The road to getting a new pharmaceutical drug on the market is long and brutal.

It begins with a novel compound that must first be tested in cells and then animals. This "pre-clinical" phase of drug development, which can last for several years, allows researchers to understand how potential therapies might work on different diseases and whether the drugs are likely to be safe or toxic in people.

But for every 5,000 compounds assessed at this stage, only about five are promising enough to even try in humans. And after the clinical trials in humans, only one will actually reach pharmacy shelves.

This overwhelming rate of failure here is often attributed to the fact that mice and cells are poor substitutes for people.

But it increasingly looks like that gap may be caused by something else entirely: the quality of animal and cell studies.

"There is this idea that drugs seem to work in animals, and then when you test the same drugs in humans, they fail," said Emily Sena, a researcher at the University of Edinburgh who has been dissecting the world of animal studies. Instead, some drugs may fail, Sena argues, because some animal studies are just so poorly designed.

Sena became attuned to the bad animal science problem about a decade ago, when she and her colleagues began to investigate why NXY-059, a highly touted drug for stroke patients, failed in human studies after extremely promising results in animals.

They quickly realized the animal research on the drug was flawed because the researchers had not taken basic measures to reduce the risk of bias.

NXY-059 turned out to be just one case study in a sea of examples. Many basic studies, Sena and other researchers discovered, are too small, riddled with flaws, or so contaminated as to be useless for testing whether drugs work.

This epidemic of bad basic science means breakthroughs are lost in translation, and potentially lifesaving therapies, unnecessarily delayed on their way to helping people who need them. It also means animal lives are being wasted on sloppy studies that can't really tell us anything about the world.

Animals studies are often so small they’re irrelevant

With any new drug, there are myriad questions about how the human body will absorb it and respond to it. But testing new drugs in people is risky and expensive. So researchers heavily rely on animals like mice that are biologically very similar to humans (we share 95 percent of the same genes, and get many of the same diseases) to answer some of the most basic questions about a potential new medicine.

Over the years, animal rights activists and ethicists have pointed out that tests on animals can be unnecessarily cruel, painful, and wasteful of animal lives.

This awareness has led to mandates like the UK’s 3Rs principles: Any animal experiment application that gets ethical approval should demonstrate that it has considered how to reduce the number of animals used in research, replace the use of animals with other models, and prevent unnecessary suffering by refining the ways scientists care for animals. In the US, the Animal Welfare Act of 1966 led to similar protections.



Researchers like Sena argue that there’s been an unintended consequence of the push to reduce the number of animals used in studies: Too many animal studies are now so small as to be meaningless.

Researchers analyzed more than 2,600 studies that used animal models, and found that only 1 percent reported a sample size calculation

Sena leads the Collaborative Approach to Meta-Analysis and Review of Animal Data in Experimental Studies (or CAMARADES), an international group that’s dedicated to systematically analyzing animal data across a range of different conditions. (They’re basically the Cochrane Collaboration of animal research on diseases.) In one study, Sena and her collaborators found that fewer than half of the animal experiments they looked at included a large enough sample size (i.e., enough animals) to be statistically meaningful.

In another, they analyzed more than 2,600 UK studies that used animal models and found that only 1 percent bothered to report a sample size calculation. In an ideal world, researchers should publish how they determined the minimum number of animals required to make sure they could answer the question they set out to answer. But in animal studies, that step overwhelmingly doesn’t happen.

Sena thinks this is because researchers have misinterpreted the push to reduce the number of animals in studies. "Use the fewest number of animals to answer your research question has turned into using the fewest animals," she said. And this means, too often, animal studies are so small as to be irrelevant.

"I don’t think it’s ethical to do an experiment with five animals in each group when that’s [underpowered]," she says. That’s a nuanced message that hasn’t been easy to get across, she added. "I have a few folks who misinterpret my stance. They think it’s, ‘Don’t do animal studies.’ I’m not saying that at all. I’m saying do them properly, and you probably need to do bigger ones."

Small studies also undercut the validity of the findings and the goal of using fewer animals in the long run.

"Smaller studies also give larger effect sizes," said University of Edinburgh’s Malcolm Macleod, a pioneer in this field who helped establish CAMARADES. "They create red herrings that other people have to come along and fix later. And it always takes longer to fix something … so you end up using more animals."

In one study, Macleod and his colleagues looked at the use of p-values, those tests of statistical significance that are now commonly perceived as a signal of a study's worth, in animal studies of neurological disorders. They wanted to test whether there were too many studies with "positive," or statistically significant, results. Of the 4,445 studies they looked at, 1,719 boasted a "positive" result — nearly double what they calculated would be statistically possible.

Animal studies aren’t just too small — they’re also rife with biases

"Publication bias" is a big problem in the world of research: Not all studies that are conducted actually get published in journals, and the ones that do tend to have positive and dramatic conclusions, leaving a skewed impression of the research base.

Estimates suggest the findings from half of all clinical trials that are conducted in humans are never published. It turns out the problem in basic research is not much better.

In an analysis of systematic reviews of animal stroke studies, the CAMARADES team estimated 20 percent of animal studies were unpublished, which leads to an overestimate of the effects of treatments. And the problem likely extends beyond just stroke research. "It is probable that publication bias has an important impact in other animal disease models, and more broadly in the life sciences," the researchers wrote.

So not only are researchers failing to publish all their work on clinical trials in humans but the publication track record of pre-human findings looks similarly lackluster.

The CAMARADES group also found that researchers conducting animal studies often don’t take the simple steps to reduce bias: randomizing which animals get the placebo and which get the control, and being transparent about potential conflicts of interest.

Looking at a sample of 2,600 animal studies of drugs, the CAMARADES team found only 622 (or 23 percent) used randomization. Meanwhile, 308 (or 11.5 percent) included a statement on potential conflicts of interest.

For high quality studies, Sena said, "You want animals to be randomized, and you want conflicts of interest to be declared — all that [should be] upfront so you can interpret that." But again, it’s more the exception than the rule in the world of animal research.

Up to 36 percent of cell lines are misidentified or contaminated

Along with animal research, early testing in cells is another common pre-clinical step in drug development. Researchers use cell lines, which have been grown in controlled conditions, to better understand how diseases work. They can use them to see how, for example, malignant or healthy tissues might respond to potential cancer drugs or vaccines.

At first glance, this may seem like a purer endeavor compared with messy human experimentation. But meta-researchers who study cell research say that can’t be further from the truth. Over the years, they’ve found that a lot of basic research on cells isn’t reproducible because it’s also plagued by flaws and biases.

In a new study published Tuesday in the journal Scientific Reports, researchers found that breast cancer tumor cells from the same cell bank responded differently to the same chemical treatments. The cells were supposed to be clones — they had been vetted for quality before the experiment, and they came from one of the world’s best cell banks. They should have had the exact same responses to the chemicals.

Yet "there were dramatic [genetic] differences from one vial of these cells to another," said study leader Thomas Hartung, a professor in environmental health sciences and molecular microbiology and immunology at Johns Hopkins. He and his co-authors decided to investigate why, and discovered that the cells had undergone genetic drift.

"They could be doing really good science but with a fundamentally flawed system, which means whatever they find is wrong"

Since the cell line in question is very common — there have been about 23,000 articles written about MCF-7 cells — Hartung said he’s concerned about what his findings mean for other research involving them.

Troubles with cell quality aren’t exclusive to genetic variation, said Andy Bradford, a University of Colorado researcher. Researchers are supposed to validate that they’re working on the correct cell model, and whether their cells have been contaminated, before starting a study. In other words, they should make sure the breast cancer cells they think they’re working on are indeed breast cancer cells and that those breast cancer cells haven’t been mixed up with lymphoma cells, for example. But all too often, Bradford said, that doesn't happen.

And that’s a big problem, because researchers have found that up to 36 percent of cells lines are misidentified or contaminated. In one instance, Bradford explained, a researcher thought she was working on a thyroid cell line, testing a potential therapeutic, when in fact she had been working on melanoma cells.

"That misidentified cell line led investigators to pursue a misdirection," Bradford said. "They could be doing really good science but with a fundamentally flawed system, which means whatever they find is wrong."

To guard against the problem, some journals (including Nature) and funders (like the National Institutes of Health) are requiring researchers to confirm they’ve validated their cells to make sure they’re the correct type before starting an experiment. But as Ivan Oransky and Adam Marcus pointed out at Stat News, progress has been slow. Researchers have known about the problem for more than 50 years, and yet the vast majority of journals still require no such validation step.

The problems that plague animal and cell research affect the rest of science

We know that perverse incentives are behind a lot of bad research. That’s what we found when we asked 270 scientists about all the ways research can go wrong. In order to keep their jobs and continue doing science, researchers told us they are pressured to publish and attract lots of funding, and that pressure too often leads to exaggerated findings and sloppy studies.

Macleod said that’s just as true in the world of animal research. "Academic institutions have become factories," he said. "They now have a business model that requires people to get grants."

That pressure can lead to corner cutting in basic research — which sets researchers on wrong and misleading paths long before the messy and expensive science of testing in humans.

Still, bad science surely is not the only reason so many drug trials in humans fail. Sena, Macleod, and other researchers have produced good evidence that animals just aren’t great models for some human diseases.

But reducing the amount of bad animal science out there will help the situation. For their part, the CAMARADES team helped set up Multi-PART, a European funding project to enable multiple institutions to collaborate around higher-quality animal studies. Some of their objectives include increasing randomization and blinding in basic research.

Macleod also advocates for funders to withhold a portion of research grant funding until researchers have published their work. With more formal acknowledgements of these problems, we may start to see some change.