Molecular biologist and science policy leader Professor Keith Yamamoto discusses the current revolution in biological sciences and the emerging field of precision medicine.

SHANE HUNTINGTON Im Dr Shane Huntington, thanks for joining us. Scientists have long laboured to understand life and its complex processes. Their work through the centuries has brought us all enormous benefit, from the development of drugs to treat once incurable diseases, to an increasingly sophisticated understanding of the ecological impact of human activities on the planet. As we expand our investigations into data rich fields like genomics and personalised healthcare, biology is becoming a field populated not just by biologists but also by mathematicians, physicists and statisticians. Biology as a result is changing. Naturally these changes bring the promise of better healthcare standards for people with a cancer or other life threatening conditions, as well as preventative measures to keep people well in the first place. But are we really prepared for this revolution in biology? Do we need to adjust their educational models to make sure we equip health researchers with the right skills? How will this affect the type of healthcare systems we'll have in the coming decades? To answer these questions and discuss the broader implications of a new view of biology, we are joined on Up Close by molecular biologist Professor Keith Yamamoto, Vice Chancellor for Research, Executive Vice Dean of the School of Medicine and Professor of Cellular and Molecular Pharmacology at the University of California, San Francisco. Keith is in Melbourne as a guest of the ICT For Life Sciences forum. Welcome to Up Close Keith.

KEITH YAMAMOTO Thank you, it's nice to be here.

SHANE HUNTINGTON The field of biology has changed dramatically since you began your research career in the 1970s. Can you give us an idea of the main differences in how biology is practised now compared to back in those days?

KEITH YAMAMOTO We're at a very interesting time in biology and in science in general. Biological research at the time that I started in the 1970s as you said, was very much a descriptive field. We'd look through microscopes and examined cells, took pictures of them, did experiments in biochemistry where we would break down specific cellular components and look for the presence and absence of a signal. That descriptive period was a wonderful one. Ones where we gained immeasurably in our understanding of the components that are players in biological processes and understanding the framework - an outline - of the way that those biological processes work. Today things have changed a lot because we have realised that if we're going to move forward from collection of information, naming the players that are involved in the play to actually understanding those processes. Understanding them in ways that we can intercept them or modify them then we have to become a quantitative field. We have to understand things in numerical detail. And to do that biology needs to invite into the field - and it's doing this progressively successfully - scientists who practice their work in a different way. People who are doing physics and chemistry and math and computation and engineering, who'd bring a different way of thinking about problems, as well as working on them. So that's the transition; it's a remarkable one that we're just in the midst of right now.

SHANE HUNTINGTON Now I have to dig a little bit there when you refer to biology as a quantitative field in the current day and in the future, how do you define that relative to what it's done in the past? Certainly I think a lot of biologists would assume they were doing a quantitative version of a research.

KEITH YAMAMOTO Right. So we were able to infer biological processes and even the ways that those processes and even the ways that those processes worked with descriptive means, looking in a microscope to look at the change and the shape of a cell for example. Or the cells that a particular cell would choose to interact with; maybe even merge with and fuse with. Those kinds of descriptions carried us a long way in making theories about exactly how those processes worked. But they don't actually tell us how the processes work. So now the next step is to understand those processes using quantitative methods of engineering and chemistry and physics that will bring us the real numbers behind those observations. It's those numbers that turn out to give us the mechanistic detail to be able to carry forward. The real test of understanding something in a sense is being able to reproduce it yourself - by putting the pieces together and the steps together - the [imagines] working. So we're getting an outline of the players but don't know how to put them together well enough. We don't know whether when we put together a reaction in a descriptive mode whether when it looks like it's working whether it's working the same way that it works in the cell. But getting the numbers behind it all will tell us that. That level of understanding is crucial for doing some of the things that you talked about in your introductory statement where we have the chance to be able to understand them well enough to be able to intercept disease mechanisms and things of that sort.

SHANE HUNTINGTON This presumably will mean that we have to look at our education models - especially at university level - for training biologists. Is the current version adequate to deal with this new biology that you speak of? Or do we have to go back to the drawing board and start redescribing the way in which a biologist will go about their day?

KEITH YAMAMOTO I think we have to go back to the drawing board. But it's going back to the drawing board in I think exciting ways that are going to extend further back from the graduate period of training into undergraduate and even earlier and that is finding a common language for all of these different scientists to speak. The work has gone forward in ways that have taken us to more and more hyper-specialisation. So there are biologists who speak different languages and really can't communicate well with each other. You can imagine what happens when we begin to try to interact with engineers and physicists. So we're at a stage where finding that common language will have a huge payoff; it's going to be very exciting. And we can begin doing that early on. One of the things that we're doing in the University of California, San Francisco UCSF where I work is to begin bringing our first year graduate students together in teams in which the team members - four or five people - come with different backgrounds. Some have been training in physics, some have been training in molecular biology, some have been training in computer science. Bringing them together in teams and then having them to go through a series of so-called boot camp courses - very short intensive courses - intended to bring everyone up to a common level of literacy. And they see immediately the different languages, but somebody on the team understands the language and other people don't and they begin interacting with each other and teaching each other right away. You can see that that can be done any time, it doesn't have to wait until graduate school. So we think that that kind of model can actually get us to where we need to go, not only painlessly but in a way that's fun and interesting.

SHANE HUNTINGTON In that model you're not just talking about retraining the language skills of the biologists, but the other fields as well - the physicists. So it's a two way process isn't it?

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