Well, now I've been trying draw out a model for you of accidentally to deliberately, starting from a native messenger molecule, modifying its chemistry and making compounds which would interfere with the message. I believe that's the general principle. And the way to do it is you start off, and you systematically modify the messenger molecule, and you work your way through. Now, this is slow and tedious. It takes years. So, as much as anything, what you require in this drug research is... is a matter of character. Have you got the bacon, or whatever it is, to keep going? So you... as you know, in these projects we've... in the case of H2, for example, we kept going for years not getting anywhere, and so you have to have this belief that it's doable to keep you going. But when you get there... this is now my belief; my reading of the literature is that molecules which are made as derived from a natural one have got more selectivity than ones which... so what has happened in... since I left big pharma is there have been a number of massive technological revolutions; this was the genome... genomic one, and then the second one was the ability to make combinatorial chemistry, to make molecules at high speed, and then the technology of being able to make a molecule interact in an in vitro system, such that you could screen... well, nowadays they screen 1000's of molecules a day. Now, just to put that in perspective, industry is screening, any one company, 1000 molecules a day. In... since 1988 my group here have made about under 4000 molecules, and of the 4000, we've taken three drugs into man. It so happens none of them have made the grade but, nevertheless, this was... that's what we got out of 4000 compounds. The industry now is doing more than that molecules in a week and yet their productivity in terms of output is dropping, and everybody's worried about it. So this is the question whether the method which is now being discredited because it was too slow – the iterative feedback measurement that the industry used to use – had something going for it which high throughput screenings through just molecules which are in databases – very lumpy databases I have to admit. So I... I think there's something to be learned from it, and I personally think the industry should... it has become obsessed with technology, and we originally were, as I've told my stories, obsessed with physiology. We were trying to deal with heart beta acid secretion and whatnot, and not just us; everybody was doing it for blood pressure, all kinds of things.
