 Dyfodd mewn gyfweld, yn fwy o'r cyffredinol iawn. Felly, mae'n gwybod i'n gwybod i'r ysgol ac mae'n i'n gwybod i'n cyffredinol iawn. Felly, ddweud, ddodd yma. Fel ei wneud, ddwy'n gwybod i'r ddweud. Felly, y cyhoedd pwysig hynny, sy'n creu'n gwybod y cwmpio'r ysgol. A fwy o'r cyffredinol iawn, efallai y llwyddo'r llwyddo'r cyffredinol iawn. I will go through them slowly, but those of you who are more expert at this than I am, I apologise that some of you may not be technical enough. So, personalised medicine, let me just think it through what is going on at the moment in terms of the NHS. Alan said that I've been interested in drugs and the study of drugs. Drugs are using drugs and drugs represent the second biggest cost to the NHS after staffing costs. At the moment, in the whole NHS, we spend £16 billion per annum on drugs, which is a huge, huge budget. And if the drug were working perfectly in everybody, that would be worth it. But unfortunately, drugs are costing more and more and not only working perfectly. As you can see, this list of the top 10 most expensive drugs in the NHS, I won't go through each one of them in terms of what they use and what they use them in. But the top four drugs cost the NHS £1 billion per annum. And this is only likely to increase in terms of costs for the NHS and the cost is increasing year on year. And part of the problem is that as we move into the future, the cost of developing a drug increases. At the moment, it has been estimated that to take a drug from the first time it is discovered in a test tube, to working in patients and being able to be prescribed by a general practitioner or a hospital specialist, costs £1 billion. And the reason for that is that there's quite a lot of attrition. Only one of the drugs that a pharmaceutical company makes in a test tube out of 5,000 different drugs it may produce, only one of those will actually make it a market. So there's a huge attrition rate. And that was the answer to the cost of failure. Part of the problem is that not every drug works in every patient that we give it to, first of all, some of the physicians. I think I've practised personalised medicines to do all of the physicians. But what we do is rather crude. We do it on the basis of population-based studies, random mass control trials, in which you look at thousands of patients in a random mass control trial, and that tells us what may be the best drug to use. However, when I have a patient in front of me in my surgery, what I'm trying to do is to extrapolate from the thousands of people in a random mass control trial to that individual in front of me. And that is a relatively crude way to be able to treat a patient. Or it's not surprising not all the drugs work in every patient that we use in the first time, and we need to be able to improve on that. Unfortunately, there's also the issue that some patients have outside of their drugs. No drug is without risk. We try to prescribe drugs on the basis of benefit, but unfortunately some drugs also have a risk associated with it. And anti-drug reactions are common, unfortunately, in the NHS. 6.5% of all the admissions to our hospitals are caused by anti-drug reactions. At this very moment in time, if you take all the beds in the NHS, including Scotland, Wales and England together, 8,000 NHS beds, that's 10 800-bed hospitals. If you consider that each hospital has 800 beds, 10 800-bed hospitals are offered by a patient with side effects to drugs. And we need to be able to overcome that cost to NHS £1 billion per annum. And we need to be able to improve on that. So these are issues in the centre of prescribing drugs, and the way to be able to solve that there are many different ways people are trying, but personal medicine is one of those. A personal medicine is not the answer to everything, but it is at least a step forward in the right direction. And really if you go to buy something for yourself, as this person tried to do, you're not going to buy clothes that are not going to fit you. You're not going to buy clothes that are too big or too small. You want clothes that fit you perfectly. And so we should be expecting the same thing of the drugs that your doctor prescribed to you. You should have drugs that are personalised to you, that make you feel better, that are right those for you, that improve your symptoms, cure your disease and no cause side effects. That's what we should be able to do. And that's a tall order. Now I'll show you why that's a tall order, but nevertheless that's what we should be able to do. And that's what personal medicine tries to do. Now at the moment we've got some fantastic tools, technologies, knowledge that's been generated in this century that allows us the ability to progress the potential for personal medicine. Obviously one of the biggest, if not the biggest, advance in science has been the sequencing of the human genome project. Now that was completed at the first draft in 2001, the final draft in 2003. And the one thing is that all that knowledge is now made freely available to anybody in the world who wants to study it. We've gone from the era of actually producing, finding advances and keeping it secret. The internet has been fantastic in terms of allowing us to be able to share that knowledge for lots of people who can look at it. And the work that's been done since the human genome project was sequenced is that we know that 99.9% of our human genome is exactly the same. Almost all of you are in this room. Now the 21% is different. Now if it's a 21% isn't very much, actually if you consider that the human genome has 3 billion bases, 3 billion codes, 0.1% of that is 3 million. So if you consider how many random variations you can make from 3 million, you can see that's why you all look different from each other. And that's the reason for why this kind of diversity and human progress is so important for survival. But also unfortunately it means that some people have pre-dysmysgian disease because of this 0.1% difference. But also different people react differently to the drugs we give them because of this 0.1% difference. And this variation in the human genome is present in every population in the world, in this country, in the world, including in Liverpool and Anflu. Honestly, don't believe the internet. This is only what they can use. At the same time as the fact that we've got this advancing knowledge on the human genome project, there's been advances in technologies as well. So the first human genome project took 13 years to complete. At a cost, as you can see there, of 3 billion dollars. A huge amount of 13 years. But now we can actually get a whole human genome sequence for less than $1,000. It's taking less than two weeks and in fact it's coming down. I got an email from a company saying that for my research if I wanted to sequence some human genomes, they would do it for people $600. In the next five years, ten years, it would be down to $500 to the old sequence of human genomes. The problem is when you sequence it, there are 3 billion letters in there. You need to know how to analyse a string in bed. And that's where the challenge lies as well. So people say that although the human genome sequence is costing less than $1,000, the analysis is probably taking $100,000 at the moment. However, it's improving all the time. The ambition of the 100,000 genome project, which is going on in this country, is to be able to rapidly plan around the whole human genome sequence within the week or so. Which is a fantastic achievement as well. At the same time, what we're doing is producing huge amounts of data. And there's a data revolution going on. And I think that's also the driver of that nice mess in there. At the moment, we're producing 5 exabytes of data every two days. And if you don't know what exabytes are, that's 5 times 10 to the 18. 5 centillion. And that's 500 to 3,000 times the content of the Library of Congress. So we're producing so much data and we need to be able to utilise it. And obviously, big data is the thing that everybody talks about. I'm not sure what most people know what that means. But it is coming along. There's huge amounts of things going on. And that is something that we need to be able to learn how to use. So that we can actually take into all areas of medicine. And personalised medicine is certainly taking advantage of that. And some of the drivers of personalised medicine are seen on this slide. So the first one is more slow, which relates to what I showed you before. That the fact that computational capacity is doubling every two years. And that's continuing and that's important. Cooper's Law says that the amount of data we transmit doubles every 30 months. So that's a huge, huge increase as well if you think about it. And also, Metcalf's Law about networking and so on. The networking, the enormous improvements in the internet, etc. is again a portion of the square of the number of connected users. Imagine the number of users there are at the moment in the whole globe. And unfortunately, Erin's Law is also about drug cost doubling every nine years or so. And these are all drivers for personalised medicine. And we need to be able to utilise the technologies, the advances that are occurring, really to help us drive forward personalised medicine. So one of the things that you will also see in the papers, and certainly within medical literature, is that people could really use different terminologies. Personalised medicine is one thing. Who's had the personalised medicine? And who's ever had a stratified medicine? Very few. And who's had a precision medicine? And precision medicine is term which was introduced recently, more recently, and Obama has probably made it famous. But personalised medicine is what people know or heard of. Stratified medicine is a very UK-based term. How the entity elsewhere in the world uses it. But in a way, they're all interchangeable, and there may be subtle differences, but people do use them interchangeably. And what they basically mean is the tailoring of medical treatment, the characteristics of individual patients. So you can classify people into either small groups or the individual setting in front of me in my surgery, so I can give them the right drug at the right time, at the right dose, for the right outcome. And this will hopefully improve outcomes. People worry about that, is that you should start treating individuals in front of you. But there's something over all population. Are you going to reduce public health? And we know that public health is hugely important. The major advances that have happened in terms of improving our lifespan when it relates to public health interventions, vaccines, clean water, et cetera. But they're not competitive. Our personalised health and public health are actually complementary. And we need to be able to do both of those at work and really take that forward for the population. So the way I look at personalised medicine is that at the moment what we do in medicine is really rely on things that came out in the 19th, 20th century. We have very gross descriptions of diseases. That is that a disease such as Crohn's disease or ulcerative colitis is just called ulcerative colitis. But in fact what we are learning when we move into the newer era of genomic medicine is that each individual disease is many subtypes of disease. And we are really starting to invent a new taxonomy of disease. So in the next 20 years I think we're going to have a completely new taxonomy of disease which says that this is ulcerative colitis, subtype B, subtype C, subtype D, et cetera. And that also allows us to be able to then treat individuals with different subtypes of disease. Unfortunately, even though we have some strata of disease when we define this, there is still going to be variability on how each of us individually respond to a drug. And this is the area of pharmac genetics which is where I have been particularly working and I'll show you some examples of why this is probably the most advanced state in terms of trying to introduce the precision of personalised medicine into clinical practice. The final aspect which is the most difficult is what you do in your life and so on. All of you will be different in terms of the amount of exercise you do, the amount of drink, the amount of eats, and other things as well. Smoking, et cetera. And all of that can affect how you react to a drug. And so that's going to be the most difficult to capture to be able to intersect with the genetics, et cetera, and how we can then integrate all of that to be able to tell us how we treat people better than we do at the moment. So to go from the bottom of this pyramid to the top, there's going to be long journey, there's huge opportunities, there's huge challenges as well. And that's what a lot of work that's going on in this country and worldwide is really trying to tackle. So what I'm going to do is in order to talk to you in theoretical concepts, but I thought it might be better if I give you some specific examples of diseases where it's actually working, where things are, and you can see from that what the challenges are as well. So I'm going to start off with cancer. And obviously the cancer, one in three people in this country will get cancer at some point. Cancer is a genetic disease. We're born with a genome and we live with that genome for the rest of our life. Unfortunately cancer is a second genome that develops in some of us, and cancer is a genetic disease. So somebody who has cancer has two genomes, a cancer genome and the genome that they're born with. The cancer genome has lots of mutations in it. Those mutations are things which are driving the cancer forward. And in some cases, and I know you may not be able to read all of this on the slide, in some cases, people will find that those particular mutations are the drivers for that cancer and you can develop drugs for that particular mutation and therefore try to treat that particular cancer. So here's an example. Malignant melanoma. Most cases of malignant melanoma if captured early can be resected and patient is fine. But unfortunately in some cases, melanoma does metastasise. It goes over to the bones, to the liver, et cetera. And on this of the first PET scan, this is a PET scan, Poster and Mission Traumographies scan. And what you can see are these red spots, which are all the metastasises. And investigators in the Saga Centre, in the Cambridge, were able to see tons of patients metastasises like that. And they found that there was a gene called BRAF, and they found there's a mutation in that gene. And that mutation was driving that cancer forward. And so what they did was to work with a drug company and they were able to develop a drug called Beryratholib, but the name doesn't matter, which was able to actually interact with that particular mutation in BRAF. And when they gave it to a patient like this, with two weeks later the cancer disappeared. You can see in this one, the cancer has completely dissolved the way, which is a fantastic result. And there are many examples of that in different cancers. Unfortunately cancer is a hugely complex disease, hugely complex biology. And what happens is that you get secondary mutations occurring after you give the drug and the cancer comes back after six months. So the next challenge in this area is how you give two or three drugs in combination to prevent those mutations from occurring in a long lasting survival after developing cancer. But interestingly, this is the way that most cancer drugs have been developed now. Most companies have this huge amount of programs going on in all pharmaceutical companies throughout the world. And they are really focusing on this way of being able to treat cancer. And there are benefits as well because if you can actually show in a small trial that a drug such as this works in that way, then you can actually have to take a very small trial which doesn't cost you as much as taking a large trial and you can get it approved by Drug Regulatory Institution's FDA. So this drug that I talked about was the fastest RFDA approval in history. And so there are benefits for the pharmaceutical industry in trying to develop this. So people talk about a pharmaceutical industry and actually about blockbusters. But actually for some of the stratified indications on personal medicines, they actually have benefits because they have to do smaller studies and get it to market quicker as well. But it's not only important for cancer this new way of developing drugs based on genetics. It's already beginning to make inroads into 65 roses. 65 roses is a commonest autosomal recessive disease in the Caucasian population. It occurs in 1 in 2500 people. We've known since 1987 what the mutation was on chromosome 7. But it's only in the last couple of years that people have started to do drug therapies come through which is specific for mutations. So there is a particular mutation in the 65 roses gene which is called G551D which is only causing 4% of the 65 roses patients. And these two individuals working in a company called Vertex with 200 scientists were able to identify particular compounds which were able to affect this particular mutation. They screened 600,000 compounds. They did screening on the computer of 2.7 more million compounds and they came out with a drug called Ivercaftor. Now Ivercaftor works on this particular mutation and starts making it function normally. And this has been a fantastic innovation in those patients kids who have this particular mutation in that their respiratory functions include that life has completely been transformed, they've worked to school, they have fewer hospital admissions, etc. And that's innovation for you in terms of amazing drugs like that. Unfortunately, this comes at a price. It costs the NHS £150,000 per patient per year to treat this particular drug. So that is an issue that maybe we can debate later on. How are we going to be able to form all these expensive drugs coming through? That's not a matter. However, it doesn't necessarily need to be expensive drugs. So here's another example. And when I was a medical student I loved acronyms. I loved names of syndromes. So I had to put this one on brand, brand, brand, brand, brand, brand. It sounds fantastic, doesn't it? It is a childhood motor neurone disease. Kids are born with this initially defined that at the age of 102 they start in developing some problems. By the time they have speech which doesn't develop, they develop swelling problems and so on. Unfortunately, it used to lead to death. And when diseases like that come out about Gone breeding was like that. It's like that, Kamara, about rare diseases. A few people don't know what they are. They're diagnostic odyses. Unfortunately, young kids born with a rare disease go from hospital to hospital, doctor to doctor, having multiple investigations, and nobody knows what's going on. But the ability to sequence a human genome is actually transforming that and for us to know that we're able to identify diagnosis and their potential treatments. In this particular case, Byddwch chi'n gweithio'r gynhyrch a fyddwch chi'n gweithio'r gynhyrch yn y gynhyrch, ac mae'n gweithio'r SLC5203, ond byddwch chi'n gweithio'r gynhyrch sy'n gweithio'r riboflavin. Y rhai riboflavin yw bitwyn B2. Rwy'n gweithio'n gweithio'n gweithio'n gweithio'n gweithio'n gweithio'n riboflavin, bitwyn B2, a oedd yn menlyg yw yn bynnig yn ei wneud wrth yn amlŷwren. Mae'r interested yn gallu allu ei ddangos. A os prison iawn yn gweithio'r cosiwn gweithio'n gweithio'n gweithio'n gweithio'n gweithio'r gynhyrch, oedd yn bwysig yr öllun tŷ, yw ddwy'r ddau ffordd rhan. Mae'n amlŷfyrdd sy'n gweithio'n gweithio'r bwysig o'r ddau gweithio'n gweithio'n gweithio'n gweithio', aoli arall mae'r cyfrifiadau saith, mae'n lle'r bwysig yn deall. Felly, mae'r hoffwyr yn ymdyn nhw'n 100,000 genomes fydd yn ysgrifennu, y projec fydd yn ysgrifennu, sy'n 70,000 rhai o'r hoffwyr yn ysgrifennu, ac mae'n ddatblygu'n ei ddweud i'r NHS, i ddoddau yn y clynyddiadau hosedau, i'r genocraptio ac os ymddangos. Felly mae'n ddweud i'r hoffwyr yn ysgrifennu genomes, i ddweud i'r NHS, ac mae'n ddweud i'r hoffwyr yn ysgrifennu i ddim yn y ffordd, ac yn ffrif destroy'r hyn, mae'n ddweud i ddim yn ysgrifennu genomes, yn byd 2019 o Toweringdon, a beth y byd yn ddweud i'r hoffwyr yn ysgrifennu gynnal, neu ddiwedd wedi gwnaeth gyda'r hoffwyr yn ysgrifennu, sy'n gyfeill o'n fwynydd, ond yn fwynydd o'r hoffwyr yn 2019, beth y bydd yn ddweud i'r hoffwyr yn ysgrifennu gyda hyllaf rhai o gyllid, a hynny'n wedi cymorthwyr yn ymen Gysgrifennu clywg, Mae'r ddechrau drwy'n sylwgr honno yn cael ei ddefnyddio i'r ddweud, felly fyddai'r Llywodraeth Llywodraeth yn cael ei ddefnyddio i'r ddefnyddio i'r llwyddoedd. Mae'r ddiogel yn gwneud hynny'n bod yn cael ei ddefnyddio i'r ddefnyddio. Yn ychydig yw'n ddarparu cyfathau sydd yma, yn fawr ei ddechrau sy'n ddweud. Yn y clywodraeth, mae'n mynd i ymddangos sydd yma, oherwydd yna yma yng nghymru. y cyfnod yw'r hyn yn ymddangos cyfodol o'r necrolwys. Mae'r cysylltu yn ymddangos yng Nghymru, a'r cyfnod cyfnod cyffredigol, a'r cyfnod cyffredigol yn ymddangos cyfnod cyffredigol a'r cyfnod cyfnod cyffredigol, y 60% o'r bodyserfysgau cyffredigol. Mae'r clywed o'r mawr a'r cyfnod cyffredigol, yw ddwy'r gwneud, yw ddwy'r gwneud. Na dweud o'r ychydig ond yw 30% o adeg y buddig arwag 60% oherwydd niferodiadau eich ddweud o'r ddweud. Aw, ychydig yn amlwg iawn am dwy'n ddリfwch o'r ddylch iawn. Gweithio'r ddwyf yn 500 million o ddwyf yn cyflant o'r ddweud o'r ddweud o'r cyflant o'r ddweud. 999,000 o'r ddweud o'r ddweud arweig o fod yn cant i gynnwys, ond mae'n ddweud o adeg. Mae'n 100 million o ddweud o'r ddweud o'r ddelch i'r methu? ac dyma'r rhaid i'r cyffredinol y gwirio allan gerdwyr i'r gwahodau a'is ychydig yn gweithio eich mydag rhagorau gyda'r hynny eich ddyn nhw. Ac unrhyw ni'n defnyddio y'm ddefnyddio ddyloedd o'r cyffredinol yw eu cyfwyr. Nid yw'r drwg hefyd o eichwallydd i'ch bwysig, yw'r bosib ydy gwaith i wahanol cynydol yn gweithio arbennig ym 7% ymen. Mae yw'r ceisio bwysig yw'n defnyddio'r ceg... arall, i'w tyfnod o'r gen i'r gen i ddod yn y cyflogol, ac yn ymgyrchu'r gweithio'r gweithio'r gweithio, ond mae'n meddwl i'w ddysgu'r drwsgol. Yn y cymryd yw'r gweithio, yw'n meddwl i'w ddweud y cegau'r gweithio'r hwnnw, mae'r wneud o ddyn ni'n gwneud o'r gweithio'r hwnnw? Yn y cwylwyd gan ddylch chi'n unid yw'n meddwl i'w ddwylo'n gweithio'r gweithio. Ond wedi gwpeth idydd gael o'r cymdeithas wedi gweldio'r cyflom a gwyddwch eich cyflom yn ei ddweud o'r ddall Scotiaeth yma fel eu perthyn i yw'r gyflom yn Yn Gwlad场 mewn Yn Gwlad Nadu Gwlad Rhaglion Unedig. Na dwi'n meddwl arall y Cymru, bod yw'r cyflom yn y Gwlad Rhaglion Unedig yn y ddweud o'r cyflom lleol ein cyflom yn y dystau'r cynnig aeth yn eu ddweud. Dyna ydych chi'n yn dweud? Yn y ddu... pan mae'r test yn ymweld, mae'r reacio'n ysgrifennu yn rhan o'r 70% i'r unig. Mae'r test yn ymwylltio ar y 2006, y reacio'r rhath honno yn ymweld yn ymweld yn 1%. Felly, rwy'n meddwl y cwymod yw'r bach o'r hefyd yn ymweld yn y ffrifos five yma. Yn yw'r genetig yn ymweld yn ei hun, yn y NHS. And there are many other genetic factors that should be identified all the time in relation to these serious adverse stress reactions. And I'm showing you just three of them and in fact since the beginning of the century, twenty-four different HLA aliens, which are the genes which we are looking at, have been identified with different serious types of adverse stress reactions. Those that may cause bone marrow suppression, those which cause blistering of the skin, those which limit failure, those which affect the muscles and cause your muscles to necrose. And we've now got the tools to be able to really try to prevent these particular reactions. And the way we're doing that at the moment is to try to get these HLA tests being better available within our NHS hospitals. At the moment, if I wanted to get an HLA test, I would have to get each individual HLA test done. It would cost me, it would cost a hospital. I worked for about 100 pounds to do that test. It would take me two weeks to get the test through for my patient. But two weeks is a long time. I don't want to wait two weeks before I give the drug I need to give to the patient while waiting for the test result. And so what we've done recently is to work with the company and we've developed another technology which allows us to be able to type all of those different genes that you saw in the previous slide very quickly with a turnaround time of less than 48 hours. And the cost of that panel is going to be about 20 quid, which is much less than the 100 quid activity for each individual test at the moment. And so while technology is improving, it is also becoming cheaper and that's the reason for showing you this particular example. The important thing is also that most doctors out there will not know how to interpret that kind of very, very complex test that we are developing. So in order to help them, we've also developed a clinical decision support system. And what that means is that when a test result comes through, the doctor can click on his computer to a link. He'll be taken to a website which he'll have these kind of data. He can then press on a drug that he wants to look at that will tell him what that particular gene that is important is for that particular drug and will tell him what to do if a patient is positive for that particular gene. And that kind of clinical decision support system is going to become very important in the future. Nobody will be able to hold 3 million data points in their head and remember what each one correct did. So we will need to use information technology in a much better way so that we can actually utilise it to be able to give the best drugs to the patient in front of us. It's important to note that our general practitioner has 10 minutes to see a patient in this country. If I give him 3 million data points and say, interpret that, you can see that 10 minutes is going to go out the window, right? It's either going to say, well I'm going to interpret that and I'll see if my next patient is 3 years from now or you just throw it away. More likely he's just going to throw it away. So we need to use computers to be able to help us to interpret that so that we can actually improve on the way we treat patients. I'm just going to do something which is very important I think in terms of how we treat patients, the dose. Everybody knows that every drug that you take has a dose on it. It will be 10 milligrams, 50 milligrams, etc. And how selfless was a polymath? 500 years ago he said, poison isn't everything. No thing is without poison. The dosage is what makes it either a poison or a remedy. And you may have thought that we've learnt in 500 years to be any better than we have at the moment, but unfortunately not. We still don't actually do dosing properly and so on. Because we assume that the dose that we give to the patient is equivalent to what actually gets into the bloodstream and into the area where the disease is. And that's not correct. It varies. So if I, again, each of you is 10 milligrams of the same tablet, I will be able to find a 54 variation in the amount of drug you have in your bloodstream. And we need to get better at actually making sure you're getting the right dose at the right time. And in fact, this is happening with every drug. Here's an example of a drug which is used in inflammatory bowel disease in osteoclitis. It's called infliximad. It's a biologic. It's given by injection. And people have been trying to find out why infliximad works in some patients and doesn't in others. And the best indicator at the moment seems to be the amount of infliximad you have in your bloodstream is a determinant of why it works better. And I will know that there was something called therapeutic drug monitoring, which people have used it, and he was the exponent of this. And therapeutic drug monitoring has gone out of fashion in this country. And in fact, I can promise you that therapeutic drug monitoring is going to be the major component of precision of personalized medicine in the next decade. And this is what's called reinventing the wheel. Great. We've tried to look for very complex solutions. In fact, some of the simpler solutions are, but we've already tried them before and started them when we're coming back to those. And in fact, this is exactly what we do at the moment. If I see a patient with kidney failure, kidney impairment, I know from the drug label that I need to be able to reduce the dose of a certain drug. So he is an example of an antibiotic. In patients who have a form of kidney failure, I need to be able to reduce the dose. So I don't cause any side effects in them. But at the moment, when we have a genetic factor in a patient, which causes the same magnitude of change as you see with kidney failure, we ignore it. We don't change the doses. And that can lead to problems as well. And so can we actually tackle that and can we actually improve that as well? And that is also happening. And that's something that happens, for example, with drugs such as warfarin. Now, many of you will have heard of warfarin. Some of you may be on warfarin. And warfarin is a drug that's used by 1% of the UK population. The problem with warfarin is that we don't know what dose you'll require. Some people require half a million pounds a day, some people require 20 million pounds a day. And we're trying to identify why it is that there's this variability in 44 variability in dose requirements. The problem is if we get those wrong, we think we're bleeding as in these patients. And we want to avoid that bleeding. So warfarin has been undertaken by us, but also by other people. And this is a very complex diagram. And basically, this was a single study undertaken in 714 patients. And we got a million different data points on each of those 714 patients. So the 714 million data points on that one slide. That's the complexity of studies which are being undertaken now. And what this shows, and this is the most important part to focus on, it says that as one gets older, you need lower doses of warfarin. And you're a very young audience. And this is something for you to look forward to. As you get older, you'll never get smaller, so you need lower doses of warfarin. As one gets heavier, you need a higher dose of warfarin, which is what you'd expect. But actually, the most important factors determining the dose requirement for warfarin are two genetic factors, which is shown there. This one calls CYD2C9, and this one called DECO C1. And those are the most important factors that determine why one requires different doses of warfarin. And in order to determine whether we can actually introduce this into clinical practice, and I'm sorry, I'm getting a bit technical now and go through this a bit more slowly, we undertook a randomized control trial. Because my physician colleagues are pretty skeptical, conservative, and they need to be, they don't want to introduce innovation without showing that it is working in clinical practice. And so I undertook a randomized control trial with my collaborators. And what we did was to say, if we compared genetic base dosing to what we do look around in NHS, would it be better? And we did this randomized control trial in both the UK and in Sweden. And what we were able to show was that genetic base dosing was 7% better than standard dosing. Now, 7% doesn't seem a lot, but because you're looking at a coagulation system, which amplifies its effect, it is actually clinically significant. And so we've shown the 7% difference. But when then I go and show it to commissioners in England, we have to talk to the clinical commissioning groups. That's how we get funding for hospitals and so on. They say, well, actually we haven't shown it to be cost effective. So we don't have to do cost effectiveness study. That is to show that if we introduce a new innovation to the NHS, it will be affordable to the NHS. And again, we went and showed that it was cost effective to the NHS, which is shown on this particular slide here. And you can see the UK curve shows that by the time, and the threshold for cost effectiveness is about £50,000, and 90% probability to be cost effective at that kind of threshold. So then once you've done that, people come and say, well, actually, we're still not building new. You need to do more studies. Okay, we'll do more studies. So the next thing we did was to actually go and work with the company and develop a new way of genotyping, which is more efficient than we did in the randomised control trial. So we worked with a company called LGC. And basically what this test does is that we take a mouse swab, we put it into this machine here, and within 45 minutes we can give results on those two genes that I showed to you before. And this can be done by nurses in the clinic. So the next step we're supposed to share, well, actually, if we can give the machine to the nurses, they'll see the patients and they can dose them based on the genetics they do in the clinic. Will that work? So we did the randomised control trial, as I said, and so what we then did with the new machine was implementation study. And the implementation study has just been completed. It's now published. And what this shows is that the implementation study is that nurses undertake doing a mouse swab, doing the genetic test, doing the dosing themselves based on the algorithm on the web, while able to improve dosing with orphan by 7% as they were with the randomised control trial. So this actually shows you that it is working as well. It can work in a real world setting, such as NHS with the complexity of the NHS. Now, I'm just going to the last part of the talk. So, unfortunately, we do have changing demographics, and our population is getting older. And as one gets older, once kidney function goes down, once liver function is not so good, once respiratory function declines as well. I'm sorry, I don't know how to give you the rest. And unfortunately, you need multiple drugs to be able to control those diseases at the time when all these kidney function, liver function and so on is going down. So the big challenge that's facing personalised medicine, I think, is how are we going to be able to improve the way we treat our elderly so that they can have better lifestyle, better quality of life, stay out of hospital and have an independent life in the community. And there are many things that one can do, and not just personalised medicine, and obviously those are all on-going, but there are ways of being able to look at this with personalised medicine as well. And this is one particular study which has been done in the States, and what they did was to say, well, if you had a genetic profile on all your patients and they were able to dose-space on that genetic profile, would that improve various outcomes, such as hospital admission, emergency room attendances, et cetera, and death as well? And they did this in a group of patients who were over 50 years old, who were on multiple drugs at more than five drugs each, and then they did a small trial of 57 patients versus 53 people. And they introduced this genetic profile first of all in a group of patients, 57 patients, and they compared them with the 53 who didn't have genetic profile. And what they were able to show was that in those people who were untested, they all had worse outcomes. So you could see the death rate was higher, the hospitalisation there rate was higher, et cetera, based on genetic profiling. So what was happening for here was that doctors were using the genetics in the patients to be able to modify the doses they were giving, and I again come back to dosing being important, but also drops they were giving as well to be able to improve the outcomes of these patients. Unfortunately, this is a very small study. It's only 57 versus 53. So what's going on at the moment and is funded by the European Commission is a 15 million euro study in 10 EU countries with seven different countries recruiting patients. Two, see whether genetic profiling, before you see a doctor, improves things for you in terms of the outcomes. And the only site in the UK is in the local whereabouts of you are leading that study. And what we're trying to do is to see whether we can actually improve outcomes in terms of reduced side effects of patients and making genetics available the first time to see the doctor rather than as a reactive response. So it's preemptive genatagin. And this is really a foreigner to when everybody has a more genuine sequence. And if you have a more genuine sequence, you need to be able to take that into account and not ignore it. And this study will tell us whether we can do this in a clinical and cost-effective manner to be able to improve outcomes of our patients. So just the very last part of the talk is really patients and public empowerment. I think one of the major drivers for genomics will actually be the public. And some people have already gathered genome partly, and no sequence, but tight. Has anybody had a 23 AB test down here? Well, it's available for 110 pounds. Now, you just said before, it goes off to the company in the States and you get the result back and you get that interpretation. And this is exactly what happened with this particular individual. This was in mid Wales on a Saturday morning. This patient was having an anesthetic procedure. And this patient handed the 23 AB result to the anesthetist and said, I've got a genetic deficiency in this particular enzyme. Please don't give me this an anesthetic. And I've had patients coming to the in my clinic handing me those genetic test results. And that's going to become more and more common. And this is really patient empowerment. And as general practitioners, doctors, et cetera, we need to get ready for this so that we can actually answer our patients because I think it's terrible if a doctor said, I have no idea what you're talking about. And they need to be able to interpret it and actually say, well, this is useful or not useful or if it is useful, now I'm going to change your therapy because of that. So that's really important. A patient empowerment is coming through. Some patients are going much further in terms of what they're doing. So has anybody heard of microbiome? Yeah? Microbiome is the bacteria we carry. There's more bacteria in our body than there are in cells. That's something else we use at the point. So some people, you can actually do your microbiome for $90 in a way and you can stick a swab up your bottom and you can do a microbiome of that or you can send some pieces to a place in the United States and they'll do a microbiome for you. If you're really rich, you can do it four times for $400. And you can see whether your microbiome changes from week to week. And some people have done that and some people, particularly in the sense that they're going into extreme. They had an interpretation saying that microbiome is not very healthy so that they've given themselves a fecal transplant. This is patient empowerment. Now, if you don't know how to do fecal transplant, go to YouTube. There's a video there of how to do it. Honestly. And this person from NIH said that some lay people have taken this idea of fecal transplants that perform in their own fecal transplants at home. Folks are finding to provide them with stool making stool smoothies. I hope they use it from London when they use the truth smoothies. And then they give themselves stool and I was without medical supervision. And then she said, ends up by saying this is a bit bizarre for a culture where people smear hand sanitizer of the handles of the shopping carts. So that's anemoginomics. So the last thing I want to let you with is to come three of our sensors. Who has the thick bits? Have you got the thick bits? Yeah, I've got thick bits and so on. And I think sensors are going to be a major part of what we do as well. If you look at what a conventional engine does at the moment, new cars are out there, it's collecting data all the time. A flight data recorder will collect and go by some data from the flight. Yes. In Newborn baby, we use the same five data points that we use in 1952 at the moment. Which is crazy. And with the technology in other areas why are we still using these five data points in the baby that was divided between the after in 1952. And that is going to change with the sensors and so on. And this is already happening. And patience again, the power is very important. Now by sensors, which can actually record their own ECG on a live phone. Okay. And this has actually been asked of medical consequences as well. Because many patients will go have been to see me and the cardiologists and they say I've got palpitations. So we do a recording for 24 hours. We don't find any arrhythmias. We do a recording for five days. We don't find any arrhythmias. It's just that you can give the sensor and many cardiologists now do give the sensor to their patient. They can put it on the back of the iPhone. When they get palpitations, they just put both fingers on that sensor and that gives you an ECG recording like that. And from that ECG recording you can tell whether you've got an arrhythmias or not. And these are really patients helping themselves with their treatments and so on. And those kind of sensors are going to get more and more common. And the reason for that is the digital revolution. And it says the number of smartphones is going to cost about 6.1 billion by 2020. And apparently that at the moment we carry about 1.8 devices per person. I'm not sure what the price is. And by 2020 you're going to carry 6.6 devices. What will be overloaded with iPhones now? But that is true. We are in the middle of the digital revolution which is going to be very important. So let me finish. For some areas, I think for example in cancer NHS is already delivering personalized medicines. How access to medicine is diagnosed is required to practice personalized medicine can be patchy. It's important that we actually make sure that it's available to everybody so we don't exacerbate health inequalities. Genome sequences will become more common and everybody will have genome sequences at birth eventually. We need to learn how to be able to interpret that and use it effectively. I think an important aspect of any kind of delivery of personalized medicine is going to be the education training of our workforce to make them more skilled in delivering that. Also important is the education of the public in terms of what they can expect to practice medicine, what are the benefits but also what are the limitations. Personal medicine is not a panacea. It's a refinement of what we do in medicine and everything we do in medicine apart from occasional revolutions is a refinement. It's an evolution of the way we practice medicine and that's important to understand that. So what I'm going to do is to cover some aspects of that. There's only small aspects of COVID. There are an enormous number of things going on that you are interested in. There's lots of different sources that you can read on the internet but please be aware of fake news. So I'm from Liverpool and I'm going to give you a quote from John Lennon. It will all be okay in the end. If it's not okay, it's not the end.