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Human-focussed technologies to revolutionise cancer treatment

Published on June 5, 2023

Progress in cancer research at crisis point

The number of people surviving cancer has doubled in the last 40 years, but the disease is still devastating people and their families, with 1 in 2 UK people diagnosed with cancer in their lifetime and around 167,000 people dying from the disease each year.

In medical research, there’s a consensus, both in academia and industry, that promising, early preclinical (lab-based) research findings aren’t translating to benefits for cancer patients. The likelihood of a cancer drug being approved and progressing from small Phase 1 trials (which test safety in 20-100 people with and without cancer) to larger clinical trials is less than 6% (shown in the graph below). The average time taken to get a new compound to market is between 10 and 17 years and only 1 in 10,000 pre-clinical candidates ever reach the market at all.

The likelihood of a cancer drug being approved and progressing from small Phase 1 trials (which test safety and involve 20-100 people) to larger clinical trials is less than 6%; a failure rate of over 94%

One of the reasons behind this high failure rate is the over-reliance on findings from unreliable animal experiments. Cancer in people is unique, with a complex interplay between cancer cells and their surrounding ‘microenvironment’ (the cells, tissues and molecules surrounding the cancer), something which can’t be accurately mimicked using animals. Furthermore, the impact of results from animal experiments in preclinical research studies are often over-stated, hailing imminent ‘breakthroughs’ prematurely.

There’s an urgent need to develop more human-focussed ways of studying cancer and testing cancer drugs which will lead to more effective and successful personalised treatments with fewer side effects.

Animal experiments fail to accurately mirror human cancer

Approximately 20 million animals (mostly mice and rats) are used in oncology research globally, with around 200,000 of these experiments conducted in the UK (2021 UK figures from the Home Office). There are two main means researchers use to mimic cancer in animals. One of these is through patient-derived xenografts (PDX) whereby (as seen in the image below) patient cancer cells or tissues are transplanted into mice which then develop tumours.

However, these PDX are poor cancer models as they don’t reflect the spontaneous nature of tumour development:

  • The mice used have deliberately weakened immune systems (to reduce chances of rejection), but this ignores the critical impact of the human immune system on cancer progression.
  • Genes in humans work very differently to those in mice, so tumours evolve differently
  • Most PDX models use late-stage, malignant cancer cells and therefore can’t be used to model cancers that develop early and spontaneously
  • Creating PDX animals is unreliable and slow: tumours may not develop and if they do, may take 4-6 months – this is time and cost consuming

Another method used to study cancer is through using genetically engineered mice (GEM) to induce the development of tumours. Similarly, these are a poor cancer models because:

  • There are substantial genetic and metabolic differences between humans and mice; the tumours that do develop are often vastly different between animals
  • Creating GEM mice is unreliable and slow and can take several months or even years and some mice may never develop tumours – this is time and cost consuming

These animal experiments lead to significant and unnecessary suffering for the animals used. The work is also time consuming, costly and is failing most cancer patients as only certain cancer patient cells can be successfully used. The experiments often lead to irrelevant results as these models fail to mimic complex patient-specific tumour genetics and tumour microenvironments. In addition, there is a significant impact on experimental results caused by the stress endured by animals raised in a lab environment.

The solution: human focussed technologies for human diseases

What’s urgently needed is a more human-focussed approach to tackling cancer. That’s where new approach methodologies or ‘NAMs’ come in. These technologies (which can be used successfully in combination) enable human tumours to be mimicked more effectively than in animals. The architecture and microenvironment of the original tumour can be faithfully re-created using only human cells and proteins (e.g. human collagen). Tumour heterogeneity, which refers to the different ‘subtypes’ of cancer cells that comprise one tumour (e.g. breast cancer subtypes within breast cancer) can be mimicked using NAMs. They also offer more potential for personalised drug development and testing to better predict how a drug will work in each patient which means more effective therapies, with fewer side effects for patients.

Some examples of NAMs (which can be used in combination) that are being further developed to boost complexity 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


Patient-derived organoids – 3D simplified miniaturised versions of an organ, produced from human cells to study cancer and test drugs. Read below about this research in action below, in doctoral student Lauren Hope’s research



Tumour-on-chips – miniature replicas of human tumours on microchips, composed of a network of controllable fluid-filled microchannels, used to investigate the tumours and test drugs. Read below about this technology in action below, in Dr Adrian Biddle and Professor Valerie Spiers’ research.


Omics/ Multi-omics – patient-derived ‘big-data’ is analysed to find disease markers and differences between normal and cancerous tissue, to decipher how cancer develops and progresses.  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.


Artificial Intelligence (AI) – computers used to optimise diagnosis and predict cancer progression as well as drug efficiency, including possible side effects. Cancer biobank data – collated cancer tissues and samples and information collected from health professionals can contribute to AI modelling for both diagnosis and prediction.



Human-focussed NAMs successes and on-going development

Organoid technology has already laid the foundations for the development of new therapeutic strategies for glioblastoma (a type of brain tumour). Here are some examples of the human-focussed cancer research studies that we’re currently supporting to help bring about more breakthroughs for cancer patients:

  • Dr Adrian Biddle, at London University, is developing 3D metastasis-on-a-chip models. He’s growing small human tumours which mimic the way cells move out of the tumour and spread. This is known as metastasis and is responsible for around 90% of cancer deaths. Dr Biddle and his team are also developing a new AI tool to better understand and predict metastasis in cancer, ultimately paving the way for new anti-metastatic treatments.



  • Dr Dania Movia, at Trinity College Dublin, is developing a lab model to monitor and detect lung cancer drug resistance earlier. This could enable doctors to switch patients to more effective treatments more quickly, vastly improving their outlook. This novel, fully humanised model could pave the way to replacing animals used in lung cancer drug testing, saving many animals’ lives.


  • Professor Matt Dalby and PhD student Lauren Hope at the Glasgow University are developing a pioneering animal free model of human bone marrow which will offer a unique solution for overcoming blood cancer drug resistance and finding more effective, reliable and safer treatments through drug testing.



A call for the further development and wider uptake of human-focussed cancer research models

Our grant holder Dr Davina Simoes, at Northumbria University, who is currently working on organoid development has just published a scientific review Next generation organoid engineering to replace animals in cancer drug testing.

In this review, Dr Simoes discusses the high failure rate of cancer drugs and the main hurdles facing cancer therapies being treatment toxicity (i.e., debilitating side effects from chemotherapy), drug resistance (where cancers evolve/change or are influenced by their microenvironment so that drugs stop working) and relapse.

To overcome these hurdles, Dr Simoes points to the need for more human-focussed models, such as organoids which can effectively mimic human tumours through incorporating multiple cell types and enabling re-creation of the tumour microenvironment. She outlines some of the traditional preclinical models used in cancer drug testing and how next generation organoids are being used to replace not only animals but also, as the technology progresses, to replace more simple, earlier lab models.

She goes on to discuss the evolution of human-focussed technologies which 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) towards more complex lab models such as organoids. These are now being upscaled using new automated technologies such as bio-printing which means close mimicry of human tissues and organs with 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 non-tumour 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 have a key impact on cancer cell behaviour.

Dr Simoes states: “Innovation of such cutting edge 3D models will enable extensive implementation in preclinical studies to meaningfully impact future cancer research to a point where it can effectively replace animals in cancer drug testing”.

The future of cancer research

It’s no longer cost effective or ethical for governments to keep using animals to tackle cancer, given that we now have human-focussed alternatives which will yield faster and more accurate results, more likely to benefit people. New approach methodologies hold great promise for personalised medicine in particular, where drug development and therefore cancer treatment can be tailored to patients’ specific cancer profiles. This means more effective treatments with fewer side effects.

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 a human-focused drug development was the recently passedFDA Modernisation Act 2.0 in the US, 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 cancer research and best practice is shared.

Embracing NAMs across the board will undoubtedly bring benefits for cancer patients sooner as well as ending the suffering for millions of animals.

Dr Lilas Courtot – Animal Free Research UK’s Science Manager who carried out post doctoral cancer research said “We are at a tipping point for cancer research and biomedical research more generally, where scientific relevance of NAMs and their predictive power are becoming obvious. Human-focused research needs to be widely embraced, as it holds the promise to revolutionise drug discovery and development, making these processes more reliable, time and cost effective, and ethical at last”

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