New models for preclinical evaluation of drug efficacy in common solid tumours
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Prediction of cognitive properties of new drug candidates For neurodegenerative


Start Date
End Date
IMI1 - Call 2
Grant agreement number

Type of Action: 
RIA (Research and Innovation Action)

IMI Funding
8 756 641
EFPIA in kind
9 661 201
2 602 918
Total Cost
21 020 760


When it comes to developing new cancer treatments, most drugs fail before they ever reach patients. This is partly because the models which scientists use to predict the success of future drugs in the laboratory have been too simple when compared to the real tumours. IMI's PREDECT project has developed new laboratory models that more accurately mimic the three-dimensional complexity of tumours, and their behaviour within the microenvironment of the patient’s body. These models could help researchers discover more effective treatments in the future, thereby boosting survival rates.

Laboratory tests are insufficiently predictive of cancer drugs’ activity in humans. The rate of failure to take novel drugs from the laboratory to humans, and then to registration for clinical use, has been very high. According to some estimates, between 90 and 95 per cent of drugs that went into clinical trials had no to only marginal effect on patients’ tumours. One of the reasons for that is that cancer is a very complex disease, both genetically and in terms of the tumour's interaction with the body. The models which scientists have been using in the laboratory to predict the success of a cancer drug in patients do not capture that complexity. IMI’s PREDECT project set out to change that.

By bringing together top researchers from nine pharmaceutical companies, eight academic institutions and three SMEs, the project developed and characterised new laboratory models which should better capture the complexity of the disease and so predict drug efficacy more reliably. This could eventually lead to a lower failure rate in the development of new cancer drugs for the benefit of patients.

Models that capture tumour architecture

The most common way of investigating tumours in the laboratory is by growing cancer cells on plastic dishes. However, this method captures neither the three-dimensional architecture of tumours, nor their heterogeneity, nor the interactions between cells and their surroundings.

In order to better capture the three-dimensional nature of cancers, PREDECT project scientists further developed and reciprocally compared an array of spheroid models of tumour cells, as well as models generated from freshly collected tumour tissue. As an extension of this effort, the project initiated a biennial conference called ‘Goodbye Flat Biology’, under the auspices of the European Association of Cancer Research (EACR), to promote a continued dissemination of the concept that architectural aspects of cancer are very important in building good models.

Reducing use of animals in research

Other important tumour aspects are that they are genetically diverse and that they are in constant interaction with their host. In order to capture that heterogeneity within the native microenvironment of the tumour, PREDECT project scientists developed a method to obtain very thin slices of tumours. These slices capture the complexity that is so essential for validating that a particular drug is going to work in the future.

The tumour slicing method developed by the project significantly reduces the use of animals and required research time. Whereas in the past 18 animals had to be used to obtain 18 tumour samples, now 18 to 20 slices can be obtained from a single tumour. For this work, PREDECT scientists won one of AstraZeneca’s awards for the use of tumour slices as an innovative in vitro platform to reduce animal use.

‘Game-changer’ in breast cancer research

The project also developed a much-improved animal model to study oestrogen-receptor positive breast cancer, one of the most commonly diagnosed breast cancers. Experts wrote that this model was a ‘game-changer’, with the potential to lead to new treatments. The academic partners who developed this model now organise a course on this technique to enable other researchers to use it.

Transfer of technology and other accomplishments

In addition to the successes mentioned above, other top project outputs include:

  • a collection of open access papers, four of which include detailed protocols on the making of new laboratory models developed within the project;
  • a collection of more than 30 000 images generated from a series of 16 oncology marker stainings done on all models created within the project - there are plans to make these available to the research community in the future;
  • transfer of important technology, from SMEs and academia to pharma companies, which could increase the industry’s success in the development of future drugs.

For the benefit of industry, academia, SMEs

The academic community is benefiting from gaining a deeper understanding of challenges in the development of complex cancer models, and from the new models which were created within the project. Thanks to this project, they also gained a better understanding of the thinking, constraints and needs of the industry.

Industry, academia and SMEs are benefitting from the transfer of technology which occurred within the project. For example, a Portuguese SME transferred their bioreactor technology to pharma companies. Thanks to this, pharma companies changed the way they work, and the SME expanded its business and gained important new customers.

The pharmaceutical industry is also benefitting from other technologies and models developed within the project, including tumour slices, as well as a range of 3D and animal models.

All project participants are also benefitting from the collaborative network which was established as part of the project.

What's next?

Although this project achieved significant breakthroughs, there are still many questions left unanswered. The knowledge and insights gained during the project have solidified new collaborations, and may also lead to new projects in the future.

Read the interview with the project coordinators

Achievements & News

‘We made significant breakthroughs’ – an interview with the PREDECT project coordinators
April 2018

When it comes to developing new cancer treatments, most drugs fail before they ever reach patients. This is partly because the models which scientists use to predict the success of future drugs in the laboratory have been too simple when compared to the real tumours. IMI's PREDECT project has developed new laboratory models that more accurately mimic the three-dimensional complexity of tumours, and their behaviour within the microenvironment of the patient’s body. ###These models could help researchers discover more effective treatments in the future, thereby boosting survival rates. In an interview the IMI Programme Office, project coordinator John Hickman of Servier, and academic coordinator Emmy Verschuren of the Institute for Molecular Medicine Finland at the University of Helsinki, explain the project’s most significant breakthroughs, and how these achievements will help in the future search for new drugs. ‘We have published a series of papers, which are open access, about how to create and work with these types of more complex cancer models,’ said Hickman. ‘That data is now available for everyone – it’s kind of a recipe book.’ Read the full interview

PREDECT’s new tumour models could lead to more effective treatments
December 2017

Laboratory tests are not sufficiently predictive of cancer drugs’ activity in humans. The rate of failure to take drugs from laboratory to registration for clinical use has been estimated to be as high as 90 %. In clinical trials, patients are thus exposed to drugs that don’t work and the cost to industry is enormous and unsustainable.### Real human cancers are complex: genetic changes within tumours over time cause cells in one cancer to differ from each other. To this complexity is added the cancer’s interaction with normal cells. IMI’s PREDECT project tackled the problem of complexity by creating laboratory models of the disease that better represent the complex characteristics of different cancers. More appropriate laboratory models for preclinical studies should increase the ability to predict drug efficacy. This will expand the number of treatments available for different types of cancer, potentially providing patients with a higher chance of survival.

‘We chose to focus on complex and sometimes difficult models of cancer,’ explains project coordinator John Hickman of the Servier research institute in France. ‘As an academic-industrial consortium we believed that although our models may not be rapid, nevertheless they better represent the complexity of cancer. These models provide a high content of information more relevant to human cancer. With the high rate of failure of current high-throughput and rapid models to predict clinical activity, we considered something had to change in the way industry looks for drugs.’

Capturing cancer’s complexity – PREDECT models show the way
July 2016

During the earlier stages of cancer drug development, researchers study cancer cells in the laboratory, for example in petri dishes. These two-dimensional models of cancer are relatively cheap and easy to use, so they are still widely used in research, yet they do not accurately replicate real tumours in the body.### This hinders the ability of researchers to study cancer in detail and develop new treatments. IMI’s PREDECT project has developed and analysed a number of more complex, three-dimensional models of prostate, breast and lung cancer that may more accurately mimic the behaviour of tumours in the body. According to Boehringer Ingelheim’s Ralph Graeser, there is no single perfect model that fits all purposes. To help scientists pick the right model for the right situation, the project team has written a paper in the journal Scientific Reports. The article sets out the strengths and weaknesses of the different models and provides detailed protocols for their use as well as advice on when and how to use them. ‘Although people have called for an end to use of 2D cultures, these models are still predominantly used, even though they poorly represent human tumours,’ explained Dr Graeser. ‘The robust protocols for the set-up and analysis of 3D cultures, as well as the cross-comparison of the platforms presented in this paper, should help scientists both in academia and industry to better incorporate these complex models in the drug discovery pipeline.’

PREDECT project delivers ‘potential game-changer’ for breast cancer research
April 2016

Scientists from IMI’s PREDECT project have developed the first animal model of a common form of breast cancer that faithfully replicates the human disease, opening up new avenues for studying breast cancer and developing and evaluating treatments. The findings are published in the prestigious journal Cancer Cell.### Some three quarters of breast cancer cases feature tumours that have a receptor for the hormone oestrogen. Efforts to study these ER+ cancers have been hampered by the fact that animals (like mice) used to study the disease do not accurately replicate how the disease behaves in human patients. Now, PREDECT researchers have created a mouse model that mimics human ER+ cancer better than any other existing model. ‘With this breakthrough, breast cancer disease, progression and metastasis now become amenable to study,’ said George Sflomos of EPFL, the first author of the paper. ‘We can now study crucial factors, such as the action of hormones and molecular responses to therapies, for the first time in a relevant context. But more importantly, this model opens up new opportunities not only for the development but also for the evaluation of breast cancer therapies.’ Meanwhile an accompanying editorial states: ‘This finding is a potential-game changer for breast cancer research, and we predict that it will likely translate into new therapeutic strategies for ER+ breast cancer in the near future’.

PREDECT takes lab-based cancer models to the next level
January 2016

IMI’s PREDECT project is making progress on its goal of improving lab-based cancer models to make them better, more reliable tools for use in medical research and drug development. Studying cancer in the laboratory is challenging; tumour samples in petri dishes simply do not behave in the same way as tumours in the body.### PREDECT is working to improve these over-simplistic models by designing complex three-dimensional models that also include cells from the body’s connective tissues which interact with the tumour. Analyses of the models reveal that these models’ behaviour is much closer to that of cancer in the body. Scientists in the project are now using these models in their research. Another group of researchers in the project is looking at improving ways of studying slices of tumours in the laboratory. Tumour slices provide a lot of information on the architecture and make-up of complex tumours. However, the act of creating a slice and keeping it alive can affect the cells’ behaviour. Scientists from PREDECT have found ways to get round some of these issues to create samples that give more reliable results. The models are all the result of collaboration between scientists from small companies, universities, and large pharmaceutical companies. Details of the models are published in open access papers. The new models offer a number of advantages. Most notably, their complexity means scientists will be able to study tumours in the lab in unprecedented detail, and this will reduce their reliance on animal models. ‘There is a growing wave of concern that an over-dependence on reductionist models is one factor contributing to limited success in drug discovery in all therapeutic areas,’ commented project coordinator John Hickman of Servier. ‘To go to more complex systems that model pathology usually means using more animals. This is also expensive. We are attempting some compromise solutions: complex in vitro models.’

Participants Show participants on map

EFPIA companies
  • Abbvie Inc, North Chicago, Illinois, United States
  • Astrazeneca AB, Södertälje, Sweden
  • Bayer Pharma AG, Berlin, Germany
  • Boehringer Ingelheim Internationalgmbh, Ingelheim, Germany
  • F. Hoffmann-La Roche AG, Basel, Switzerland
  • Institut De Recherches Servier, Suresnes, France
  • Janssen Pharmaceutica Nv, Beerse, Belgium
  • Orion Oyj, Espoo, Finland
Universities, research organisations, public bodies, non-profit groups
  • Cardiff University, Cardiff, United Kingdom
  • Ecole Polytechnique Federale De Lausanne, Lausanne, Switzerland
  • Erasmus Universitair Medisch Centrum Rotterdam, Rotterdam, Netherlands
  • Robert Bosch Gesellschaft Fur Medizinische Forschung Mbh, Stuttgart, Germany
  • Stichting Radboud Universiteit, Nijmegen, Netherlands
  • Tartu Ulikool, Tartu, Estonia
  • University of Helsinki, University of Helsinki, Helsinki, Finland
  • Weizmann Institute Of Science, Rehovot, Israel
Small and medium-sized enterprises (SMEs)
  • Biomedicum Genomics Ltd, Helsinki, Finland
  • Charles River Discovery Research Services Germany GMBH, Freiburg, Germany
  • Instituto De Biologia Experimental E Tecnologica, Oeiras, Portugal
Project coordinator
John Angus Hickman
Institut de Recherche Servier
Managing entity
Emmy Verschuren
University of Helsinki