The development of New Approach Methodologies (NAMs) is changing how scientists study drugs and human health. Instead of relying on animal testing, researchers are now using systems like organs-on-chips, 3D organoids, and computer models to better represent how the human body works. These methods are important because animal models do not always predict human responses accurately, so using human-based systems can improve results (Nature, 2026).
One major advancement is the use of organs-on-chips and 3D organoids, which are often made using induced pluripotent stem cells (iPSCs). These are human cells that have been reprogrammed to act like stem cells, meaning they can turn into various types of cells. Organoids grow into small, 3D structures that act like real organs, such as the liver or brain. Organs-on-chips go a step further by adding fluid flow and physical forces, helping cells behave more like they would inside the body. Because these systems are based on human cells, they give more realistic results than animal models. For example, liver-on-a-chip models are typically better predict how a drug might be toxic to humans compared to animal testing (Pal et al., 2025)
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Another important part of NAMs is the use of computational models and AI. These tools analyze large amounts of biological data to predict how chemicals or drugs will affect the body. For example, AI can predict skin reactions or liver damage by comparing new chemicals to existing data. This allows researchers to test many compounds quickly without using animals. According to the Nature article, these models are becoming more advanced and can even simulate biological responses, helping scientists make decisions earlier in drug development (Nature, 2026). This saves time, reduces costs, and avoids unnecessary testing.
Even though these methods are promising, they still have some limitations. Many NAMs are considered reductionist, meaning they focus on one part of the body instead of the whole system. For example, an organoid might model the liver, but it cannot fully show how the liver interacts with other organs like the kidneys or immune system. This makes it harder to study complex processes like whole-body responses or hormone signaling. While scientists are working on multi-organ systems, they are not yet perfect (Yang et al., 2020).
Another challenge is modeling aging and long-term changes. Most lab-grown cells do not fully represent how cells change over time in the body. This can affect how accurately diseases or drug effects are studied. There are also technical issues, like differences in how organoids grow, which can make results less consistent. In addition, AI models depend on the quality of the data they are trained on. If the data is limited or biased, the predictions may not be completely accurate.
In conclusion, NAMs are a big step forward in replacing animal testing. Technologies like organoids and organs-on-chips create more realistic environments for human cells, while AI helps predict how drugs will affect the body. However, these methods still cannot fully replace the complexity of the human body. As research continues, these tools will likely improve and become more reliable, helping scientists study human biology in a more accurate and ethical way.