What seems obvious to me is that the animal model paradigm is broken when it comes to complex neurologic diseases. This is arguably one reason why many preclinical studies in rodent models have failed to translate to humans. A recent paper in the journal Neuron illustrates this point. These mice were then cross-bred with 28 different mouse strains. The genetic makeup and background of the offspring varied considerably, although all had the 5XFAD genes.
As it turned out, the gene set had vastly different effects on behavior in different mouse strains. Most of the 5XFAD mice showed impaired memory with aging and, taken as a group, there was an average acceleration of impairment compared to their parent strains.
Mouse Behavioral Testing: How to Use Mice in Behavioral Neuroscience
Yet the effect size varied considerably. In some strains, 5XFAD had a strong effect, in others it had little or no effect. In a few, the gene set was remarkably associated with improved memory relative to the parent strain!
Clearly, the effects of an experimental compound would likely vary a great deal depending on which strain of mice was used for preclinical testing. If mice genetics are complicated, human genetics is infinitely more so. Furthermore, it is impossible to model in mice all of the complex environmental inputs — everything from nutrition to education to exercise levels — that affect cognition, function, and behavior in people with neurologic disorders.
Other variables such as transgenic drift, technician variability, and confirmation bias also play roles in the lack of translational power with behavioral phenotypes from transgenic animal models. They are clearly helpful for basic research and to study drug effects at the molecular, structural, and functional levels. To begin, it helps to have this discussion frankly — and to have it with investors, board members, and executive teams. We must all be hesitant to overweight behavioral phenotypes when making key decisions in late-preclinical neuroscience drug discovery.
We also must continue to advance novel preclinical approaches to evaluate the effect of a therapy before deciding whether it merits a clinical trial. Affirmative data from these tools do not, of course, constitute proof that a drug will do the same thing in the human brain that was observed in the rodent brain. But they do suggest that the therapy has quantitative molecular and structural effects on neurons, brain circuitry, and the like — effects on systems that we have solid reasons to believe more closely mirror the human brain than rodent behavior mirrors human behavior.
Still, many in the field are unwilling to abandon requiring rodent behavioral activity as a must-have before moving a compound into the clinic. And none of this touches on the ethical considerations of using animals for research purposes, which should always be conducted in the most humane and thoughtful ways. Adam Rosenberg is the president and chief executive officer of Rodin Therapeutics , a company based in Cambridge, Mass.source site
The trouble with mice as behavioral models for Alzheimer's - STAT
Amen brother. I have been thinking this for a while now. By using a library of known failures we can thereby empirically test the impact of suggested solutions such as enrichment, controlled heterogenization, biomarker-based models, or reverse-translated measures. Biomedical research at its core is ethically, societally, and scientifically justified by its ability to deliver real-world benefits to human health Rollin While industry in general, and some academics in particular, have openly discussed the shockingly poor translation of basic animal work into human outcomes for some time e.
However, as will be discussed, not all results are created equal ly meaningful , and the creation of more or less meaningful results i. As a result, biomedical research is close to a tipping point with potentially dire consequences for the future, scope, and funding of basic animal research. This should come as no surprise: the NIMH's strategic plan National Institute of Mental Health mentions animal work a paltry two times in 38 pages; instead emphasizing the use of imaging, genomic, and other next-generation approaches to answer questions traditionally pursued in animals. Yet academic institutions continue to invest in increasingly elaborate and expensive infrastructure for animal studies e.
These infrastructure investments are justified in terms of both need, and economic viability, by projections that an institution's research animal population census will grow, fuelled by increased funding support. While this may be reasonable in top-tier academic institutions, a systemic shortfall in funding for animal research would be catastrophic for most research universities.
Pharma provides a cautionary tale: Kola and Landis pointed out in that Pharma's investment model was unrealistically unsustainable over the coming 5 to 10 years Kola and Landis , and, sure enough, Pharma has been forced to disinvest in animal research Hunter Indeed a key strategy has been to shift the expense and risk of basic discovery into academia Hunter Now that essentially the same forces come to bear on academic research, what can be done to prevent a similar contraction in the academic sector? In theory, the answer is simple—we need to do a better job of producing animal results that translate to human outcomes.
Similarly, the changes required are relatively simple, and this article outlines some of the systemic issues and potential solutions available to animal researchers. The real challenge, however, is changing the culture of biomedical research so that even small simple changes are adopted.
The potential rewards are worth the effort. At the end of the day, the failure of animal results to translate is arguably the greatest laboratory animal welfare issue of our day and a source of many societal ills. Furthermore, real advances in personalized and biomarker-based research the supposed panacea to the problems in animal research will in truth be very hard to attain without animal models of disease development.
It is hard to think of a better example where good-welfare-is-good-science, or good-welfare-is-good-business. If this problem can be solved, then the rewards for animal welfare, biomedical research, patient populations, return-on-the-funding-dollar, and society in general will be immeasurable. Thus, this article is not intended primarily for researchers.
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The research community by and large has been unable or unwilling to heed the calls for changes in culture and practice in the literature e. In particular, peer review can be a stifling force of inertia—innovative methods are less likely to be funded than established but weaker methods. Meanwhile, reviews or methods papers that challenge the status quo or point out that the Emperor has no clothes can be almost impossible to publish. In both cases, the risk and costs for young scientists are particular high, just at the time when they are most open to new ideas and at their most creative.
Similarly, differential funding opportunities and success rates for grants proposing new work versus renewal of an existing program are a powerful disincentive to established researchers to adopt new methods or challenge the status quo ironically at the time when they can be most influential. Researchers need to be given both the safe space in their careers to adopt new approaches, and the incentives to do so Pusztai et al.
For instance, multiple reviews of the systemic issues with knockout mice did nothing to change the culture Crusio ; Wolfer et al. Thus, this review is targeted at other stakeholders with a vested interest in increasing the translational value of animal research from patients, to funding bodies, to animal advocates, to university administrators, to Institutional Animal Care and Use Committee [IACUC] members, to journal editors, and beyond in the hope of creating similar opportunities for a change in culture and practice. Traditionally, attrition has been viewed as an issue with clinical trials, simply because this is when it is most visible and most costly.
The most detailed economic data are provided by Paul and colleagues and provide an instructive window on the problem. These numbers underscore the huge societal impact of clinical attrition in particular—these costs can be diluted in a large patient population that will need the drug for a long time.
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Drugs for rare diseases, or for diseases with which patients are unlikely to seek help, and drugs that cure rather than manage diseases will be more expensive to the patient, and potentially too expensive to be worth development. However, digging deeper into these data sets reveals that attrition is fundamentally an animal issue, not a human one. To understand why, we need to consider two sides of a coin: What are the identifiable reasons for failure in human trials? And what is the structure of decision making in the drug discovery pipeline itself?
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The drug discovery pipeline is traditionally divided into preclinical and clinical phases which correspond to animal and human phases , but it can also be subdivided by the type of questions being asked. Of course, efficacy is not an all-or-nothing phenomenon and drugs fail in these stages for other reasons. For example, bioavailability of the drug at the target may be very different in humans, limiting efficacy or narrowing the therapeutic window to the point where side effects become unmanageable; or drug—drug interactions may interfere with the study or preclude widespread use in a human population.
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Thus, the real issue is whether a new drug is efficacious enough given its cost of manufacture, the patient population, and the cost and efficacy of competing products. Nevertheless, taking very different approaches, Kola and Landis and Hay and colleagues identify lack of efficacy as the single largest reason for why a drug fails in human trials.
The other side of the coin is to think of the pipeline in terms of decision making. Thus the pipeline makes early go decisions on the basis of animal results, then turns its attention to making no-go decisions on the basis of safety, before finally assessing the predictive validity of an animal result i.
From a statistical point of view, the initial stages of the pipeline emphasize sensitivity making sure all hits are identified, at the cost of false positives , before emphasizing specificity making sure that false positives are weeded out. From this perspective, attrition has a deceptively simple cure—moving the no-go decision making as early as possible in the pipeline.
While this point has been made with respect to economics Paul et al. The scale and invasiveness of animal use in the pipeline peaks in preclinical toxicology. Thus every failure for lack of efficacy is a prima facie welfare issue through the needless use of animals in preclinical toxicology.
If a highly specific no-go decision on the basis of efficacy could be inserted prior to this stage, then good-welfare-is-good-business: invasive animal use is massively reduced, as is attrition at the most costly stages of the pipeline.
A Venn diagram representation of the effects of specificity and sensitivity on validity and false discovery. The figure illustrates an imaginary space of all the deficits we might want to detect.