Podcast: Meet our Researchers

Chas Bountra

Identifying target proteins for the selection of new drugs

Professor Chas Bountra is interested in identifying and validating target proteins for drug discovery. Various technologies and strategies have allowed him to progress promising clinical candidates into Phase I, II, III studies, and to market. These new drugs offer novel treatments for neurodegenerative and gastrointestinal diseases, as well as pain disorders.

Drug Discovery

How to translate a promising molecule into an efficient drug

Drug candidates are first selected by screening compounds capable of binding to a target protein. Those compounds are then tested in various assay systems, healthy volunteers and finally in patients. Academic research excels at defining good target proteins. Pharmaceutical companies then facilitate the transition from basic research to clinical trials, producing new therapies for patients.

Translational Medicine

From Bench to Bedside

Ultimately, medical research must translate into improved treatments for patients. At the Nuffield Department of Medicine, our researchers collaborate to develop better health care, improved quality of life, and enhanced preventative measures for all patients. Our findings in the laboratory are translated into changes in clinical practice, from bench to bedside.

Chas Bountra: Drug Discovery

Q: Drug discovery can take several paths, what is currently the most prominent method?

CB: It's maybe worth stepping back and just appreciating that all the drug molecules that are out there, they all bind to what we call proteins. Now in humans there're about 26,000 of these proteins. At the moment what we tend to do is we run what we call high throughput screens against these proteins. We take one of these 26,000 proteins that there are in humans, we develop an assay system which can detect whether a small molecule is binding to that protein and leading to a functional effect.  So we develop assay systems which are high throughput and cheap.  They have to be high throughput and cheap because of course what we usually want to do is we want to screen maybe several hundred thousand compounds quickly.  Now what happens is when we run that screen after we put a million compounds through, maybe we might detect a hundred compounds that actually bind to a specific protein.

Q: How can we predict if a molecule can turn into a beneficial drug?

CB: What we normally do is that we have various assay systems which mimic, if you like, or predict the benefit that we want.  What we tend to do in those assay systems is get a sense of what potency we need, how much of the molecule we need to produce the desired effect. That gives us an idea of efficacy, potential benefit with that molecule. What we also try and do is to get an idea of whether that molecule is going to produce any undesirable effects. Then once we've done that then of course we take them into what we call phase I study.  This is where we take the molecule for the first time into humans, and normally in phase I the individuals are healthy volunteers. We try and get an idea of what's the highest dose we can go to without running into side effects in humans. What we would then do is go into a phase II study. A phase II study is when for the first time you actually go into patients and you actually find out if your molecule actually does anything in patients.  Then if we get efficacy in phase II we would go into phase III studies. These are much bigger studies maybe 500 patients each, and normally we do maybe two or three of those studies and each of these phase III studies can cost several hundred million pounds.  Once we have done phase III, then of course we register it and launch it.

Q: How do you overcome the profit motive of industry when collaborating on drug discovery in an academic environment?

CB:  I think it's again worth stepping back and appreciating that any industry has to make a profit to survive.  Pharma, the Pharmaceutical industry, wants to collaborate with academia. They realize that there are certain things that they are extremely good at. Pharma is extremely good at for example running high throughput screens.  They are extremely good at converting lead molecules into clinical candidates.  They're very good at doing things like the toxicology studies.  They're very good at doing the big clinical studies, the phase II B or the phase III studies. And of course they're very good at dealing with the regulators and preparing the relevant documents and then launching the molecules.  We in academia I don't think we'll ever be able to do that, because we just do not have this sort of infrastructure, the scale or the resources etc. 

But I think what Pharma appreciates is that what they are not good at and frankly I think we as a scientific community, all of us are now particularly good at, is what we call target validation or target discovery.  So it's our ability to say that one of these 26,000 proteins that each of us has, that one of these proteins,  if we modulate it, if we stimulate it or inhibit it, it's actually going to make a drug which is going to be beneficial in patients.  We won't ever get rid of the profit motive of these organizations and we need to keep that in fact.  But I think by being free with our science and our knowledge and our expertise and not constraining it with intellectual property, we can bring together many organizations, many private organizations, and I think that that puts us in a much better position to accelerate science and hopefully facilitate drug discovery.