U.S. Department of Energy Genomic Science program An immense body of empirical evidence has supported the position that animal models offer no predictive value for human response to drugs and disease. But perhaps more importantly, recent developments in evolutionary and developmental biology, genetics, gene regulation, gene expression, and gene networks gained in large part as a result of the Human Genome Project, in addition to advances in understanding complex systems, have significantly increased our understanding of why animals have no predictive value for human response to drugs or the pathophysiology of human diseases. Applying Complexity Theory and the Theory of Evolution to the problem of using one evolved, complex adaptive system (CAS) as a model in order to predict responses of a second, has resulted in what Dr. Ray Greek has called Trans-Species Modeling Theory (TSMT)1: While trans-species extrapolation is possible when perturbations concern lower levels of organization or when studying morphology and function on the gross level, one evolved, complex system will not be of predictive value for another when the perturbation affects higher levels of organization. TSMT allows scientists to place the empirical evidence regarding the failure of animal models in context. TSMT is a theory (although not universally accepted at present). In order to understand theory in science, note the following statements from the American Association for the Advancement of Science and the National Academy of Sciences. According to the American Association for the Advancement of Science: In detective novels, a “theory” is little more than an educated guess, often based on a few circumstantial facts. In science, the word “theory” means much more. A scientific theory is a well-substantiated explanation of some aspect of the natural world, based on a body of facts that have been repeatedly confirmed through observation and experiment. Such fact-supported theories are not “guesses” but reliable accounts of the real world. The theory of biological evolution is more than “just a theory.” It is as factual an explanation of the universe as the atomic theory of matter or the germ theory of disease. Our understanding of gravity is still a work in progress. But the phenomenon of gravity, like evolution, is an accepted fact. The National Academy of Sciences states: The formal scientific definition of theory is quite different from the everyday meaning of the word. It refers to a comprehensive explanation of some aspect of nature that is supported by a vast body of evidence. Many scientific theories are so well-established that no new evidence is likely to alter them substantially. For example, no new evidence will demonstrate that the Earth does not orbit around the sun (heliocentric theory), or that living things are not made of cells (cell theory), that matter is not composed of atoms, or that the surface of the Earth is not divided into solid plates that have moved over geological timescales (the theory of plate tectonics). Like these other foundational scientific theories, the theory of evolution is supported by so many observations and confirming experiments that scientists are confident that the basic components of the theory will not be overturned by new evidence. However, like all scientific theories, the theory of evolution is subject to continuing refinement as new areas of science emerge or as new technologies enable observations and experiments that were not possible previously. One of the most useful properties of scientific theories is that they can be used to make predictions about natural events or phenomena that have not yet been observed. For example, the theory of gravitation predicted the behavior of objects on the moon and other planets long before the activities of spacecraft and astronauts confirmed them. The evolutionary biologists who discovered Tiktaalik predicted that they would find fossils intermediate between fish and limbed terrestrial animals in sediments that were about 375 million years old. Their discovery confirmed the prediction made on the basis of evolutionary theory. In turn, confirmation of a prediction increases confidence in that theory. In science, a “fact” typically refers to an observation, measurement, or other form of evidence that can be expected to occur the same way under similar circumstances. However, scientists also use the term “fact” to refer to a scientific explanation that has been tested and confirmed so many times that there is no longer a compelling reason to keep testing it or looking for additional examples. In that respect, the past and continuing occurrence of evolution is a scientific fact. Because the evidence supporting it is so strong, scientists no longer question whether biological evolution has occurred and is continuing to occur. Instead, they investigate the mechanisms of evolution, how rapidly evolution can take place, and related questions. TSMT is supported by vast amounts of empirical evidence, is consistent with science outside of the specific areas of biology it addresses, and both explains current scientific facts as well as predicting the answers to future questions. Why is TSMT important? When AFMA was formed in 1999, the case against the predictive value of animal models for human drug and disease response was of the empirical or clinical variety. A wide variety of clinical studies and case reports had shown that, when compared with how drugs ultimately affected humans or how diseases affected humans, animal models had reacted the same way a small percentage of the time. That meant that animal models had failed to meet the scientific standard for burden of proof in terms of offering predictive value. From the perspective of the physician practicing medicine in the real world, this evidence would be sufficient to abandon the use of animal models in hopes of learning about drug and disease response in humans. For the clinician engaged in the world of cancer patients and auto accident victims, human response is the final arbitrator of truth—not what happens to animals in a laboratory. So when physicians observe a drug kill or maim even a small number of patients, that is enough proof for them to stop administering that drug, regardless of how much the drug was studied in the laboratory and what was learned from those studies. They don’t need to know—and are not necessarily even interested in—the pharmacology of the drug in eight different animal species. Far from the often messy and chaotic world of clinical medicine, some medical researchers believe, and have stated, that the laboratory (meaning the laboratory where animals are used) is the “true sanctuary” of medicine, as opposed to the clinic or hospital where clinical research is performed. Indeed, clinical medicine is fraught with variables that cannot be controlled, thus leaving any clinical study or observation open to criticism and second-guessing. In this respect, the animal-based researchers are correct in their assertion that laboratory-based research is much more controlled and thus, from their perspective, better than clinical medicine. But patients suffer from disease in the real world, not the artificial world of the laboratory, and hence must be studied in the real world. This is not intended to undermine the importance of in vitro or in silico research, provided such research is human-based. But the final arbiter of truth is how patients respond, not what happens in an animal or other non-human system. Accordingly, empirical evidence in the form of clinical observations, controlled studies, and case reports refuted the claims for predictive value by the animal model community. But the animal model community, as well as some that do not rely on animals, demanded more before abandoning animal models. Such people believe that what one aims for in science is an overarching theory that can predict outcomes without having to perform experiments every time a question is raised. Therefore, they asserted that the empirical evidence previously put forth had not been scientific enough, for it has failed in their view to adequately answer the “big” question: why do animal models fail? The reason animals sometimes—but more often do not—react as humans is being illuminated by our knowledge concerning genes, gene regulation, gene expression, and gene networks. This knowledge has come in large part from the results of the Human Genome Project and other similar genome projects. In addition to advances in genomics, application of Complexity Theory to biomedical research has informed scientists on the subject of animal models. This combination of scientific advances allows us to formulate an overarching theory to explain what we have observed empirically for decades. In short, all animals are examples of robust, complex systems (on many levels) and hence demonstrate emergence, are modular, are dependent upon initial conditions, and are nonlinear, in addition to exhibiting other relevant properties. This means that a perturbation to complex system S1 that led to effect A will not necessarily lead to effect A in complex system S2, regardless of how similar the two complex systems are currently or were at one time. Living complex systems manifest different responses to the same perturbation due to: 1. differences with respect to genes present;2. differences with respect to mutations in the same gene (where one species has an ortholog of a gene found in another);3. differences with respect to proteins and protein activity;4. differences with respect to gene regulation;5. differences in gene expression;6. differences in protein-protein interactions;7. differences in genetic networks;8. differences with respect to organismal organizations (humans and rats may be intact systems, but may be differently intact);9. differences in environmental exposures; and,10. differences with respect to evolutionary histories. These are some of the important reasons why even two nearly identical living complex systems (e.g., a chimpanzee and a human, or even monozygotic twins) may respond differently to drugs and experience different diseases, and hence why one evolved complex system/species cannot reliably predict responses for a different evolved complex system/species.Current biomedical research is studying disease and drug response at the level where the differences between complex systems (be they two different species or two different humans) are critical, hence using animals (e.g., vertebrates) as predictive or causal analogical models (CAMs) for human diseases and drug testing is a scientifically invalid paradigm.Because we have scientific theories, we don’t have to evaluate examples covered in the theory on a case-by-case basis, we just apply the theory. Theories and laws in science prohibit certain hypotheses. For example, the Germ Theory of Disease prohibited, and indeed replaced miasma—the notion that rotting organic matter caused disease. The Germ Theory does not prohibit other causes of disease, such as cancer, vascular abnormalities, and endocrine disorders, but it does mandate the clinician consider bacteria and viruses instead of rotting matter for certain clinical presentations. Likewise, Atomic Theory prohibits an infinite division of matter into smaller and smaller units, and the Theory of Relativity prohibits faster than light velocities. Suggesting that animal models must be evaluated on a case-by-case basis is like asking that each flora or fauna that fills an ecological niche be evaluated for achieving its position through an act of special creation or evolution. There is no logical reason to assume the trait in question was not the result of a special creation. But in light of theory—the Theory of Evolution—and empirical evidence, there is no reason to seriously consider such a hypothesis. Despite the development of an all-encompassing theory as to why animals offer very low predictive value, there remains—much to the detriment of human health and medical progress—extraordinary resistance to abandoning the use of animals as predictive models (see Why All the Opposition to AFMA?). The goal of AFMA, therefore, is to educate the scientific community, as well as society in general, about the urgent need to move away from the ineffective animal model and to move toward research methods that truly reflect the enormous strides science has made in knowledge of living systems.For more on TSMT, please read the books and article listed in the Resources section. Greek, R. and L.A. Hansen, Questions regarding the predictive value of one evolved complex adaptive system for a second: exemplified by the SOD1 mouse. Progress in Biophysics and Molecular Biology, 2013. http://dx.doi.org/10.1016/j.pbiomolbio.2013.06.002.