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The Predictive Value of Preclinical Research

Vivisection activists frequently claim that animal models are never, or very rarely, used to predict human response to drugs and disease and or deny that there is such a thing as predictive value in research in general. In his essay regarding mouse “avatars,” Dr Gorski characterizes opponents of animal-based research:

This generally involves cherry picking data and studies to paint as dim a view of animal research and its usefulness as possible, usually through a combination of exaggerating how bad the animals are treated and claiming that the research using animals doesn’t produce any useful results. One variant of this latter ploy is to claim that animal models aren’t “predictive” of human responses. Again, any animal models that are predictive are dismissed, and situations where animal models fall short are hyped to the max.

Note the scare quotes around predictive when Gorski is questioning the value of predictive value and the lack thereof when he is claiming some animal models are in fact predictive.

Gorski states in another blog:

In reality, the use of animals as “predictive models” that Dr. Greek keeps harping on is not nearly as large a slice of the pie when it comes to using animal models as he seems to think it is.

More scare quotes.

Gorski also stated in comments on the Dr Hall essay, Learning from Animals: Evolutionary Medicine with a Twist:

Indeed. It’s ridiculous to lump all animal models into a “class.” There are too many such animals used for too many purposes. Some animal models are more reliable than others. Such generalizations reveal more about the good Dr. Greek than and his ideology-inspired lack of nuance than they reveal about the actual utility of animal models.

Blue Sky Science wrote

It has been a debate shaped by Dr. Greek’s attempts to persuade readers to agree with his very narrow concept of what prediction means in biology and his frankly impoverished view on the role of basic research in advancing medical science, and to oblige those debating them to accept a playing field rigged to set them at a disadvantage.

So, on the one hand we have vivisection activists denying that predictive value even exists or denying that it should be applied to animals models. On the other hand, when it suits them, vivisection activists acknowledge that predictive value is routinely used in science and want to claim that animal models have predictive value and thus save lives.

Dr David Gorski states in his discussion of the Italian geologists:

Science can predict some events with incredible accuracy. If it couldn’t, it would not be possible to fly airplanes, land on the moon, send probes to Mars, or predict the decay of radioisotopes. Other things can’t be predicted as precisely because such predictions are based on stochastic models that have a lot of random noise and factors that we don’t yet understand. Some things, like earthquakes, can’t be predicted very well at all because of high variability and our lack of understanding of key mechanisms by which they occur.

Gorski in the mouse “avatars,” essay: “So in the end, what we have here is an animal model that very well might be predictive of human response in a way that is more direct and individualized.”

(For more on the prediction problem and how vivisection activists deal with it, see my recent two-part blog on prediction and my five-part blog: “More Misrepresentations, Fallacies, and Other Lies,” beginning here. Sorry about the length, but science is complicated and some thing cannot be explained in 2000 words or less.)

With this background in mind, I want to examine an article from Nature, October 11 issue, titled: “A call for transparent reporting to optimize the predictive value of preclinical research.”(1) The multiple authors are not as reticent about discussing the predictive value of animal models as vivisection activists are. The article calls into question the methodology and sloppy reporting that is common in animal-based research:

Numerous publications have called attention to the lack of transparency in reporting, yet studies in the life sciences in general, and in animals in particular, still often lack adequate reporting on the design, conduct and analysis of the experiments.

The problem is so bad that:

To develop a plan for addressing this critical issue, the US National Institute of Neurological Disorders and Stroke (NINDS) convened academic researchers and educators, reviewers, journal editors and representatives from funding agencies, disease advocacy communities and the pharmaceutical industry to discuss the causes of deficient reporting and how they can be addressed.

When I have criticized the use of animal models, I have usually avoided analyzing methodology because even with professional-level methodology standards, the model would still fail to be predictive.* Hence, I have just avoided the methodology issue. However, as one of the reasons scientists claim for their use of animal models is to control variables, I find the sloppy practices described in this article and elsewhere to be very revealing of the mindset.

The Nature article by Landis et al continues:

There was broad agreement that: (1) poor reporting, often associated with poor experimental design, is a significant issue across the life sciences; (2) a core set of research parameters exist that should be addressed when reporting the results of animal experiments; and (3) a concerted effort by all stakeholders, including funding agencies and journals, will be necessary to disseminate and implement best reporting practices throughout the research community.

The article also agrees with me that animal models are used to predict human response to drugs and disease: “In the life sciences, animals are used to elucidate normal biology, to improve understanding of disease pathogenesis, and to develop therapeutic interventions.” It then describes the myriad ways animal modelers have failed to practice good science. I will not go into the details here, as there is just too much to report in a blog. The problems include lack of randomization and lack of blinding. Those two problems alone would be enough to invalidate most studies.

Landis et al continue to agree with me by separating animal uses into predictive and heuristic categories: “However, because such experiments are likely to be subject to many of the limitations described above, they should be viewed as hypothesis-generating experiments and interpreted as such.” They continue stating:

Calling upon investigators to provide key information about the design, execution and analysis of animal experiments described in grant applications and manuscripts and encouraging reviewers to consider these issues in their evaluations should, over time, increase both the quality and predictive value of preclinical research.

They reinforce the fact that animal models are used to predict human response by stating:

We believe that improving how animal studies are reported will raise awareness of the importance of rigorous study design. Such increased awareness will accelerate both scientific progress and the development of new therapies.(1)

I encourage everyone to read the entire article, as it is very enlightening. It also refutes much of what vivisection activists claim when attempting to justify their use of taxpayer money. Apparently, I am not the only one concerned about the lack of predictive value of animal models.

*The article recommends standardization of protocols and use of systematic reviews to improve the quality of animal-based research. I currently have a paper in the peer review process explaining why this will not solve the prediction problem. I will post when it is published.


1.         S. C. Landis et al., A call for transparent reporting to optimize the predictive value of preclinical research. Nature490, 187 (2012).


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