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How can stem cells enhance the drug discovery process? An interview with the StemBANCC coordinators

10/04/2019

IMI Programme Office: Why do we needs projects like this and what challenges were you addressing?

Martin Graf: When we started, in 2012, there were not many iPS cells available, so it made sense to build the list of diseases and disorders, with patients’ cells. At that time, there was not a possibility to order cells, so for the science, the establishment of StemBANCC was necessary.

Zameel Cader: In neuroscience, we are trying to get new medicines for very challenging and disabling disorders, but despite lots of work in academia and the industry, we are not doing well enough. Because the way of discovering and validating new drugs is not working. When the discovery of iPS cells came, the ability to be able to grow human neurons in the dish completely transformed that area. There is an opportunity to directly examine disease mechanisms for neurological disorders in a way that was never been possible before.

IMI Programme Office: Of which achievement are you most proud?

Zameel Cader: When we started working with stem cells, there was this new toy, rather magical, a bit scary, but at the end, the StemBANCC has become routine, it is embedded both in the academia and in the industry, as the regular way to try to understand the diseases process and discover drugs. The main goal of StemBANCC was to be able to have iPSC lines available for both the industry and academia. They are now easily available, through EBiSC and Coriell. StemBANCC has enabled the methods of producing specific cell types that are relevant to the disease, then to tease apart the molecular bases and the gene expression signatures. With Parkinson’s disease, we managed to identify drugs that have the reverse drug signature to the disease process. We can then apply that drug, and show that the disease phenotype that we have been observing, corrects. That gives us quite a complete story around the disease process and the methods by which you might be able to break up that disease.

Martin Graf: We reached most of our goals, and StemBANCC is working nicely.

IMI Programme Office: Would StemBANCC have happened without IMI?

Zameel Cader: It would have been very difficult to undertake the kind of task without the PPP, and the IMI framework. StemBANCC was more than just generating iPSC lines; it was also about the disease models and thinking about how to use them to make assays. Five years ago there was no academic that I knew who would know how to design an assay. By the end of StemBANCC, my and Martin’s groups were running phenotypic assays. This is only because of the IMI- funded programme.

Martin Graf: If the collaboration comes just from pharma, this is typically just one partner, but it is an advantage to have lots of different expertise. The pharma industry could try to build up the consortium, and for some projects, we do so, but it is clear that without IMI, StemBANCC would not have happened.

Zameel Cader: StemBANCC helped both academia and the industry to adopt the stem cell approaches and best practices, giving groups the confidence to be able to use stem cells as part of their routine work. That has then moved the whole field forward, along with the way of using stem cells, without having to talk explicitly to regulators and other grant funding groups. Because these are now employed, the policy conversation has shifted. These types of technologies are now in the routine use, they are reliable, and they can have value.

IMI Programme Office: From the side of pharmaceutical industry, how did you benefit from the project?

Martin Graf: In Roche, we started to work with stem cells three years before StemBANCC. At the time, they were just an exploratory tool. Now we are not just producing neurons; together with Oxford, we learned how to build much more complex, hopefully more relevant models.

IMI Programme Office: In what way did the academic community benefit from the project?

Zameel Cader: The academic community learned a lot about how to use stem cell models in order to understand the disease processes. There has been a lot of sharing of the approach to undertake experiments that have benefited academia: I think that the standardisation to improve reproducibility is important. Before StemBANCC, and without IMI, I would have no idea how I could contact someone in the industry, and now, through IMI, I have those powerful channels.

Martin Graf: We have built up trust with academic community, and we understand each other much better. In the beginning when somebody from academia talked about the assay development, it was ‘another language’, now they know what can help us, and that is a huge difference.

IMI Programme Office: Are patients already benefiting from this project?

Zameel Cader: No, not directly, but the benefit is not far. With respect to finding a completely new drug purely from the stem cell based method, that will take many years to come to fruition. But, in terms of understanding the disease process better, in terms of understanding how the genetic susceptibility releases the disease and therefore which drug would be beneficial for which patients - in those areas we will see the benefits rather sooner than later.

Martin Graf: We have a spinal muscular atrophy (SMA) drug in the pipeline, and the testing on patient iPS derived cells was crucial in drug development. Stem cells are key to disease relevant models; they are starting to give input, while in the past we had to use less relevant animal models.

IMI Programme Office: What are the next steps?

Martin Graf: We know most of the people in Europe that are working with stem cells, and we are now aiming for very specific collaborations, so we know exactly to who to talk to, if we want to develop an assay in various fields. Building the network, knowing the people and building up trust, that is extremely useful.

Zameel Cader: From the scientific perspective, we have shown that the stem cells models can be used for disease modelling in the best kind of way. Can we use stem cells for the stratified medicine approaches; can we use them to understand better the drug mechanisms; for target validation? Those kinds of things are essential for the drug discovery process. What I would like to see in the future is for that to be more broadly available.  In addition, the concept of the in vitro clinical trial – can we make that a reality in the next 5 to 10 years? A conventional clinical trial has to be done on human subjects to prove that the drug was safe and efficacious.  Do we actually need to recruit human subjects, or can we do the same, but using cellular models in a dish? For example, if I want to conduct the study in migraine, I would have pain sensory neurons, I would take efficacious drugs, and I would then be able to test that medicinal product from the subject that I would otherwise recruit. Then I would show that it is efficacious in vitro, which would be cheaper and faster. At the same time, on those same individuals, I could make liver cells, cardiac cells, and I can show that it was safe, that it was not causing the abnormalities of their liver or cardiac functions.  So, to conduct the trial, I would not come to real human subjects - I would start from their cells.

IMI Programme Office: How would you describe your experience as project coordinators, and what is your advice for the future coordinators?

Zameel Cader: You need to be able to put the needs of the project above your own. It is about sharing responsibility with a good core team, and it is about having effective communication channels.

Martin Graf: It is crucial to have academic and EFPIA coordinators who are not doing that in selfish way.  You need a great project office, and we had it for five years from Concentris, and we have built an efficacious, pragmatic, not complicated core team and we were always aware if something is not working well. As a coordinator of such project you are not a dictator, you do not have any power, you are just a coach. Building the network is really the key of the success of our project - that is one of the biggest values.

Find out more

Read the project factsheet