A November 10, 2011, press release from the University of California – San Diego titled, Knocking out key protein in mice boosts insulin sensitivity,states: “By knocking out a key regulatory protein, scientists at the University of California, San Diego School of Medicine and the Ecole Polytechnique Federale de Lausanne (EPFL) in Switzerland dramatically boosted insulin sensitivity in lab mice, an achievement that opens a new door for drug development and the treatment of diabetes.” The entire article can be found here, for a fee. This is typical animal-based research. Researchers create a knock-out mouse that they hope will inform them about the human condition. This is interesting science and can be used as a heuristic or to learn more about mice. However, the track record for knock-outs predicting human response is poor and genome studies are performed in humans everyday. Consider the following.
Geerts, of In Silico Biosciences in 2009, stated:
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The tremendous advances in transgene animal technology, especially in the area of Alzheimer's disease, have not resulted in a significantly better success rate for drugs entering clinical development. Despite substantial increases in research and development budgets, the number of approved drugs in general has not increased, leading to the so-called innovation gap. While animal models have been very useful in documenting the possible pathological mechanisms in many CNS diseases, they are not very predictive in the area of drug development. . . . This has led others to question the predictability of rodent animal models. A live discussion on the Alzforum website, called 'Mice on trial; issues in the design of drug studies2; recently gathered ideas and suggestions from many researchers working in the field of amyotrophic lateral sclerosis as to why so many drugs that work in animal models fail in the clinic. Similarly, clinical researchers in the field of spinal cord injury are questioning the face validity of animal models. Of the 22 drugs shown to provide benefit in animal models of spinal cord injury, none of them worked in the clinical situation. . . . 
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Gabor Miklos wrote in 2005:
There is enormous phenotypic variation in the extent of human cancer phenotypes, even among family members inheriting the same mutation in the adenomatous polyposis coli (APC) gene believed to be causal for colon cancer. In the experimental mouse knockout of the catalytic gamma subunit of the phosphatidyl-3-OH kinase, there can be a high incidence of colorectal carcinomas or no cancers at all, depending on the mouse strain in which the knockout is created, or into which the knockout is crossed . . . Thus, although a mutation-cataloging research megaproject may be a diverting occupation for sequencing centers and gene hunters, leading scientists should think carefully before they tout its therapeutic promise to patients and politicians. The simple truth is that the money would be much better spent if research priorities were reevaluated. A good place to start would be to dismiss the fallacious notion that single mutations in primary tumors are the optimal starting point for research that would lead to the discovery of new, more effective cancer drugs. The clinical reality is that it is not single genes, but rather the properties of aneuploid-based methylated networks that allow metastatic cancer cells to explore novel niches in different genetic backgrounds and to rapidly become resistant to drug-based therapies. 
Nijhout stated in 2003: “The importance of context is also illustrated by studies of the effects of “knockouts” of specific genes in mice, a method that completely eliminates the function of a gene’s product. For example, knockout of a retinoblastoma-related gene causes severe abnormalities and embryonic death in one strain of mice, but the same mutation in another strain has no effect. The mutant mice are viable and become fertile adults, as shown by Michael Rudnicki  and his colleagues at McMaster University.” 
Van Regenmortel wrote in 2004:
However, there is probably a more fundamental reason for these failures: namely, that most of these approaches have been guided by unmitigated reductionism. As a result, the complexity of biological systems, whole organisms and patients tends to be underrated . Most human diseases result from the interaction of many gene products, and we rarely know all of the genes and gene products that are involved in a particular biological function. Nevertheless, to achieve an understanding of complex genetic networks, biologists tend to rely on experiments that involve single gene deletions. Knockout experiments in mice, in which a gene that is considered to be essential is inactivated or removed, are widely used to infer the role of individual genes. In many such experiments, the knockout is found to have no effect whatsoever, despite the fact that the gene encodes a protein that is believed to be essential. In other cases, the knockout has a completely unexpected effect . Furthermore, disruption of the same gene can have diverse effects in different strains of mice . Such findings question the wisdom of extrapolating data that are obtained in mice to other species. In fact, there is little reason to assume that experiments with genetically modified mice will necessarily provide insights into the complex gene interactions that occur in humans (Horrobin, 2003). The disappointing results of knockout experiments are partly caused by gene redundancy and pleiotropy, and the fact that gene products are components of pathways and networks in which genes acting in parallel systems can compensate for missing ones . As many factors simultaneously influence the behaviour of a system, one part might function only in the presence of other components. The essential contribution of other genes in achieving a particular function will therefore be missed, which will further encourage the reductionist view that a single gene has adequate explanatory power  It remains true that human disease is best studied in human subjects (Horrobin, 2003). 
Studying anatomy, physiology, and biochemistry in animals can be useful if the animals are used as a heuristic, but anatomy, physiology, and biochemistry imply function and function varies greatly among organisms, despite other similarities. Studying events in the cell can be done using animal or human cells but human cells should be used in order to decrease the probability of inter-species differences influencing the results. When the level of study moves to the whole intact system and the intact system argument is used to justify inter-species extrapolation, that argument fails. (For more see Vivisection Or Death: Part III, No Other Options.)
1. Geerts H (2009) Of mice and men: bridging the translational disconnect in CNS drug discovery. CNS Drugs 23:915-926. 10.2165/11310890. http://www.ncbi.nlm.nih.gov/pubmed/19845413.
2. Miklos GLG (2005) The human cancer genome project--one more misstep in the war on cancer. Nat Biotechnol 23:535-537. nbt0505-535 [pii] 10.1038/nbt0505-535. http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=15877064.
3. Lecouter JE, Kablar B, Whyte PF, Ying C, Rudnicki MA (1998) Strain-dependent embryonic lethality in mice lacking the retinoblastoma-related p130 gene. Development 125:4669-4679. http://dev.biologists.org/content/125/23/4669.abstract.
4. Nijhout HF (2003) The Importance of Context in Genetics. American Scientist 91:416-423.
5. Horrobin DF (2001) Realism in drug discovery—could Cassandra be right? Nat Biotech 19:1099-1100. http://dx.doi.org/10.1038/nbt1201-1099.
6. Morange M (2001) A successful form for reductionism. The Biochemist 23:37-39.
7. Pearson H (2002) Surviving a knockout blow. Nature 415:8-9. 10.1038/415008a 415008a [pii]. http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=11780081.
8. Morange M (2001) The misunderstood gene. Harvard University Press, Cambridge.
9. Van Regenmortel M (2004) Biological complexity emerges from the ashes of genetic reductionism. Journal of Molecular Recognition 17:145-148. http://dx.doi.org/10.1002/jmr.674.
10. Van Regenmortel MH (2004) Reductionism and complexity in molecular biology. Scientists now have the tools to unravel biological and overcome the limitations of reductionism. EMBO Rep 5:1016-1020. 7400284 [pii] 10.1038/sj.embor.7400284. http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=15520799.