Online collaborations to aid treatment development
Dr Patrick Johnson – Dassault Systems, France
You work for Dassault Systems, it’s a computer software company, and we’re here at WIN where we’ve heard a lot about cancer drug developments. What is your involvement?
What we do in our company is we provide collaboration on-line environment. We’ve been doing that for a lot of industries and we’ve been contacted by WIN and Alexander Eggermont from Gustave Roussy because we are engaged in a large scale consortium for pharmaceuticals, cosmetics, agrochemical companies to invent the next generation on-line collaborative environment and experience. So what we do is we work, we have a consortium with a dozen partners, pharmaceutical companies, computer science companies, research labs, and we develop, we create an environment where all scientists can connect to analyse data, scientific data, in vivo, in vitro but also what we call in silico which is the idea to model a phenomenon like a mechanism of action, a drug somewhere or, let’s say, a specific hallmark of a cancer and we develop something, the wave is called systems biology. The idea is to be able to model a context, a study and with the power of the digital world to see if we can infer some knowledge, simulate and understand better. The first return on investment, I would say, for scientists is not so much simulation, the first is collaboration because when they share the same view of a scientific fact they can better interact and more easily understand between disciplines, between departments, even between companies. So first collaboration and then, of course, modelling and simulation if the power of the digital world enables that. We have done some studies, and we are still conducting studies, with pharmaceutical partners to understand specific phenomena like metastasis, invasion, angiogenesis, model that in our software system and emulate the phenomenon and the progression of the disease. The idea is why do we do that? The idea is to better understand how it is happening and therefore where we should act, where we should invent strategies, targets. It’s not so much a one target approach, since we have the systems view, this global view, it’s a holistic approach. Should we better focus on different spots at the same time because the software will tell us that we have a better chance of action and maybe a cure. That’s the idea.
Can you give me an example, a working model, of something that maybe is on-going?
For example… in cancer, you mean?
Maybe, yes, if there is.
For example, there are specific pathways, very famous pathways like EGFR which is the very famous pathway, we can model that, given the knowledge that we have today. If you put that pathway in the context of other pathways, you have what we call cross-talks, those are linked together. With the knowledge that we possess today, if you simulate the cross-talks of the two, then you understand that by only looking at the first one you miss some phenomena and it’s better, maybe, to act on the second only because you will have an indirect impact which is exactly the effect that you are looking for. So it’s the holistic view of all the interactions between all the pathways, this is the goal of systems biology, that maybe will provide a better understanding and better collaboration for the scientific teams.
Absolutely. So I think we’re seeing that attacking cancer is becoming a multidisciplinary, multi-experience.
It’s multidisciplinary. We believe like, for example, Robert Weinberg from the USA that it will become a logical… we will develop a logical approach to cancer with those models and maybe by mixing, composing those models and experiencing, we call that experiencing them, maybe we will better understand them. Of course, systems biology is just a view, the goal will be to have the full view, like a 3D view, imaging a digital cell. This is, let’s say, not reality today but with all the means that we have in my company we believe this is within our reach in a not too long future. So by having a functional, a system, a structural 3D view, we could maybe 3D experience a biological phenomenon. This is what we target.
OK, thank you.