New Drugs and Animal Testing
An editorial in Nature in 2009, stated: “Animal-research policies need to be guided by a moral compass—a concensus of what people find acceptable and unacceptable” (1). Giles, also writing in Nature in 2006, stated:
In the contentious world of animal research, one question surfaces time and again: how useful are animal experiments as a way to prepare for trials of medical treatments in humans? The issue is crucial, as public opinion is behind animal research only if it helps develop better drugs. Consequently, scientists defending animal experiments insist they are essential for safe clinical trials, whereas animal-rights activists vehemently maintain that they are useless. (2)
So, does testing new drugs on animals result in safer and better drug? According to Kelly Rae Chi, writing in The Scientist, September 1, 2012, it does: “The most straightforward way to find out whether a drug or environmental chemical might harm an unborn baby is to test its effect on a pregnant lab animal.” (3) (For the reality of teratogenicity testing on animals, see The History and Implications of Testing Thalidomide on Animals.) Dr. Keith Cheng of Penn State's College of Medicine agrees, stating: “Animal tests are necessary for some research, such as testing drugs for toxicity. It would be, in my opinion, improper to release drugs for human use without animal testing.” (4) Former UK science minister Lord Drayson said that without animal-based research “it is not possible to develop new medicines.” He went on to state that animal-based research was “necessary and that people would ‘suffer and die’ without it.” Examples of similar sentiments could easily be multiplied.
But data supporting such statements is scarce to nonexistent while data to the contrary is ubiquitous.
For example, van Meer et al, writing in Regulatory Toxicology and Pharmacology, 2012, stated:
The value of animal studies to assess drug safety is unclear because many such studies are biased and have methodological shortcomings. (5)
I have pointed this many times, including our critique of the Olson study (6) in Animal Models in Light of Evolution. Van Meer et al also commented on the Olson study, stating:
Olson et al. defined a true positive non-clinical event as one in which ‘. . .the same target organ was involved in humans and in animals in the judgment of the company clinicians and the toxicologists’ (Olson et al., 2000). While identifying toxicity at the target organ level in animals may be useful for evaluating the safety of a drug from a development perspective, it is inadequate when attempting to establish the predictive value, because toxicity in the target organ may give rise to several specific side effects in humans.
Van Meer et al retrospectively studied whether serious adverse drug reactions (SARs) in humans could have been identified using animal models prior to the drug being released. They evaluated drugs currently on the market and discovered that only 19% of 93 SARs were seen in animals. Van Meer et al state: “Accordingly, the sensitivity of the animal studies for detecting SARs in humans was 19%.” Again referring to the Olson study, they state:
Because we think that a stricter definition of true positive results is needed, we distinguished between target organ involvement and non-clinical events that were either identical to the SAR or causal to it. For this reason, non-clinical events which were related to the target organ but which did not give rise a SAR by similar mechanisms were not considered true positive.
One could argue that non-clinical studies are not designed to identify rare adverse reactions that appear after market approval. Although the number of animals used in non-clinical studies is relatively small, the studies are designed to find important side effects that are likely to occur in humans. (5) (Emphasis added.)
For support of this statement, they cite: International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use, 2009. Guidance on Non-Clinical Safety Studies for the Conduct of Human Clinical Trials and Marketing Authorization for Pharmaceuticals M3(R2), EMA, London.
It should also be noted that sensitivity does not equal positive predictive value (PPV). Therefore, a sensitivity of 19%, while inadequate in and of itself, would result in a PPV that is even less helpful.
This is why Pharma has statistics like the following:
- 5% of cancer drugs that have IND go to market. (7)
- Young 2008: “The success rate of this heuristic approach [to drug development] is very low. For example, the average probability that a candidate emerging from lead optimisation will not make it to be a drug is above 99.8% (8). . . .” (9)
- The FDA: “a new medicinal compound entering Phase 1 testing, often representing the culmination of upwards of a decade of preclinical screening and evaluation, is estimated to have only an 8 percent chance of reaching the market. (10)
- 80% of drugs for which an IND has been filed, fail in development and approximately 50% fail in Phase III. (11)
- Kola and Landis wrote: “Analyses success rates from first-in-man to registration during a ten-year period (1991–2000) for ten big pharma companies in the United States and Europe. The data indicate that the average success rate for all therapeutic areas is approximately 11%; or, put another way, in aggregate only one in nine compounds makes it through development and gets approved by the European and/or the US regulatory authorities.” (12)
- Kola and Landis: “Even the rate of failures in Phase III trials — by which stage significant amounts of the costs of discovering and developing a drug would have been incurred— is far too high: approximately 45% of all compounds that enter this phase of full development undergo attrition.” (12)
This is, in part, why medications are so expensive. There are many misses before even one hit and Pharma has to pay for the development of all of them.
Vivisection activists will point out that there is a difference between drug testing and drug research using animals. Animals are frequently used in so-called basic research in an attempt to find druggable targets and this differs from testing drugs on animals in order to evaluate safety, efficacy, and so forth. But using animals in an effort to find druggable targets has not been very successful either.
An editorial in Nature titled “Must try harder,” addressed a major problem in the basic research community: the results are not replicable nor are they translating to human treatments. (13) The editorial was accompanied, in the same issue, by two articles on the same topic. According to Ledford, author of the first article: “Between 2008 and 2009, only 18% of drugs in phase II clinical trials succeeded. (14) And, as described in a Comment in this issue (see page 531), when the biotechnology company Amgen, based in Thousand Oaks, California, tried to reproduce data from 53 published preclinical studies of potential anticancer drugs, it failed in all but six cases.” (15) (For more see Is the use of sentient animals in basic research justifiable?)
A recent example of the failure of animal models to predict human response is the drug dexpramipexole. Dexpramipexole was supposed to slow the progression of ALS, also known as Lou Gehrig’s disease, based on animal studies. (16) It failed in human clinical trials.
Yet, animals continue to be used in research and testing despite a history of failure and despite a scientific theory that explains why they fail. (For more on evolved complex systems theory see Animal models and conserved processes, Systematic Reviews Of Animal Models: Methodology Versus Epistemology and Complex systems, evolution, and animal models, which is available here.) For example, a January 15, 2013 press release from the University of Missouri-Columbia describes: “A quantum leap in gene therapy of Duchenne muscular dystrophy,” which is based on gene transfer experiments on dogs. (FYI, beware of anything with the word quantum in it when the author is not a physicist discussing physics.)
Once again, all of the above must be placed in the context of the fact that human response to drugs and disease also varies. For example, a recent study (17) revealed that: “African American women coinfected with human immunodeficiency virus (HIV) and hepatitis C virus (HCV) are less likely to die from liver disease than Caucasian or Hispanic women.”
As the Nature editorial stated: “Animal-research policies need to be guided by a moral compass—a concensus of what people find acceptable and unacceptable." (1) Note that the editors did not say the consensus of what those with a vested interest find acceptable. But even if the entire scientific community were to state that animal testing was essential, if the basis for a consensus opinion is shown false, then you can no longer rely on or quote the consensus opinion in terms of supporting the position. Such would be unethical and immoral. The scientific consensus, though usually both valuable and reliable, has been shown incorrect more than once.
1. Editorial, A slippery slope. Nature 462, 699 (2009).
2. J. Giles, Animal experiments under fire for poor design. Nature 444, 981 (Dec 21, 2006).
3. K. R. Chi, Stemming the Toxic Tide. The Scientist 26, 55 (2012).
4. E. Gibson. (The Patriot-News, 2012), vol. 2012.
5. P. J. K. van Meer, M. Kooijman, C. C. Gispen-de Wied, E. H. M. Moors, H. Schellekens, The ability of animal studies to detect serious post marketing adverse events is limited. Regulatory Toxicology and Pharmacology 64, 345 (2012).
6. H. Olson et al., Concordance of the toxicity of pharmaceuticals in humans and in animals. Regul Toxicol Pharmacol 32, 56 (Aug, 2000).
7. S. Kummar et al., Compressing drug development timelines in oncology using phase '0' trials. Nature reviews. Cancer 7, 131 (Feb, 2007).
8. European Commission, “Innovative Medicines Initiative: better tools for better medicines” (Luxembourg, 2008).
9. M. Young, Prediction v Attrition Drug Discovery World, 9 (2008).
10. FDA. (2004).
11. L. J. Lesko, J. Woodcock, Translation of pharmacogenomics and pharmacogenetics: a regulatory perspective. Nat Rev Drug Discov 3, 763 (Sep, 2004).
12. I. Kola, J. Landis, Can the pharmaceutical industry reduce attrition rates? Nat Rev Drug Discov 3, 711 (Aug, 2004).
13. Editorial, Must try harder. Nature 483, 509 (2012).
14. J. Arrowsmith, Trial watch: Phase II failures: 2008-2010. Nat Rev Drug Discov 10, 328 (2011).
15. H. Ledford, Drug candidates derailed in case of mistaken identity. Nature 483, 519 (2012).
16. P. Corcia, P. H. Gordon, Amyotrophic lateral sclerosis and the clinical potential of dexpramipexole. Ther Clin Risk Manag 8, 359 (2012).
17. M. Sarkar et al., Lower liver-related death in African-American women with human immunodeficiency virus/hepatitis C virus coinfection, compared to Caucasian and Hispanic women. Hepatology 56, 1699 (Nov, 2012).