Is a Future Without Animal Models Possible?
A remarkable number of scientific breakthroughs owe their existence to a cadre of animal models from both land and sea. But do we really need them? It’s a pertinent question in an experimental landscape populated by increasingly complex in vitro and digital systems. Even more so, given that the National Institutes of Health (NIH) is that focus exclusively on animal models.
The use of animals in research has always been a sticking point, an ethical conundrum and engine of scientific innovation in equal measure. And while the next frontier of science will lean into alternative model systems (e.g., organoids, organ-on-a-chip technologies and more), whether we ever move entirely away from animal models is less certain.
“The general idea of trying to limit the use of animals in research is a worthy goal,” said , William Henry Fitzbutler Collegiate Professor of Internal Medicine/Infectious Diseases at the University of Michigan. “[But] the rate at which things are being done—because there's an assumption that we have great alternatives for all of the uses of animals that we have—I think that's premature.”
Why Do We Use Animal Models?
Bodies are complex. This fact is at the heart of why animals have become integral to the scientific enterprise. Such models allow researchers to in “whole body” systems—without involving humans.
“I think the role for animal models is a bridge from really basic bench science to studies in people,” Young said. He listed several reasons why animals are advantageous, including the ability to conduct experiments with more subjects (and more experiments overall) at a comparatively lower cost than you can with people, as well as explore developmental processes at earlier life stages.
A key benefit of animal models is that scientists can experimentally modify the genetic and physiological blueprint of animals in ways that are, for technical and/or ethical reasons, not possible in people, such as knocking out genes. These alterations allow scientists to better understand why biological systems behave the way they do by altering their components to see what happens.
The for exploring host-microbe interactions, which encompass a vast web of connections between microbes, host cells/tissue, the immune system and microbiota. For example, while one can glean insights into how a pathogen engages with host cells in a dish, it is tricky to infer what the findings mean in the context of a full body system, where both the pathogen and host are active participants in the disease process. Animals help bridge that gap.
Countless breakthroughs have come from work in animal models, ranging from understanding how the microbiome impacts local and systemic development in the host (and vice versa) to accelerating the development and deployment of life-saving COVID-19 vaccines in the early days of the pandemic. It is reasonable to say we would not be where we are without them.
Animals Are Not People
Even so, animal models are not perfect. Their biggest limitation is also their most obvious feature: they are not humans. Young highlighted that while there may be similarities between, say, mice and people, their mean that not everything observed in mice translates to humans.
For , George Barth Geller Distinguished Professor of Immunology at Duke University, who studies barrier functions of the placenta, this distinction is critical. “Placental evolution is such that the mouse placenta is so far removed from a human placenta. And so, if you're studying pregnancy in a mouse, that's great, except you really are studying mouse pregnancy,” she said.
These discrepancies can , particularly in drug development. Candidate compounds that were may be ineffective (or, in a handful of cases, harmful) in people. —which are implanted with human-derived cells or —narrow the species divide somewhat, though there is only so “human” a mouse can become.
There's also the matter of ethics. to replace animal models with other systems when possible, reduce the number of animals used in experiments and refine those experiments to minimize potential distress to the animals. Still, the is a question that perpetually underlies the use of animal models.
It is for these reasons that federal agencies have accelerated the shift away from using animals at all. The U.S. Food and Drug Administration that it is phasing out animal testing in drug development (a move in the works since 2022). The , noting it will no longer ask for research proposals relying solely on animal models. that it will still support grants using lab animals “if scientifically appropriate, justifiable and with appropriate animal welfare oversight,” though the point is to continuously and drastically decrease animal use over time.
Oh My Organoid: Leveraging Alternative Model Systems
But this turn away from animal models prompts a turn toward something else, namely alternative research technologies and digital model systems. Collectively known as new approach methodologies (NAMs), these models leverage . The assumption is that by using such systems, scientific observations may more accurately reflect what happens in the human body.
A slew of systems fall under the NAM umbrella. Take . Derived from embryonic, induced pluripotent or adult stem cells, these 3D orbs mimic the structure and cellular composition of organs like the gut, brain and lungs. Scientists can incubate or inject organoids with different microbes, such as , , and , to understand how host tissues respond.
Coyne, a big proponent of organoids, uses them to study enteroviruses and human placental development—research areas for which animal models are not the most robust. Her lab’s has been particularly foundational. From a single full-term donor placenta, researchers can derive 2 types of organoids: one from the maternal component (the decidua) and one from the fetal component (trophoblast). Using these systems, the lab has explored topics like how human trophoblasts respond to congenitally transmitted pathogens (e.g., ).
technologies take the organoid idea a step further. These systems simulate aspects of the physiological environment that standard in vitro models lack, such as shear force or peristalsis, which are critical for tissue structure, function and . Indeed, preliminary work from Coyne’s lab shows that growing placental organoids under shear stress—mimicking the force of maternal blood flow—“fundamentally changes the biology of the cells.”
Many NAMs require a lab bench, but some scientists are focusing on the computational realm, building virtual models that encapsulate host-microbe interactions to examine disease. , a professor of microbiology and immunology at the University of Michigan and a 2025 American Academy of Microbiology fellow, is one such scientist. Her lab builds digital (in silico) models for tuberculosis to simulate infection dynamics over time. Their models the host immune response to Mycobacterium tuberculosis at the molecular, cellular, , organ and whole-host scale, allowing researchers to ask and answer questions in ways they may not be able to in the lab or clinic.
“A lot of stuff in biology happens at a single scale—you're pulling out some tissue; you're staining it; you're looking for a signal,” Kirschner explained. “But [anything] underneath or above that signal is kind of lost. You might have life or death of an animal to give you a big picture outcome, but for the most part, you’re sort of stuck at a single scale.” With computational models, scientists can zoom in and out of many biological layers with relative ease and identify mechanisms operating at and between scales.
No Model Has It All
Though NAMs are evolving, “they're not the ultimate answer,” Young said. Many emerging models are complex relative to standard in vitro systems, but still only represent a piece of a broader, interconnected system. The important point for NAMs, and any model system, is to understand what they’re modeling.
For example, “I think that organoids can tell us a lot about the human side of things,” Young noted. “[However], in my area of research, it's not clear how much the organoids tell us about the behavior of the microbe.” that the survival and colonization dynamics of E. coli lacking a key stress response regulator differed between human intestinal organoids and the germ-free mouse gut—a comparable in vivo model—suggesting how the bacterium responds to each environment, and the stressors inherent to those environments, vary. But which model is "right?" Well, it likely depends on what you're asking.
Coyne similarly highlighted that when a given model is used, it is context-specific; no single system makes sense for all research questions. “It’s very difficult to do true pathogenesis and immunology in an organoid,” she explained. “There's no immune component. There’re no immune cells.” If someone is studying T cells, for example, organoids are not the ideal choice. But “they make a really beautiful model to understand the epithelium, the barrier cells.”
Models also don’t exist in isolation. In silico models must be trained using data from other models or human studies. Indeed, the Kirschner Lab’s virtual TB models are built with data from humans and studies with non-human primates. Moreover, findings from these models must be tested and verified in others.
To that end, Kirschner emphasized that virtual models are useful in tandem with other systems and workflows to direct and refine experiments, the data of which can further hone the model. “[Digital modeling] can help optimize your system. It can help make predictions of the next-best experiment so you're not shooting in the dark.” She highlighted that digital models could be inserted in between pre-clinical drug testing in animals and clinical trials in humans to determine if a drug has a shot at success, potentially saving substantial time and money.
There is, ultimately, no perfect model system. A diverse toolbox filled with both new and established models is an asset to scientific progress and our ability to understand human health and disease.
A Future Without Animal Models?
Which raises the question: is eliminating animal models possible? During interviews for this article, the question was met with sharp skepticism. Young acknowledged that limiting the use of animal models is a goal worth striving for, but cautioned that “the blanket idea that, with a stroke of a pen, we're going to eliminate it [is] too extreme in the other direction.”
“I also think it can be very dangerous,” Coyne added. “I would certainly not want to be a patient enrolling in a clinical trial of something that had only ever been tested in an organoid. It must be put into some living system that has fully capable immune responses.”
There is the possibility that NAMs will increase in complexity to a point where they could fill in some of the gaps. Perhaps to recapitulate systems within the full human body, something researchers are already attempting. At some point, we may be able to generate of humans and all their composite, interlocking features. But Kirschner underscored that the only way that can happen is if we understand “every single nook and cranny” of an organ or system—and, right now, we don’t.
Apart from the conceptual limitations, the idea that animal models can be readily replaced by NAMs overlooks substantial technical and financial hurdles. “These policies clearly do not appreciate the barrier to entry here,” Coyne noted, alluding to the NIH’s blunt move to phase out animal testing. For instance, if someone plans to establish an organoid system in their lab, how are they going to do it? Where are they going to get the tissue/cells, especially if their institution doesn’t have an established health care branch? Do they to acquire those tissues? In Coyne’s eyes, if NAMs are going to be pushed to the forefront of research, institutions, including the NIH, must actively support scientists in their development and implementation.
The Importance of Communication
This idea taps into a broader need for open and honest communication and collaboration to shape the future of animal modeling. Forging partnerships between scientists using and developing diverse models can help ensure continued innovation in how research is conducted, and that the most pertinent systems are employed to advance scientific knowledge. “Collaboration is the best way to do science. There's no doubt about it, and there's no way we're going to move forward in the complicated world that we are in without it,” Kirschner said.
For Young, that collaboration extends beyond the research world, especially in a regulatory landscape with shifting scientific priorities. “We can say, ‘Okay, I really would love to decrease my use of animal models and be quicker to get to proving that something works in people,’” he said. “But [we need] to work together as a whole scientific community, plus the funders and regulatory agencies, toward that common goal.”
Effective communication is a powerful tool; with it, scientists can inform decisions about health and sustainability of the planet. Check out our Science Communicator's Toolkit for resources to help you hone your skills!
Author: Madeline Barron, Ph.D.
In This Issue
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- Is a Future Without Animal Models Possible?