Too Good to be True

| by Dr Ray Greek
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John Ioannidis, Malcolm Macleod, and colleagues have authored a study reviewing the use of animals in research.[1] They found that “the results [were] too good to be true” according to Ioannidis.[2]

Tsilidis et al conducted an analysis of 4000 data sets from animal studies of neurological disease. They discovered that 40% of the studies revealed a statistically significant result. This number was far above what would have been expected based on the number of animals studied. Heidi Ledford, writing for Nature, explains: “The results suggest that the published work — some of which was used to justify human clinical trials — is biased towards reporting positive results.” These results are in line with our recent article on mouse models of amyotrophic lateral sclerosis.

Ledford points out that others have faulted animal studies based on the small sample sizes and lack of binding. One possible correction for this is standardization of protocols followed by systematic reviews. We addressed this in our article: Systematic Reviews of Animal Models: Methodology versus Epistemology. Even if all the problems with animal studies were corrected and the researchers using animals were finally doing proper science, animal models will never be of predictive value for humans in terms of drug and disease response because animals and humans are examples of evolved complex systems. I call this Trans-Species Modeling Theory (TSMT).[3] *

John Ioannidis and Malcolm Macleod are brilliant, yet both continue to be apologists for the animal model machine. There is no excuse for scientists that obviously understand evolutionary biology and complex systems but continue to defend the position that animal models have predictive value for human response to drugs and disease. There simply is no “reasonable prospect of efficacy in human disease,” that is provided by animal models.[4-9] Granted animal models can generate hypotheses but that is far cry from being of predictive value. Dreams can generate hypotheses.

The institutions where these men work have heavily invested in animal models and I understand that all of heaven would come down on their heads if they were to state the obvious. But that does not excuse them as human lives are at stake. They are cowards.

*For more on TSMT please read the numerous articles I have published on animal models in the peer-reviewed literature. These can be found on PubMed or Google Scholar and most are open access.


1.         Tsilidis, K., et al., Evaluation of Excess Significance Bias in Animal Studies of Neurological Diseases. PLoS Biol, 2013. 11(7): p. e1001609.

2.         Ledford, H. Animal studies produce many false positives. 2013 July 16, 2013 [cited 2013 July 17]; Available from:

3.         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: p.

4.         Seok, J., et al., Genomic responses in mouse models poorly mimic human inflammatory diseases. Proceedings of the National Academy of Sciences of the United States of America, 2013.

5.         Suter, K., What can be learned from case studies? The company approach., in Animal Toxicity Studies: Their Relevance for Man, C. Lumley and S. Walker, Editors. 1990, Quay: Lancaster. p. 71-8.

6.         DiMasi, J.A., et al., Trends in risks associated with new drug development: success rates for investigational drugs. Clinical Pharmacology and Therapeutics, 2010. 87(3): p. 272-7.

7.         Arrowsmith, J., Trial watch: Phase II failures: 2008-2010. Nat Rev Drug Discov, 2011. 10(5): p. 328-329.

8.         Morgan, P., et al., Can the flow of medicines be improved? Fundamental pharmacokinetic and pharmacological principles toward improving Phase II survival. Drug Discovery Today, 2012. 17(9/10): p. 419-24.

9.         KMR Group. R&D Performance. 2012 August 8, 2012 [cited 2013 July 12]; Available from: https:// KMR PBF Success Rate & Cycle Time Press Release.pdf.