Images of monkeys undergoing experiments in a German laboratory stirred a wave of public outrage recently, prompting questions whether such barbaric procedures are necessary in the 21st century. Technology exists today that could replace animal testing in the future, but how far is it from practical use?
In 2018, a team of Oxford University researchers announced that their computer models of human heart cells were able to predict side effects of various medications on the heart more accurately than animal studies.
While studies done on animals assessed the risk of arrythmias in human users with the accuracy of 75-85 per cent, the computer model of actual human heart cells made a correct prediction in 89-96 per cent of cases. That means that drugs could pass the animal tests but still later cause dangerous heart problems in patients, while this risk is lower when using computer models.
We took 62 drugs such as painkillers, antihistamines or antibiotics, many of which are on the market, and we looked for biomarkers indicating the risk of arrhythmias in our simulations, says Elisa Passini, a senior researcher in the Computational Cardiovascular Science team at the University of Oxford and the lead author of the paper published in the journal Frontiers in Physiology. Then we compared our results with what is known about these drugs. For example, there are reports of patients who have had a cardiac episode while taking these drugs. We compared our results with these reports and thats how we calculated the accuracy.
Passini says the difference in favour of the human heart cells computer model might arise because animal cells and organs, while having been widely used in drug development for decades, are in many ways similar to but by no means identical to human organs and cells.
Sometimes you dont see an effect in animals and then, if you give the drug to a human being, you will see an adverse effect on the heart, she adds.
In fact, according to a 2009 paper by Yale University epidemiologist Michael B Bracken, which was published in the Journal of the Royal Society of Medicine, there have been many cases in the past when drugs deemed safe in animal studies in fact caused serious harm once introduced to humans.
For example, thalidomide, a drug sold in the late 1950s and early 1960s as a sedative and treatment for morning sickness for pregnant women caused the foetuses to develop serious defects. Such side effects were not observed in animal studies.
A 2006 UK-based phase I clinical study of am immunomodulatory drug called TGN1412 (theralizumab), designed to alleviate symptoms of autoimmune diseases, caused life-threatening side-effects to all of the six previously healthy human volunteers enrolled in the study who were given the drug. Although they received doses 500 times lower than what had been found safe in animal studies, the human subjects quickly developed multi-organ failures and required lengthy hospitalisation. The drug had previously successfully passed tests not only in mice but also in rhesus monkeys, which up until then had been considered very similar to humans in their physiology.
Hazel Screen, a professor of biomedical engineering at Queen Mary University of London (QMUL), says that despite decades of use and refinement, the success rate in drug development based on the current animal models is extremely low.
Today, if something goes into clinical trials because it worked in animal models, the likelihood of it coming off is terrible, says Screen, who co-leads a project developing organ-on-a-chip technology another alternative that could replace animal tests in the future.
It currently takes approximately 14 years to develop a drug and only about 5 per cent of drugs actually end up being used to treat patients, she says.
Screen agrees with Passinis statement that one of the reasons for such a poor outcome is the fact that the cells, bodies and physiological processes of animals, while in many ways similar, simply do not perfectly match those of humans.
Screens colleague Professor Martin Knight says big pharma companies, hoping to improve this abysmal success rate, are looking for alternative technologies to at least partially replace animal tests.
Big pharma companies are primarily interested in increasing profits by getting better benefits for patients, rather than reducing animal testing per se, Knight says. They want to be able to predict more accurately whether these drugs are going to work and make sure that they progress more efficiently through the development pipeline.
According to the UK Home Office, 3.52 million scientific procedures were carried out in 2018 in the UK involving living animals, with mice, rats and fish making up 93 per cent of the total number.
The amount, the Home Office said, decreased by 7 per cent compared to 2017. Of the total amount, 1.80 million procedures were for experimental purposes, focusing on basic research, the development of new treatments, safety testing of pharmaceuticals, surgical training and education. The rest focused on the creation and breeding of genetically altered animals.
The cost of these experiments is substantial, especially since regulators, pressured by the 21st-century animal-rights-conscious public, require the scientists to improve conditions and minimise pain and suffering of the creatures used.
Many pharma companies are interested in the in-silico simulations of the Oxford University team, according to Passini. The team, which is part of the EU-funded Compbiomed initiative, has developed a software called Virtual Assay, which can run on a regular laptop and complete a simulation of 100 human heart cells interacting with a certain drug in about five minutes.
Our models are built on data from human patients, says Passini. Its usually patients that have gone through some surgery during which the doctors removed some cells, which were further studied. We also use data from healthy hearts that were not suitable for transplantations. The models are based on a large number of equations that represent what we know about the cardiac cells, their behaviour, their membranes, and the transport of ions in and out of cells.
These models, Passini says, are now quite ready to replace the early stage so-called in-vitro experiments experiments conducted on animal cells or small tissue samples.
We hope that our technology could in the not so distant future replace most of the in-vitro experiments, she adds. That would already make a huge difference because very large numbers of animals are used for these early stage experiments. The scientists kill the animals and take their cells. A much smaller number of animals is used for the later-stage in-vivo experiments.
The Oxford team can already run 3D simulations of an entire human heart. The availability of computational power, or lack thereof, is, however, the major stumbling block for this type of complex simulation.
We have access to some of the most powerful supercomputers in Europe, but it still takes hours to simulate a single heartbeat in 3D, Passini adds. We can afford to do this for scientific purposes, but the availability of such computer power is still limiting the use of these simulations by the industry. We are exploring alternatives, such as GPUs, which might make it more affordable in the future.
The Compbiomed project, which has recently concluded its first stage, has the ultimate goal of creating the entire human organism in silico that could be used for drug testing and simulations of various health conditions.
QMULs Knight says that the organ-on-a-chip technology could in the future reduce the number of mice, the most commonly used animal species in medical research, needed at certain stages of the drug development process. But for that to happen, the alternative technologies have to be validated and proved as reliable (if not more) as the currently used animal models.
The regulatory authorities are understandably going to be nervous about accepting results entirely from a completely new technology compared to using a set of well-established, if not always very accurate, animal models, Knight declares.
For them to accept new technologies, such as organ-on-a-chip, you have to prove that your liver, lung or gut model works in every imaginable set-up. Thats a lot of science and validation and confirmation before you reach that point.
Organ-on-a-chip systems use living human cells in a 3D device to mimic how human organs function. These devices can be used to test both the safety and efficacy of new medicines and other products, reducing the dependency on animal experiments. Usually the size of a 50-pence coin, chips already exist simulating human liver, lung and intestine.
Creating an environment that would simulate, as closely as possible, the environment in which the cells exist in the human body is the greatest engineering challenge facing the researchers.
Its become clear recently that mechanical forces have a huge impact on cell biology and therefore on how drugs behave, says Knight. Therefore, we need to make sure that the model systems that are being developed incorporate the right mechanical forces that the different tissues experience. For example, a model of the lung has to incorporate stretching as you inflate your lung; it has to incorporate the flow of air over the surface of the cells of the lung and the flow of blood in the blood vessels. And only by incorporating these key mechanical stimuli can we hope to generate a model that is truly predictive of how a drug is to behave in a body.
Last year, QMUL received a grant from Research Councils UK to lead a network that aims to bring together the UK research community in order to advance organ-on-a-chip development and cooperate with regulators and industry on validating the technology so that it can be rolled out on a larger scale.
While the complete end of animal experiments in medical science may be decades away, the researchers are positive that with the introduction of already existing technologies, their validation and further improvement, the numbers of animals required for the advancement of science will be gradually but significantly reduced over the coming decades.
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