March 26th 2021
Yesterday we highlighted one of the myths that those opposed to #AnimalResearch often spend their time propagating—that #AnimalResearch is only performed in benefit to humans—usually alongside the myth that #AnimalResearch fails to translate to humans. It is thus timely to highlight another of our posts debunking another prevalent and sensational claim—that 99% of drugs tested in animals fail in humans.
Predictability and Utility of Animal Models
Originally posted 07/25/2017
This is a guest post on the utility of animal models in drug development, misconceptions about animal models, and alternative methods of drug development, by Dale M. Cooper, DVM, MS, Diplomate, American College of Laboratory Animal Medicine. Dr. Cooper has over 20 years of veterinary experience in private practice, and as a laboratory animal veterinarian in academic and pharmaceutical research. He is committed to the welfare of research animals.
Part I Predictability of Animal Models for Effects of Drugs in Humans
Mark Twain popularized an aphorism that “there are three kinds of lies: lies, damn lies, and statistics.” While all of these strategies have been employed by animal activist groups to discredit animal based research, the misuse of statistics has the most significant impact, as the most believable lies have a kernel of truth to them. Such is the case with the intense efforts by animal activist groups to discredit the use of dogs and other animal models in biomedical research. The various statistics that are cited are that only 0.0002% of studies using animals result in an approved drug, over 90% of drugs shown to be safe or effective in animals fail to make it through human clinical trials, that animal models have a poor predictive value for the effects of drugs in humans, and that the a flip of a coin gives as good of a chance of predicting success in drug development as an animal model. Like all good lies, these statements have a kernel of truth, but are extremely misleading and demonstrate a significant lack of understanding of science and a general lack of critical thinking skills.
Experts in drug development understand the limitations of animal models, but they also understand their applications. There have been several publications that have retrospectively evaluated the value of animal models in predicting human safety across a variety of therapeutic areas and the overall percentage of human toxicities predicted by animal models is around 70% with variability between different species and body systems. Predictability for some therapeutic areas are over 90%. When different models are used in combination, the predictability increases. It is also an established fact that only about 1 in 10,000 drugs tested make it to the market and that there is over a 90% attrition rate of drugs in human clinical trials. How does this happen if animal models are predictive?
Studies that have evaluated the ability of animal models to predict clinical results in humans show very similar results, but the interpretation of the results is varied. Authors who are acknowledged animal activists claim the results show poor correlation between results in animals and outcomes in humans (e.g ‘no better than a flip of a coin’). However, most scientists (and the FDA and NIH) assert that animal models predict outcomes in humans with good reliability. What is the disconnect? This is where statistics come in. The different papers argue over the use of a calculation for predictive value versus likelihood ratio. The results come out slightly different. Predictive value calculations show better results for animal models than do likelihood ratio calculations, so animal activists tend to cite the likelihood ratios while overlooking the predictive ratios (see table below). I am not a statistician and therefore won’t weigh in on this point and will use the term ‘predictive value’ to refer to both terms.
What I feel is a far more relevant discussion is how we interpret positive versus negative predictive values. In general, the positive predictive values of animal models are higher than the negative predictive values. What this means is that the presence of an effect in an animal model is a good indicator that the same effect will be seen in humans (positive predictive value). However, if an effect is not seen in the animal that does not mean there won’t be an effect in humans (negative predictive value). Activists have focused on the negative predictive value, taking the position that because animal models don’t predict all effects in humans, they are not reliable and therefore, the use of animals in research is not scientifically justified. Is this a valid conclusion? Let’s apply it to another risk assessment situation and see if this makes sense. Say I want to cross a road but don’t want to get hit by a car. My Mom taught me to look both ways and if I see a car coming I don’t cross the road. There is a positive predictive value to look before I cross. However, if I don’t see a car, that doesn’t always mean one isn’t coming. Depending on its speed or visibility there is still some risk when I cross a road. The negative predictive value of looking both ways isn’t as high as the positive predictive value. So do I bother to look both ways knowing it’s not 100% reliable? Of course I do. But I also do other things. I listen, I assess for visibility, I may look for a crosswalk or an overpass. Just like in drug development I understand the predictive value of my risk assessment and run more than one assessment.
Unlike animal activists, biomedical scientists don’t have an agenda to limit the scope of research. We use the experimental systems that allow us to address the questions at hand to develop treatments that improve the lives of both humans and animals. The models we are using are the ones that are the most successful. Animals are one type of model employed in biomedical research, but are by no means the only models. Animal models are expensive and time consuming, and scientists recognize the emotional and ethical issues associated with animal research. We are human and many of us have our own pets. We bond with the animals we work with. There is no incentive for us to employ an animal model that may negatively impact animal well-being if another model that does not negatively impact well-being works just as well. The FDA requires animal data prior to clinical trials in humans, because they are also scientists and have come to the same conclusion — animal models provide essential data in predicting safety and efficacy of new therapies.
Part II Drug Development Without Animals
As discussed in a previous post, animal models are an important component of the development process for drugs and other medical treatments. But they are not the only method of research that is used. Drug development is an iterative process. Each study builds on data from other studies. The process involves computer modeling, benchtop chemistry, a wide range of in vitro models to evaluate absorption, metabolism, distribution, receptor binding, gene expression, and even some aspects of toxicity. We use non-animal methods so much that over 90% of drug candidates are eliminated from consideration using in vitro assays before they even reach the phase of pre-clinical animal studies.
If animal activists groups or well-meaning scientists want to see more non-animal research methods developed and put into use, there is a process for this. The Interagency Coordinating Committee on the Validation of Alternative Methods (ICCVAM) under the National Toxicology Program evaluates data to validate non-animal models for drug development in the US. There is a list of approved methods on their website. All of these methods were funded by the same research institutions that use animal models. If activist groups wanted to make a significant impact on animal use in research, they might consider funding alternative research. It is usually more effective to work on a problem rather than just talk about it. The fact that we are still using animals isn’t because of a lack of trying, it is the limitation in our scientific knowledge. To build a model, you have to know a lot about the system you are modeling. In fact, it is possible there will never be a complete replacement of animal models in research. By the time we know everything to create the perfect model, we will have answered all of the research questions that can be asked.
The final stage of drug development involves clinical testing in human patients. In vivo studies in animal models eliminate 90% of drug candidates from the development process before beginning clinical trials in humans, demonstrating their utility in de-risking the testing process in humans.. Over 1 million patients to enroll in clinical trials each year, yet there are few reports of serious adverse events relative to the number of patients in these trials. When drugs fail during the clinical trial phase, the reasons are more often related to economics or strategy than they are to safety. The testing in animals served an important purpose.
If society chooses to take more risk in the patient population, it has the power to do so. However, based on the data regarding predictive value of non animal models, this would mean that 70% of the time someone in a clinical trial would be likely to experience toxicity from a drug about which little is known because the nature of it was not first characterized in animal models. This means the physicians would not know how to treat it or the prognosis. It is already a challenge to enroll the number of patients needed for clinical trials even when providing them a significant amount of information so they can make an informed decision to consent to enroll. Having even less information would not likely help with this.
It is also not clear that humans are a better model for testing drugs than are animal models. It is extremely difficult to control variability in a human test population, due to diet, lifestyle, and genetics, which reduces the statistical power of a given study population compared to a well-controlled animal study. Clinical trials in humans enroll thousands of patients, whereas animal studies use fewer than 100 animals in many studies to achieve similar statistical power. Humans also have a long lifespan and studying the chronic effects of a drug is difficult in a clinical trial. In contrast, in 2 years, a rodent undergoes all life stages, allowing assessment of the effects of chronic drug administration. Finally, it would be very unlikely that humans would consent to participate in studies evaluating fetal toxicity, and even if they did, the long duration of human pregnancy and low reproductive rate (1 offspring every 9 months) reduces the power of detection relative to a rodent model that produces 10 offspring in 3 weeks.
It is true that all of these issues will be considerations in patients after a drug is in general use. There is some inherent level of risk in medicine. However, the development and approval process using both animal and non-animal studies is the best that science can currently offer.
Part III The Big Picture of Animal Use
We can argue over the scientific merits of the use of laboratory vs animal vs human testing in drug development, and we can pontificate about the ethics of the decisions we make, but ultimately, we humans have choices to make. Are we content with our level of health and well-being? What sacrifices are we willing to make to consider the needs of animals? The impacts we have on animals go far beyond what level of medical care we choose. Animals serve as food sources, they work for and with us, and they provide for aesthetics and companionship. How much of that will we give up to reduce our impacts on them? If we go that far, we are still competing with them for food and shelter. Is it possible to not impact animals? I contend that the ethics of our society show a considerable level of care for animals. The fact that we worry at all about their welfare is something that to the best of my knowledge, no other species on the planet would do given the same choices we have.
Working with animals in research is not a one-way street. Animals benefit from veterinary treatments developed through the same research process as for human treatments, and the animals we work with in the research environment benefit from the high level of care and attention to their well-being that is provided to them. People care about them and for them. They experience medicine as part of their lives as do we all. If they were living outside of the research environment they would still experience medical issues as a normal part of life, but particularly in the case of non-companion species, would not necessarily have anyone to care for them.
I believe that the arguments proffered to discredit work with animals in research are largely based on biased and misleading interpretation of data. Where there are valid data to use alternatives, these alternatives are already being used. It is appropriate scientifically and ethically to continue to develop and validate new approaches for predicting drug safety and efficacy in the patient population, both animal and non-animal. Animals are used humanely and also receive benefits from biomedical research. Ultimately, there is a balance being struck between the needs of humans and of animals. There is room for constructive dialog on where this balance should be, but I personally do not believe that this should occur using the regulatory and legal systems as a venue. Science is too intricate and complex to be able to effectively address in this way. There is a process in place at all research institutions (the IACUC) to ensure ethical and scientific review occurs on each experiment. Those seeking to drive alternatives would do better to develop the science to validate these alternatives rather than manipulate public emotion and ultimately public policy or law.
~Dale M. Cooper, DVM, MS, Diplomate, American College of Laboratory Animal Medicine.