Animal experiments fail to accurately mirror human diseases
Over 3 million animals are killed for laboratory research in the UK. Not all countries publish data on the numbers of animals killed for experiments, but the global estimate stands at around 192 million animals.
Globally, an estimated 192 million animals are killed for experiments
The annual statistics publication relates to scientific experiments performed using living animals under the Animals (Scientific Procedures) Act 1986.
Animal experiments lead to significant and unnecessary animal suffering. The work is also time consuming, costly, and often leads to irrelevant results as these models fail to mimic complex patient-specific genetics and microenvironments in which human cells develop. In addition, experimental results can be unreliable as they are impacted by the stress endured by animals raised in the lab environment.
Human focussed technologies for human diseases
Around 92% of new drugs entering clinical trials fail, despite having shown promise in preclinical animal tests. This means that animal experimentation is failing patients.
What is urgently needed is a more human-focussed approach to tackling disease. That’s where new approach methodologies or ‘NAMs’ come in. These technologies (which can be used successfully in combination) enable human disease to be mimicked more effectively than in animals. The architecture and microenvironment of cells involved in disease can be faithfully re-created using only human cells and proteins (e.g. human collagen). NAMs also offer more potential for personalised drug development and testing to better predict how a drug will work in individuals, which means more effective therapies and fewer side effects for patients.
Some examples of NAMs (which can be used in combination), featured in our current research include:
3D-bioprinted tumours - natural tissues can be precisely mimicked by layering and linking biomaterials such as different cells, blood vessels and growth factors. 3D bio-printed models can also be tailored to an individual patient's cancer, allowing for more personalised drug development and testing to better predict how a drug will work and for the development of more effective therapies. Our researchers are using bioprinting to develop models to test drugs for blood cancer.
Miniature replicas of human organs on microchips, composed of a network of controllable fluid-filled microchannels, used to investigate organ-specific diseases and test drugs. Click the icons below to see examples of this technology in action in research we’re funding into cancer and heart disease.
Artificial Intelligence (AI) – computers used to optimise diagnosis and predict disease progression as well as drug efficiency, including possible side effects. Disease biobank data – collated tissues and samples and information collected from health professionals can contribute to AI modelling for both diagnosis and prediction. We’re funding research which uses AI to help understand how cancer spreads.
Omics/ Multi-omics – patient-derived ‘big-data’ is analysed to find disease markers and differences between normal and diseased tissue, to decipher how these diseases develop and progress. For example, ‘genomics’ looks at complete sets of DNA and proteomics looks at proteins in the body. This aids in developing new targeted treatments. Different omics can be combined to strengthen findings.
3D simplified miniaturised versions of an organ, produced from human cells to study disease and test drugs. Here’s an example of a pilot study we’re funding using organoids to investigate gastrointestinal disease.
Human-focussed models are rapidly evolving in complexity
Next generation NAMs, such as organoids, are being used to replace not only animals but also, as the technology progresses, to replace more simple, earlier lab models. Human-focussed technologies previously involved a trade-off between high throughput (the ability to carry out lots of experiments) and biomimicry (the ability to mimic human cells and tissues). Simpler models are now being upscaled in complexity using new automated technologies such as bio-printing which means close mimicry of human tissues and organs, alongside high throughput, is possible. Furthermore, advancements in AI and machine learning can help identify complex relationships, saving time and money in experiments.
Work is on-going across the board to increase the complexity of organ models by ensuring they incorporate key players such as the immune system and the microbiome (the collection of microorganisms, mainly bacteria, that naturally live on, and in our bodies) both of which have shown to play a pivotal role in cell behaviour.
It’s no longer cost effective or ethical for governments to keep using animals to tackle human disease, given that we now have human-focussed alternatives which will yield faster and more accurate results, which are more likely to benefit people.
The future of NAMs and next steps
There’s a growing demand from patients, scientists and the public for a push forward, and investment into, the development and validation of NAMs to ensure they are predictive of what will actually happen in patients. A small step but encouraging sign that marked the beginning of a transition towards human-focused drug development, was the recently passed FDA Modernisation Act 2.0 in the US. This is a bill authorising the use of certain alternatives to animal testing and a call to action to scientists to develop human-focussed tools. NAMs validation will establish their quality and safety and encourage more education, training and uptake. Their standardisation, through consensus from academia, industry, regulators and government policy makers will mean that NAMs are ultimately routinely implemented in research and best practice is shared.
Embracing NAMs across the board will undoubtedly bring benefits for patients sooner as well as ending the suffering for millions of animals.
