs). They use large amounts of experimental and human data to predict how chemicals and drugs will affect the body. For example, AI can estimate whether a substance may irritate the skin by comparing it to known irritants. These tools are becoming more accepted for certain safety tests (Kwon, 2026).

Advanced AI, like generative AI, can even stimulate experiments. For example, AnimalGAN uses past data to predict toxic effects, such as liver damage, without using animals. These AI methods are faster, cheaper, and more ethical, which is why they are becoming more widely used.

Research shows that NAMs are being used more and more. One large study found that over the past 20 years, the number of research papers using only non-animal methods has grown a lot and now exceeds those using animals (Taylor et al., 2024). By 2022, studies using only NAMs were almost three times more common than animal-based studies, showing a clear move away from animal testing. However, the study also pointed out that simpler methods, like tissue models and computer simulations, are used more often than advanced tools like organ-on-chips, which are still being developed.

Even with their benefits, NAMs have some limitations. One main issue is that they are “reductionist,” meaning they study parts of the body separately instead of the whole system. For example, a liver-on-chip can show how the liver reacts to a drug, but cannot fully mimic how it interacts with other organs like the kidneys or the immune system.

Additionally, these models have trouble showing long-term effects, like aging or chronic diseases. Lab-grown tissues often behave like young cells, which can give misleading results for older people. It’s also hard to study hormonal systems, since they depend on complex signals between organs. Due to this, animal testing is still needed to understand how the body reacts.

Technical challenges still remain. Proving that these new methods can completely replace animal testing requires thorough validation, which takes a lot of time and resources. Also, growing reliable and stable cell models, especially from stem cells, continues to be difficult.

In summary, New Approach Methodologies (NAMs) are improving scientific research by providing more human-focused and ethical alternatives to animal testing. Tools like organoids, organ-on-chips, and AI models make research faster and more accurate. However, because they cannot yet capture the full complexity of the human body, animal testing is still needed. As these technologies continue to develop, they are expected to play an even bigger role in science and further reduce the use of animals.