 Mae'r gwych ond i rywun o'r llyfenau a gwahodd ei llyvern. Mae'r gwych ar gwell o'n cyflwyno, ac mae'n meddywch yn eit unexpecteduau fel bod yn ymateb. Wrth i gofynniadio'n oedd yna'r mynd i'r llawyn cyfrifiadau. Mae'n mynd i gynnyddio'r gwych a'r byw rhai a'r icain y gallach oherwydd. I gofynnyddio gweld fy hynny, ydych chi'n gofynniad gyda y prysgwysau cyfrifiadau. Y rhaid i ni i gael ar gyfer sydd yn y Llyfridd 100 ay rhaid yna y mynd i gael ar gael a'r bwysig o bwysig o'r ddod o'r bobl o'r bwysig o'r ddod o'r ddod o'r bwysig o'r ddod o'r gweithio, felly oedd y Llywodraeth Cymru yn ymdryg, a'r bwysig o cardioasgol o'r ddod o'r bwysig o'r cyffredinol o'r rhaglenau antibodicol ar y cyfrifau, ac yn ymdweud yma o'r cyfrifau'r ysgrifennu yn y ddiweddol, oherwydd mae'n gweithio i'r cerddau. Genes, we all get a set of these cards to play in life but how we play them is how we interact with our environment, our diet, our exercise regime et cetera et cetera. And all of these things determine not only your likelihood of getting disease but how you respond to therapies as well. Now, the other thing about this is that the world is connected by networks, in fact biology is connected by networks, this is a Facebook network for instance. Rydych chi'n gwych gwych, rydych chi'n gwych a'r trefl ac yn gyrsbwrt, dyna'r gwych canolwg yw ffeilio ddysgu. Felly mae'n ddysgu i'n gwych ar Ymerwch yn 1 ddysgu. Mae'r ddysgu yn byw i'r teulu yw hwnnw siarad yn ymgyrch yn gwych yn y mhwyllfa'r ffyrdiol cyllid yn ymgyrch, ond mae'n ddysgu'r gwych ymgyrch yn ymgyrch yn ddysgu'r gwych yn ymgyrch, for a whole range of different diseases. There's all sorts of things, cardiovascular, brain diseases, et cetera. It's amazing you can put it all in one page. So this is giving us new insight in the way that biology works for humans and new insights in the way to develop therapies. But just because they're connections doesn't mean to say that genes are the most important. In fact, environment probably outweighs genes significantly. America got fat and a relatively sport of time without their genes changing. And being obese unpins cancer risk, diabetes risk, cardiovascular risk, and quadruples, the chance of getting Alzheimer's disease in old age. Bad behaviour starts in childhood. So this is a snapshot of British children. 50% don't get enough exercise. 30% of children under the age of 16 get drunk once a week and 10% smoke. So we've got this tension between bad behaviours which is increasing the burden of risk and the technology trying to develop to oppose those risks. If that wasn't complicated enough, we're not alone. Within us there is a universe of microorganisms. About a kilogram in the average person and during your lifetime you put 20 tonnes of bacteria down the toilet. It's quite impressive. Now those bugs actually interact physiologically with us all the time. And carnising them is actually quite important because dysbiosis, which disorders of our microorganisms actually relate to a whole range of these modern diseases from asthma to Alzheimer's disease to cardiovascular diseases and also bugs fight off nasty bugs. So one of the potential salvations for the future is garnering our internal bugs to fight off pathogens and it may be the only hope in the future. In order to measure all of this stuff we need technology. We've got a whole range of stuff and it's very expensive. We've got blood chemistry, we've got imaging. It generates huge amounts of data and one of the big challenges is actually efficiently using this data to guide us in patient care. So we have this ocean of information that has been generated that we need to understand. It's getting better or worse depending on your point of view. We have all these new omics technologies for measuring genes, for measuring microbes, for measuring proteins, for measuring metabolites. If you sum that all up it looks like about a petabyte of information. That's 16,000 iPads worth if you like per person. And we have to capture that information, model it and use it for doctors. There are some areas where the technology is immediately appropriate for the precision patient. This is part of the i-knife developed by Aridazi myself and Jolton Tachats at Imperial where the smoke of the surgeon's knife is used chemically to diagnose on a second-to-second basis the tissue chemistry and give you a decision to cut or not to cut. Overall there's a multimodal data stream. All sorts of stuff that's coming in that the doctor has to make sense of and part of the challenge is handling the data and melding it together mathematically to produce individualised or precision models of the patient. And the biggest challenge of that is visualisation. The data has to be in a way a doctor can understand it. So we're working on what we call stratified medicine engines or navigation engines or stratnavs, okay, strat meds. And we can adapt these to taking the data and produce a new version of the patient journey that the doctor can interact with. And ultimately he can use this for training and potentially he can use it for the patient as well. There's a big tension in all of this between developed and developing world. Most of the spend goes on in the developed world. Most of the population rise and in fact the need is in the developing world. So there's a tension and science should serve all mankind. So we need to think of new ways of getting the technology over to the general population at the same time balancing off those bad behaviours with our technological development. So that leads me finally to the question posed to you which is how do we take advantage of scientific innovation and technology development in the most efficient way to overcome the financial, cultural and educational barriers to translation for efficient patient care. Thank you.