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FAQs About the Use of Animals in Science

The following is from  FAQs About the Use of Animals in Science: A handbook for the scientifically perplexed.

Why does the use of animals as predictive models persist in drug testing and disease research?

Many factors contribute to the continued use of animals as predictive models, and little, if any have anything to do with science. The animal experimentation industry is a multi-billion dollar business, with many vested interests in both industry and academia that have much to gain by maintaining the status quo—and much to lose by a dramatic change in how research is conducted. Upton Sinclair in his 1935 classic I, Candidate for Governor: And How I Got Licked wrote: “It is difficult to get a man to understand something when his salary depends upon his not understanding it.”

How would you describe the position of the scientific community relative to the value of the animal model?

Overall, there is an awakening within the scientific community that animal experiments are not accomplishing what they set out to do from the standpoint of prediction. More and more scientists are beginning to question the validity of the animal model but are reluctant to state that publicly for fear of committing career suicide. With their livelihoods and professional stature at stake, as well as those of their colleagues—not to mention the financial security of the university that employs them—most scientists stick to the “party line” that animals can predict human drug and disease response.

It is important to remember here that the biological sciences account for the vast majority of grant money for most universities and hence even someone from the chemistry or math department will hesitate to point out flaws in the money machine for the university. Until a critical mass of scientists is reached, do not expect to hear scientists, even scientists outside the biological sciences, speaking out.

How does the publish or perish system in academia fit into this?

At most universities in the United States, PhDs in science are promoted, and thus more highly compensated and respected, on the basis of how many papers they publish in the scientific literature. It is a system that remains deeply entrenched in academia despite being widely criticized.

Conducting animal studies is the most efficient way to generate a large number of papers in the shortest amount of time. It is far easier and faster to crank out five papers using animals than to conduct human-based research. The five papers may contribute nothing to ease human suffering, but that has never been a requirement for promotion.

Proposals for animal experiments are also an excellent way for universities to obtain lucrative research grants, which can provide substantial revenue for their institutions. These grants generally come from the National Institutes of Health (NIH), the federal agency in charge of allocating taxpayer-generated funds for biomedical research, as well as from other government agencies and private foundations. The public—and the policy makers who appropriate taxpayer funds—are willing to fund this research because they have been led to believe that results derived from animal experiments are directly relevant for human health and well-being.

Are you implying that no one believes in the animal model—that it’s all just a game?

No. There are many scientists who we would describe as true believers. They really are convinced that animal models predict human biomedical outcomes.

Sometimes it’s a matter of naiveté. PhDs start out using the animal models because their professor tells them to and by the time they are ready to perform research on their own, the animal model is all they know how to use. Initially, some of these people really believed that the animal model works, in part because they do not see the results of animal studies in the clinics as physicians do. They really believe that they are helping to cure disease. Eventually, many do figure out that the animal model fails—by that time, though, they have a mortgage and three kids in college. (See comments by Dr Hicks in Chapter 2.)

That doesn’t say much for those in the scientific community. Don’t you think they’re smarter than that?

Sometimes very well educated and very smart people say very wrong things. Clever people can make genuine mistakes. They may also voice their opinion because of ego or because they have an ulterior motive. The bottom line is that while people can make innocent mistakes, sometimes they just lie. There is a difference. Susan Jacoby writing in The Age ofAmerican Unreason stated:

Junk thought should not be confused with stupidity or sheer ignorance, because it is often employed by highly intelligent people to mislead and confuse a public deficient in its grasp of logic, the scientific method, and basic arithmetic required to see through the pretensions of poorly designed studies. [ (Jacoby 2008) p229]

Sometimes, there is a difference between what the scientific evidence supports and what scientists say. The motto of the Royal Society for the Advancement of Science in London, England (the world’s oldest scientific society) is Nullius in Verba, which translated loosely as Don’t take anyone’s word for it. In the present context, this is good advice.

History, however, is replete with examples of very smart people simply making mistakes: Martin Blaser, director of the Division of Infectious Medicine at Vanderbilt University, called Barry Marshall’s claim that the bacteria Helicobacter pylori caused ulcers, “the most preposterous thing I have ever heard (Mohnmaney 1993).” (Dr. Marshall received the Nobel Prize in Physiology or Medicine in 2005 for his role in the discovery of the connection between H. pylori and gastric disease, reversing decades of medical doctrine which held that stress, spicy foods, and too much acid in the stomach causes all stomach ulcers.)

Louis Agassiz, the famed paleontologist, glaciologist, and geologist who first proposed that the earth had been subject to a past ice age, denied Darwin’s theory of evolution and said in 1867: “I trust to outlive this mania [(Pigliucci 2002) p13].” He wasn’t the only one. The great geologist Charles Lyell also denied evolution, believing instead that there were many centers of creation where new species appeared as needed [Ibid.].

Lord Kelvin, the great mathematician and physicist who developed the Kelvin scale of absolute temperature measurement, thought the sun had not been around long enough for evolution to be the modus operandi of the forms we have today [Ibid p21]. Lord Kelvin (truly one of the brightest people ever to have lived) also thought that the study of physics had almost yielded essentially all truths as of 1900. Even today, there are many smart people who doubt evolution and others who underestimate the amount of truth science has yet to reveal.

Many otherwise sophisticated people in England rejected the Germ Theory of Disease, vaccines, and science as a thought process for decades in the 1800s.

Astronomer Simon Newcomb published a paper explaining why airplanes would never fly. His analysis was perfect except for the lift effect of airfoil (the reason airplanes fly)—and perhaps his timing as well. He published his analysis two months before the Wright brothers flew.

Even the brightest, most disciplined, and ambitious among us are resistant to change. If we’ve always done something the same way, we’re unlikely to change unless forced to do so. So when scientists who’ve been experimenting on animals for years, and who have published the results in hundreds of articles in professional journals, are confronted with solid evidence of the futility of the animal model, it is no wonder that they either balk or dig their heels in. In that respect, they allow themselves to become victims of the system by blindly following in the footsteps of previous animal modelers.

Sometimes, too, it’s a question of differentiating how animals are actually being used. If you confuse using animals as predictive models with using them as a modality for the generation of ideas, then clearly you are going to be using faulty reasoning. We often see this in what animal modelers themselves claim about animals predicting human response. It can actually be a very contentious issue because many animal modelers and their supporters claim that no one seriously believes or claims that animal models are predictive—rather, they are used merely as heuristic devices. Yet their statements in the scientific literature (some of which appear below) would seem to indicate otherwise, not to mention the fact that they use the predictive value of the animal model to justify its use to the taxpaying public and their policy makers.

For example, Gad wrote in Animal Models in Toxicology 2007:

Biomedical sciences' use of animals as models to help understand and predict responses in humans, in toxicology and pharmacology in particular, remains both the major tool for biomedical advances and a source of significant controversy . . . by and large animals have worked exceptionally well as predictive models for humans-when properly used . . . Animals have been used as models for centuries to predict what chemicals and environmental factors would do to humans . . . This work [in 1792] consisted of dosing test animals with known quantities of agents (poisons or drugs), and included the careful recording of the resulting clinical signs and gross necropsy observations. The use of animals as predictors of potential ill effects has grown since that time . . . Very few are familiar enough with some of the history of toxicity testing to be able to counter with examples where it has not only accurately predicted a potential hazard to humans, but where research has directly benefited both people and animals. There are, however, many such examples. Demonstrating the actual benefit of toxicology testing and research with examples that directly relate to the everyday lives of most people and not esoteric, basic research findings (which are the most exciting and interesting products to most scientists) is not an easy task . . . If we correctly identify toxic agents (using animals and other predictive model systems) in advance of a product or agent being introduced into the marketplace or environment, generally it will not be introduced (or it will be removed) and society will not see death, rashes, renal and hepatic diseases, cancer, or birth defects, for example. (Gad 2007) (Emphasis added.)

Hau, the author of a well-known handbook on animal experimentation, has observed: “A third important group of animal models is employed as predictive models. These models are used with the aim of discovering and quantifying the impact of a treatment, whether this is to cure a disease or to assess toxicity of a chemical compound(Hau 2003).” Akkina is saying the same: “A major advantage with this in vivo system [genetically modified SCID mice] is that any data you get from SCID-hu mice is directly applicable to a human situation(Anonymous 2008).”

Fomchenko and Holland express a similar sentiment in 2006:

GEMs [genetically engineered mice] closely recapitulate the human disease and are used to predict human response to a therapy, treatment or radiation schedule . . . Using  in vitro systems and  in vivo xenograft brain tumor modeling provides a quick and efficient way of testing novel therapeutic agents and targets, knowledge from which can be translated and tested in more sophisticated GEMs that faithfully recapitulate human brain tumors and will likely result in high-quality clinical trials with satisfactory treatment outcomes and reduced drug toxicities. Additional use of GEMs to establish causal links between the presence of various genetic alterations and brain tumor initiation or determining their necessity for tumor maintenance and/or progression provide us with a glimpse into other important aspects of brain tumor biology. (Fomchenko and Holland 2006)

Krewski et al. of the Committee on Toxicity Testing and Assessment of Environmental Agents imply the predictability of animal models when they state:

For the foreseeable future, some targeted testing in animals will need to continue, as it is not currently possible to sufficiently understand how chemicals are broken down in the body using tests in cells alone. These targeted tests will complement the new rapid assays and ensure the adequate evaluation of chemicals. (Committee on Toxicity Testing and Assessment of Environmental Agents 2006.

Andrew Rowan, now of the Humane Society of the United States, stated in a book review of Brute Science in 1997:

The differences in xenobiotic metabolism . . . are well known to toxicologists and are taken into consideration when trying to predict potential effects in humans. Such differences are not insuperable problems nor do they render all animal toxicology useless. (Rowan 1997)

This use of prediction is not confined to the scientific literature. If anything, it is even more widespread when scientists are speaking to the public. Chris Smith, a doctor and a clinical lecturer in virology at Cambridge University who hosts The Naked Scientist podcast, stated in the October 21, 2008 podcast:

This week scientists have made a giant step forward really in a bit of work which might help people who are paralyzed because they have had a spinal cord injury to get moving again. They’ve shown this just using monkeys to start with but monkeys are very good models for how humans work so we think the same technique should work in humans(Smith October, 19 2008).

While science as a whole is self-correcting and the scientific method is the best way we have of understanding the material world, scientists are still human, with all the frailties associated with being human. Many scientists have not questioned the basis of their belief in the utility of animal-based studies because it is so traditional and so deeply ingrained that it seems like a fundamental fact of life.


Anonymous. 2008. Of Mice...and Humans. Drug Discovery and Development 11 (6):16-20.

Committee on Toxicity Testing and Assessment of Environmental Agents, National Research Council. 2006. Toxicity Testing for Assessment Agents: Interim Report: National Academies Press.

Fomchenko, E. I., and E. C. Holland. 2006. Mouse models of brain tumors and their applications in preclinical trials. Clin Cancer Res 12 (18):5288-97.

Gad, SC. 2007. Preface. In Animal Models in Toxicology, edited by S. Gad: CRC Press.

Hau, Jann. 2003. Animal Models. In Handbook of Laboratory Animal Science. Second Edition. Animal Models, edited by J. Hau and G. K. van Hoosier Jr: CRC Press.

Jacoby, Susan. 2008. The Age of American Unreason: Pantheon.

Mohnmaney, T. 1993. Marshall’s Hunch. New Yorker, 64-72.

Pigliucci, Massimo. 2002. Denying Evolution: Sinauer.

Rowan, Andrew. 1997. Book Review. Brute Science. Animal Welfare 6:378-81.

Smith, Chris. October, 19 2008. The Naked Scientist Podcast. In Fusion: The Power of the Sun.


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