1 00:00:00,240 --> 00:00:06,960 So next up, we have Claire McKay and she her background backgrounds in as an imaging neuroscience, 2 00:00:06,960 --> 00:00:11,070 and I think she spent the last 10 years working in ageing and degenerative diseases. 3 00:00:11,070 --> 00:00:18,870 And she's now speaking mostly today about her role as the imaging informatics lead in the dementia platform. 4 00:00:18,870 --> 00:00:24,990 Okay, thanks very much, Annie and Charlotte, for organising this event and asking me to come and talk to you. 5 00:00:24,990 --> 00:00:27,000 And so, as I said, 6 00:00:27,000 --> 00:00:37,620 I'm going to talk to you today about a specific bit of work that's been done by many people working in dementia research over the last 18 months, 7 00:00:37,620 --> 00:00:43,530 two years. And I hope I'll show you that things are really changing in dementia research, as Ms. 8 00:00:43,530 --> 00:00:45,660 Nisqually outlined already for us. 9 00:00:45,660 --> 00:00:53,910 And it really started for all of us when the prime minister made dementia, its health care priority at the beginning of the last parliament. 10 00:00:53,910 --> 00:01:00,510 And this sort of ended a long, long time of dementia being, as Edwards pointed out, 11 00:01:00,510 --> 00:01:07,470 radically drastically underfunded compared to the burden that it turned that it has for society. 12 00:01:07,470 --> 00:01:14,820 But it's a big problem. And part of the reason it was underfunded is because it's seen as a rather big, difficult, intractable problem. 13 00:01:14,820 --> 00:01:17,580 So if we really want, as a biomedical research community, 14 00:01:17,580 --> 00:01:26,100 to make a difference in terms of the impact of this disease or a set of diseases that cause dementia, we need to crack to massive problems. 15 00:01:26,100 --> 00:01:32,490 The first is that we need to develop neuroprotective therapy. We need to develop ways of protecting the brain before the damage is done. 16 00:01:32,490 --> 00:01:34,380 That's a big problem in itself. 17 00:01:34,380 --> 00:01:42,060 And the second is that we need to identify the means to identify people for whom this intervention is going to be useful. 18 00:01:42,060 --> 00:01:48,090 And we're not going to be able to solve either of those problems unless we have a very dramatic, 19 00:01:48,090 --> 00:01:53,370 large scale commitment to collaborative working, to open science, to cooperation. 20 00:01:53,370 --> 00:02:00,930 And that's quite a big change in the way that we as scientists and clinicians have traditionally worked. 21 00:02:00,930 --> 00:02:11,730 So and I'm going to underline something that Emma said, which is that there are roles for clever people in all aspects of translational neuroscience. 22 00:02:11,730 --> 00:02:19,320 So down at the bottom end of this matrix, you can see the sort of nuts and bolts, the means by which we understand the mechanisms of diseases, 23 00:02:19,320 --> 00:02:26,370 the genetics, the cell biology, the the down the microscope stuff, the scary in the lab stuff that's that's beyond me. 24 00:02:26,370 --> 00:02:33,210 For example, in the middle you can see the bird, the slightly higher order, things like imaging and cognition. 25 00:02:33,210 --> 00:02:35,690 That's the sort of thing that I do. 26 00:02:35,690 --> 00:02:42,900 And then at the end of the of the translational neuroscience spectrum, as you might think of it, you also have the development of trials. 27 00:02:42,900 --> 00:02:47,070 How are you going to implement really good clinical trials, develop and implement trials? 28 00:02:47,070 --> 00:02:51,840 How are we going to turn the developments that come from further down the and the spectrum 29 00:02:51,840 --> 00:02:56,880 into really good diagnostic tools that really can be used at the bedside in your clinics, 30 00:02:56,880 --> 00:03:02,850 for example? And we need to do this across the range of different diseases that cause dementia. 31 00:03:02,850 --> 00:03:09,720 And a lot of it is also about understanding age, the normal ageing process and what this does in the brain. 32 00:03:09,720 --> 00:03:20,400 And so the real the real challenge was posed again, I suppose, in 2013 at the first ever G8 summit for dementia, 33 00:03:20,400 --> 00:03:26,280 which in itself was a real achievement to have a G8 summit specifically about this set of diseases, 34 00:03:26,280 --> 00:03:39,390 where the declaration was that the G8 health ministers commit themselves to the ambition to identify a cure or disease modifying therapy by 2025. 35 00:03:39,390 --> 00:03:43,470 That's only 10 years away. That's incredibly ambitious about to do so. 36 00:03:43,470 --> 00:03:49,530 They're going to dramatically increase the amount of funding available for dementia research. 37 00:03:49,530 --> 00:03:55,020 So a very, very ambitious goal and some commitment to more funding. 38 00:03:55,020 --> 00:04:01,830 And indeed, the amount of funding that was made available in the very next year was was very different from any other year in dementia research. 39 00:04:01,830 --> 00:04:10,170 So this was a list of the funding opportunities that were put together at the beginning of 2014 and added up to something like 130 million, 40 00:04:10,170 --> 00:04:19,710 including the 50 or so million. That's an outline from the and that came from the UK government and on several more millions that came from the UK. 41 00:04:19,710 --> 00:04:21,030 So we're getting there. 42 00:04:21,030 --> 00:04:28,290 The things are going in the right direction, but there's still an awful lot of work to do and this is what the kind of basic problem is. 43 00:04:28,290 --> 00:04:33,180 So this is a cartoon of what happens in in all diseases that cause dementia. 44 00:04:33,180 --> 00:04:38,610 You start off in a state of cognitive health and then at some point you start to deteriorate. 45 00:04:38,610 --> 00:04:44,850 And in that in that early deterioration stage, you might be described as being in the programme of the disease. 46 00:04:44,850 --> 00:04:49,800 And as things progressed further than you would, might be diagnosed with full blown dementia. 47 00:04:49,800 --> 00:04:57,360 And the problem is most of the trials, almost all of the trials have ever been done in dementia are done at this stage of the disease. 48 00:04:57,360 --> 00:05:00,440 So once you already know that, what the. 49 00:05:00,440 --> 00:05:07,190 What the status is of a patient, they've already been diagnosed with Alzheimer's disease or Parkinson's disease or whatever it is, 50 00:05:07,190 --> 00:05:12,710 and that's the point at which the disease modifying trials have been targeted. 51 00:05:12,710 --> 00:05:19,370 There are millions, if not billions of pounds have been spent trying to find treatments at this stage of the disease. 52 00:05:19,370 --> 00:05:23,870 And clearly, when you think about it like this, that's too late. The damage is already done. 53 00:05:23,870 --> 00:05:28,010 So we really need to be pushing back and doing the trials much earlier in the disease. 54 00:05:28,010 --> 00:05:30,710 But you can see the problem immediately there. 55 00:05:30,710 --> 00:05:37,310 So if you're trying to target your trials in the red zone, you've got much less of a signal to play with. 56 00:05:37,310 --> 00:05:40,550 You're not quite sure whether people have got the disease yet or not. 57 00:05:40,550 --> 00:05:46,740 And even if you even if they aren't being able to tell the difference between somebody who's deteriorating and not deteriorating, 58 00:05:46,740 --> 00:05:51,740 you're dealing with a much shallower slope. This is this is something that changes over time. 59 00:05:51,740 --> 00:05:58,280 So we the only way to solve that problem is to get better early diagnostic markers. 60 00:05:58,280 --> 00:06:00,170 And they probably not single markers. 61 00:06:00,170 --> 00:06:05,030 They're probably combinations of markers that will give you the best chance of being able to see the signal early. 62 00:06:05,030 --> 00:06:09,710 And they have to be done in a large scale, has to be done in large numbers of subjects. 63 00:06:09,710 --> 00:06:14,150 And so that was really the starting point for the Dementia Platform UK. 64 00:06:14,150 --> 00:06:21,500 So we can sort of set out the challenges in these three categories, the scientific challenges that we need to go early and we need to learn rapidly. 65 00:06:21,500 --> 00:06:24,260 We can't just be reinventing each other's wheels all the time. 66 00:06:24,260 --> 00:06:34,490 We need to come together as a community and and put our put the best brains that we have into action at this early stage of the disease. 67 00:06:34,490 --> 00:06:37,670 This poses a very large infrastructure challenge. 68 00:06:37,670 --> 00:06:45,230 So the UK has invested millions and millions of pounds in cohorts like the Whitehall cohort that you heard about earlier today. 69 00:06:45,230 --> 00:06:51,350 But these cohorts on the 1946 cohort that you also heard about are not necessarily joined up. 70 00:06:51,350 --> 00:06:56,690 You can't necessarily take data from the two and put them together. They're not always focussed on dementia. 71 00:06:56,690 --> 00:07:00,710 So there are actually lots of cohorts in the UK that have potentially useful information in them, 72 00:07:00,710 --> 00:07:07,010 but they're not necessarily been focussed on dementia and measuring the outcomes that we would be interested in. 73 00:07:07,010 --> 00:07:10,940 And we need to create an environment where instead of all competing with each other, 74 00:07:10,940 --> 00:07:19,070 all the institutions competing with each other, we create a sort of platform for studies to be done at multiple centres. 75 00:07:19,070 --> 00:07:27,170 So attract the pharma companies to come and spend their big money in the UK using our experimental experimental medicine platform. 76 00:07:27,170 --> 00:07:34,760 I'll tell you more about on the point of all of this is the economic challenges are outlined in the previous talk with it kind of goes 77 00:07:34,760 --> 00:07:43,550 without saying that the the the the burden of these diseases means that we must put some energy into trying to solve these problems. 78 00:07:43,550 --> 00:07:50,300 But we also need to reduce the research transaction costs a million to the 50 million pounds that gets spent every year by the UK government. 79 00:07:50,300 --> 00:07:57,560 We need to make sure that's being spent in the best possible way so that we're not, as I say, reinventing each of wheels. 80 00:07:57,560 --> 00:08:01,460 And we really need to be honest. It's incredibly expensive. 81 00:08:01,460 --> 00:08:09,150 Face the trials that are failing at the moment. Mm. 82 00:08:09,150 --> 00:08:18,630 So the Dimensions Platform UK was put together really at lightning speed over the course of the last couple of years and each stage of the process, 83 00:08:18,630 --> 00:08:24,030 we didn't know that the next stage was coming. So the first stage was really about establishing the cohort's, 84 00:08:24,030 --> 00:08:30,090 what cohorts are out there that exist that can be potentially put to better use if we pull them together. 85 00:08:30,090 --> 00:08:34,890 The second stage was about starting to think about creating this experimental medicine platform, 86 00:08:34,890 --> 00:08:38,400 and then the third stage was buying all the kit that we need in order to create 87 00:08:38,400 --> 00:08:47,520 this the this multicenter infrastructure for four trials for studies and trials. 88 00:08:47,520 --> 00:08:54,690 And it was always designed as a partnership between academia and industry so that we're creating what we really want to have, 89 00:08:54,690 --> 00:09:00,210 which is an open science environment, so that we're not all competing with each other. 90 00:09:00,210 --> 00:09:04,890 So you can think of the DPRK as being a sort of three main sections. 91 00:09:04,890 --> 00:09:08,400 The first section is about the cohort's bringing together all of these cohorts. 92 00:09:08,400 --> 00:09:15,730 The second section is about developing the specialist networks and then the third section is the experimental medicine programme. 93 00:09:15,730 --> 00:09:19,290 And I'm just going to go through each one of these and tell you a little bit more about it. 94 00:09:19,290 --> 00:09:28,020 So if we start with the cohorts, there are there are at the moment something like 34 cohorts included in the UK. 95 00:09:28,020 --> 00:09:30,990 But the number goes up all the time because there's no barrier to entry. 96 00:09:30,990 --> 00:09:36,450 If you have a cohort that you think might be useful and interesting and you're willing to share and be part of the platform 97 00:09:36,450 --> 00:09:44,340 and everybody is welcome and the cohorts are kind of separated into its conceptual into these three different types. 98 00:09:44,340 --> 00:09:48,720 So the the easiest one to to think about is the pink is the pink set. 99 00:09:48,720 --> 00:09:53,820 These are these cohorts that have been put together specifically for the research they contain, 100 00:09:53,820 --> 00:09:59,790 very valuable but quite small numbers of people who perhaps carry a familial gene. 101 00:09:59,790 --> 00:10:08,700 So we know that they're likely to get dementia or those specific, well, phenotype disease cohorts excuse me. 102 00:10:08,700 --> 00:10:14,460 And the second set are the the green ones. And these are the very large case rich cohort. 103 00:10:14,460 --> 00:10:20,670 So these these contain many thousands of participants and even millions of participants in some cases, 104 00:10:20,670 --> 00:10:24,480 but would not necessarily originally designed to be for dementia research, 105 00:10:24,480 --> 00:10:29,970 but maybe with a little bit of extra work, we can use some of the information in there to to good effect. 106 00:10:29,970 --> 00:10:31,050 And then the third factor, 107 00:10:31,050 --> 00:10:40,120 the other are the other are the cohorts that have been put together deliberately for this preclinical stage phase of dementia research. 108 00:10:40,120 --> 00:10:47,670 So these are people, healthy, elderly people who may have some kind of evidence that are of of cognitive decline. 109 00:10:47,670 --> 00:10:54,510 But for the most part, this is a group of people who have been put together with with dementia research in mind. 110 00:10:54,510 --> 00:10:59,760 But at the moment, they're still healthy. And there's a special case within this, which is the UK Biobank. 111 00:10:59,760 --> 00:11:05,730 The UK Biobank is an incredible resource that has been collected over the last five to eight 112 00:11:05,730 --> 00:11:14,010 years of 500000 people who are across the across the adult age range aged between 30 and 70. 113 00:11:14,010 --> 00:11:22,410 And at the moment, 100000 of them are being image. This is way bigger in imaging terms than we've ever conceived of before. 114 00:11:22,410 --> 00:11:27,870 So this is this is going to really change the game in terms of the bringing of epidemiology 115 00:11:27,870 --> 00:11:33,870 into the into the realm where we can look at complicated metrics from inside the brain. 116 00:11:33,870 --> 00:11:37,380 And very importantly, these people have all consented for recontact, 117 00:11:37,380 --> 00:11:42,420 which means they're potentially amenable for further studies and trials in the future. 118 00:11:42,420 --> 00:11:49,290 And the Dimensions platform Yuki's is enhancing the UK biobank by rescaling 119 00:11:49,290 --> 00:11:54,090 10000 of the 100000 so that we'll have to time point imaging on these people. 120 00:11:54,090 --> 00:12:02,640 And it's not been fully decided yet, but it's likely that this will be all these 10000 will come from the older end of the spectrum, 121 00:12:02,640 --> 00:12:07,750 goes to ten point imaging is much more sensitive in terms of being able to see that decline. 122 00:12:07,750 --> 00:12:14,310 See that slope that I showed you earlier? And these people also have an extended cognitive background. 123 00:12:14,310 --> 00:12:22,470 So this creates what we hope will be a cohort of readiness, ready for the the new intervention trials when they come online. 124 00:12:22,470 --> 00:12:25,920 And then the second bit of the of the platform is the specialist networks. 125 00:12:25,920 --> 00:12:33,810 And this has really been put together by this very large capital investment that the MRC have made, the UK government's made through the MRC. 126 00:12:33,810 --> 00:12:40,890 And the biggest chunk of this has gone to equipping the UK with five new pet MRI machines. 127 00:12:40,890 --> 00:12:46,590 So pet imaging allows you to see the the chemistry of the brain, the molecules in the brain. 128 00:12:46,590 --> 00:12:52,470 MRI is the best way of seeing brain structure. If you put the two together, you have a new, very expensive machine. 129 00:12:52,470 --> 00:12:56,070 That means that you can get both sets of information at the same time. 130 00:12:56,070 --> 00:13:08,070 There are two already in the UK and so we'll now have a seven site pet network which will dramatically change our ability to to to be. 131 00:13:08,070 --> 00:13:15,180 A great place for pharma companies to come and do their trials if to just explain why that's so important. 132 00:13:15,180 --> 00:13:23,100 Many of the the the large and expensive failures that you might have heard about in the media over the last few years, 133 00:13:23,100 --> 00:13:30,210 the amyloid targeting drugs that have not been successful in changing people's cognitive status. 134 00:13:30,210 --> 00:13:36,720 Well, it turned out that many in many of those trials, a lot of the participants didn't even have amyloid in the brain. 135 00:13:36,720 --> 00:13:41,970 So there was this was an amyloid reducing drug given to people who didn't have amyloid in the brain. 136 00:13:41,970 --> 00:13:45,660 So and, you know, that's that's a bit of a travesty, really. 137 00:13:45,660 --> 00:13:51,270 But the best way to stop that from happening again is but before you give any amyloid busting agents, 138 00:13:51,270 --> 00:13:56,070 you image them first to make sure that the participants have amyloid in the brain. 139 00:13:56,070 --> 00:14:01,110 It's an expensive lesson to have learnt the hard way. 140 00:14:01,110 --> 00:14:11,040 So the the imaging network, as well as procuring some very new, very expensive new kit, will also be focussed on developing new radio like. 141 00:14:11,040 --> 00:14:20,280 And so that's the chemist. That's how you attach radio labels to the compounds that you're interested in, like amyloid and cow, for example. 142 00:14:20,280 --> 00:14:29,040 We need to have a that we have a working group whose job it is to harmonise the way that we acquire data and analyse data. 143 00:14:29,040 --> 00:14:34,170 And then we need an IT infrastructure to support all of this work. 144 00:14:34,170 --> 00:14:40,440 The second research network is the stem cell network and am very kindly done the job for me of explaining 145 00:14:40,440 --> 00:14:47,580 what stem cells are and and the very exciting science that has rapidly grown in the last few years. 146 00:14:47,580 --> 00:14:52,800 That comes from the ability to turn skin cells into neurones and then further differentiate 147 00:14:52,800 --> 00:14:57,990 the neurones into the specific types of neurones that are important in different diseases. 148 00:14:57,990 --> 00:15:02,220 So that means that rather than having to rely completely on animal models, 149 00:15:02,220 --> 00:15:07,290 we now have a way of having human disease models in a dish that can that can contribute, 150 00:15:07,290 --> 00:15:13,980 for example, to screening programmes for new potential new therapies. 151 00:15:13,980 --> 00:15:21,570 And the stem cell network is looked after by wide margins and contains all of the major stem cell centres in the UK, 152 00:15:21,570 --> 00:15:32,070 including the Cambridge one that Emma talked about. And within this network, all of the aspects of stem cell biology are going to be looked after. 153 00:15:32,070 --> 00:15:37,560 And so this is a great example of bringing the community together, these centres, because this is new science. 154 00:15:37,560 --> 00:15:42,460 These centres would all otherwise be competing with each other. So by bringing them together like this, 155 00:15:42,460 --> 00:15:51,240 this is a really good way of showing how we can hopefully show that we can achieve more by by collaborating, cooperating. 156 00:15:51,240 --> 00:15:55,200 And then the third research network is the Informatics Network. 157 00:15:55,200 --> 00:16:02,010 So informatics is is is one of these sort of mysterious words that's come from nowhere and now seems to be everywhere. 158 00:16:02,010 --> 00:16:08,760 And what it really means is both the technology to bring together data and 159 00:16:08,760 --> 00:16:14,160 to analyse data in in this sort of big data world in which we're living now. 160 00:16:14,160 --> 00:16:23,700 And so it's really about the mathematicians. It's the pure nerds of the of the of the medical research world that need to put together the 161 00:16:23,700 --> 00:16:29,610 infrastructure and then the and then figure out how we use it to ask the really complicated questions. 162 00:16:29,610 --> 00:16:37,240 And I'll show you an example of that in a few slides time. And I've just realised I've just announced myself as a pure nerd because, ah, 163 00:16:37,240 --> 00:16:45,840 my name is on this slide as I'm looking after the Imaging Informatics Network for Pardeep UK. 164 00:16:45,840 --> 00:16:53,610 So if I just tell you what the other ones mean. So the core portal is the means that in a couple of years time there will be a portal, 165 00:16:53,610 --> 00:16:59,100 a place you can go to and you can say, OK, I have particular research question what cohorts are out there, 166 00:16:59,100 --> 00:17:05,940 what data is out there that might be able to answer my questions so that I don't necessarily have to go and collect all the data again. 167 00:17:05,940 --> 00:17:10,620 So the design of the portal is happening at the Far Institute in Swansea. 168 00:17:10,620 --> 00:17:16,500 Clinical informatics is another really challenging problem, which is trying to extract research, 169 00:17:16,500 --> 00:17:20,130 useful information from electronic patient records on this. 170 00:17:20,130 --> 00:17:28,440 This means using clever computer algorithms to read natural language because, of course, you might design all the forms in the world. 171 00:17:28,440 --> 00:17:33,840 But busy clinicians don't necessarily have time to click through every box and put the information in the right places. 172 00:17:33,840 --> 00:17:37,380 So actually most of the precious information is written in the case notes. 173 00:17:37,380 --> 00:17:42,810 And so you have to have clever, clever algorithms that can extract useful information from case notes, 174 00:17:42,810 --> 00:17:49,080 and that allows you to suddenly be looking at not the 100 people that you might have been able to collect careful information for, 175 00:17:49,080 --> 00:17:54,030 but a thousand 10000 people whose information might not be quite so clean and neat and tidy. 176 00:17:54,030 --> 00:18:03,000 But you've got 100000 people now, so you're dealing with a different scale. So so that's a big part of what's happening. 177 00:18:03,000 --> 00:18:07,780 I'm going to tell you more about imaging in a second. Digital health is all about the clever stuff you can. 178 00:18:07,780 --> 00:18:12,340 Do with your mobile phones or your Fitbit or whatever it is that you can can hang on 179 00:18:12,340 --> 00:18:17,680 to yourself these days and all of the information that can be collected from those. 180 00:18:17,680 --> 00:18:28,390 There's a genomics network led by Julie Williams in Cardiff and a brain banking network for post-mortem analysis that's led by Shatalov in Bristol. 181 00:18:28,390 --> 00:18:33,700 And the Informatics Network is is all about bringing information together. 182 00:18:33,700 --> 00:18:37,240 And that means that there are there's more than one informatics network. 183 00:18:37,240 --> 00:18:41,230 And part of what we have to do is make sure that they all talk to each other. 184 00:18:41,230 --> 00:18:44,680 So I'll just give you an example of what we're doing in the imaging informatics world. 185 00:18:44,680 --> 00:18:52,510 And in the same sort of thing happens in each of the other networks. So try not to bore you to tears with this. 186 00:18:52,510 --> 00:18:57,460 But there are basically three challenges that we have to we have to solve. 187 00:18:57,460 --> 00:19:06,610 One is that we need to we need to have the kit that is capable of dealing with 100000 images, not just storing the images themselves, 188 00:19:06,610 --> 00:19:12,220 but being able to process them and run all of the pipelines that we've been used to developing on tens of subjects. 189 00:19:12,220 --> 00:19:21,880 We now need to be able to run on hundreds of thousands of subjects and they compute resources required for that are our kind of mind blowing. 190 00:19:21,880 --> 00:19:25,000 But but these days, actually, that's not the biggest challenge. 191 00:19:25,000 --> 00:19:32,950 You know, the computer resources are relatively easy to come by now, and we need to expand the infrastructure for the additional 10000 scans. 192 00:19:32,950 --> 00:19:39,620 But that's actually the easiest problem to solve. The most difficult problem to solve is, is all of the existing data. 193 00:19:39,620 --> 00:19:48,010 So you heard about the Whitehall cohort today. You've also heard about the 1946 birth cohort and of the thirtyish cohort that are in the UK. 194 00:19:48,010 --> 00:19:55,720 About 12 of them have a decent amount of imaging data. These imaging, all of these imaging data exist where the cohorts live. 195 00:19:55,720 --> 00:19:59,200 So they're all in the sort of silos that all separated from each other. 196 00:19:59,200 --> 00:20:03,070 They were acquired on different machines with different protocols. 197 00:20:03,070 --> 00:20:07,810 So we have to find ways of bringing them together so that they can be combined in meaningful ways. 198 00:20:07,810 --> 00:20:13,570 And so creating that sort of platform is the biggest problem to solve. 199 00:20:13,570 --> 00:20:19,470 And we're going to be doing that by actually, I'm not going to bore you with how we're doing this. 200 00:20:19,470 --> 00:20:24,370 It's 2D. You can ask me later if you want to know how we're doing it. And then the third problem is the future. 201 00:20:24,370 --> 00:20:29,590 And actually the future is relatively if we get if we get the present right, then we can get number two sorted. 202 00:20:29,590 --> 00:20:33,250 Then the future is relatively straightforward because in the future we can design 203 00:20:33,250 --> 00:20:42,310 our experiments with the appropriate consent and the appropriate governance. That data can be shared sort of right from the right, from the word go. 204 00:20:42,310 --> 00:20:43,990 And the future is actually already happening. 205 00:20:43,990 --> 00:20:51,370 We've got a couple of large multicenter studies that have been recently funded that are going to use our infrastructure. 206 00:20:51,370 --> 00:20:56,350 So this is the thing that I decided not to tell you. It's too boring, which is that we're going to do this in a federated way. 207 00:20:56,350 --> 00:21:00,250 So we can't just bring all the data together in some central place because their individual 208 00:21:00,250 --> 00:21:05,140 cohorts wouldn't necessarily have the permission of the consent in order to to do this. 209 00:21:05,140 --> 00:21:11,080 So we have to create a federated network so that each each place in the network has its own node, 210 00:21:11,080 --> 00:21:15,190 so that data can be the governance structure for data can be maintained. 211 00:21:15,190 --> 00:21:23,260 Never mind that. OK, so then the point of all of this is so that we can do the experimental medicine and the platform. 212 00:21:23,260 --> 00:21:26,860 UK have the kind of fledgling experimental medicine platform. 213 00:21:26,860 --> 00:21:31,340 This is this, this is the kind of the last bit to get going, really. 214 00:21:31,340 --> 00:21:38,890 But but the way that it's being thought about is in these three overlapping and sort of research areas. 215 00:21:38,890 --> 00:21:43,870 And they they map onto some of the things that Emma talked about and you'll have heard about earlier today as well. 216 00:21:43,870 --> 00:21:50,630 So immunity is one big area, vascular risk is another big area, and then synaptic health is another big area. 217 00:21:50,630 --> 00:21:55,330 And those three those three things, they sound like they're kind of slightly foreign concepts for dementia. 218 00:21:55,330 --> 00:21:59,200 But if you think about it, what we're talking about is whether the blood supply is okay, 219 00:21:59,200 --> 00:22:05,770 how the immune system is coping and how the how the brain is actually working and how the three three things interact. 220 00:22:05,770 --> 00:22:09,490 So there are fledgling programmes in these three areas. 221 00:22:09,490 --> 00:22:16,030 But the main sort of experimental medicine thing that has got going so far is a study called Deep and Frequent Genotyping. 222 00:22:16,030 --> 00:22:20,680 So here's our cartoon again and the red line, which is our challenge. 223 00:22:20,680 --> 00:22:27,430 And so there have been a whole load of studies over over the last 20 years or so that have 224 00:22:27,430 --> 00:22:33,460 tried to say my measurement is the best for detecting early the early stage of dementia, 225 00:22:33,460 --> 00:22:36,340 whichever dementia is, that happens to be your favourite. 226 00:22:36,340 --> 00:22:40,870 So you'll have people who are imaging specialists doing imaging experiments, people who are cognitive specialists, 227 00:22:40,870 --> 00:22:46,390 doing cognitive experiments, people who do the blood based phenotype and CSF based phenotype. 228 00:22:46,390 --> 00:22:55,210 And actually, it's almost never the case that you get even two of these pieces of data being collected in the same sample so they can. 229 00:22:55,210 --> 00:23:00,040 Preprint phenotype is the other name for it is throwing the book at people. 230 00:23:00,040 --> 00:23:08,920 So the idea here is that we're going to take a select group of individuals who are going to have every every. 231 00:23:08,920 --> 00:23:12,640 One of each of the best measures that we know about at the moment and if you 232 00:23:12,640 --> 00:23:16,870 completely novel was thrown in and there are going to be collected frequently, 233 00:23:16,870 --> 00:23:22,690 so individuals who are participants in the computer typing study will have a cognitive battery. 234 00:23:22,690 --> 00:23:28,150 They'll have an MRI scan, a PET scan, a Mexican magnetoencephalography. 235 00:23:28,150 --> 00:23:34,180 They have their eyes scanned. They have a gait analysis. They have lumbar punctures. 236 00:23:34,180 --> 00:23:44,020 Blood's taken other physical tests, and they have all of this done on day one, day to day 30, day night and day 180. 237 00:23:44,020 --> 00:23:50,080 So it's an incredibly intensive amount of investigation for anybody to undergo. 238 00:23:50,080 --> 00:23:58,740 So you can imagine that when this was this is this is what the pharma companies most want with us, US academics, academic clinicians to do. 239 00:23:58,740 --> 00:24:03,670 They want us to tell them what the best measure for that red bit of the curve. 240 00:24:03,670 --> 00:24:07,330 And so the answer is we don't know unless we do this study. 241 00:24:07,330 --> 00:24:12,040 So then the funders, the funders and the patient groups say, but nobody is going to be able to to do this. 242 00:24:12,040 --> 00:24:17,910 It is far too much to expect anybody to do. And so the first thing that we have to do is a feasibility study. 243 00:24:17,910 --> 00:24:19,210 We just completed that, actually. 244 00:24:19,210 --> 00:24:26,710 So that was a feasibility study carried out centres where only four participants, percent were put through this rigmarole. 245 00:24:26,710 --> 00:24:30,340 And I can tell you that the participants had no problem whatsoever. 246 00:24:30,340 --> 00:24:37,270 It's the feasibility was challenged much more by the logistics of getting by the research distance. 247 00:24:37,270 --> 00:24:40,450 Actually, the research assistant to this nearly killed, not the participants. 248 00:24:40,450 --> 00:24:47,350 Participants were fine getting there, getting this all to happen on a single day, getting everything all the rooms lined up, 249 00:24:47,350 --> 00:24:54,430 all the people that you need to to make this happen was far more challenging than the participants had a lovely time. 250 00:24:54,430 --> 00:24:58,990 And this was people with early Alzheimer's disease. So that's not the challenging bit of this process. 251 00:24:58,990 --> 00:25:05,800 But anyway, it has been deemed feasible. So the full application is being written now. 252 00:25:05,800 --> 00:25:11,020 OK, so what I've described today is is only part of the picture. 253 00:25:11,020 --> 00:25:14,710 So it seems like I've hopped around all over the place, 254 00:25:14,710 --> 00:25:22,180 but they weren't really going to take for biomedical research to come up with ways of preventing dementia. 255 00:25:22,180 --> 00:25:29,050 Looks something like this. So we need all of the basic neuroscience to translate itself into both target development 256 00:25:29,050 --> 00:25:34,810 and the on the really good high quality biomarkers that we need for everything. 257 00:25:34,810 --> 00:25:40,540 Actually, we need the informatics and big data to pull together, which is part of the development of biomarkers, 258 00:25:40,540 --> 00:25:46,420 but also part of the the making best use of the resources that we already have and creating 259 00:25:46,420 --> 00:25:51,930 from that these cohorts of readiness who are ready to be put into early phase trials, 260 00:25:51,930 --> 00:25:59,080 who have the running data that we already need for and to the risk the early phase trials. 261 00:25:59,080 --> 00:26:04,420 And in the last two years, a lot of these boxes have been ticked in various ways. 262 00:26:04,420 --> 00:26:08,860 So Emma talked about the Drug Discovery Alliance, the EPA funded, 263 00:26:08,860 --> 00:26:15,850 and that's made a massive difference in terms of the target development for all of dementia. 264 00:26:15,850 --> 00:26:24,130 And what I've just spent most of today talking about the dimensions platform links, it talks to the informatics and readiness cohorts. 265 00:26:24,130 --> 00:26:28,690 And then there are some other large scale European initiatives, 266 00:26:28,690 --> 00:26:33,130 public private partnerships run by something called the Innovative Medicines Initiative. 267 00:26:33,130 --> 00:26:35,710 And these things are like 60 million euros big. 268 00:26:35,710 --> 00:26:43,970 These are big, lots of money and lots of in kind contributions from pharma companies and other companies. 269 00:26:43,970 --> 00:26:47,260 And and they're involved in various bits of this as well. 270 00:26:47,260 --> 00:26:56,620 And most recently, there's a new adaptive trial for for dementia has been has been funded called iPad, if you like. 271 00:26:56,620 --> 00:27:00,280 The sound of that, you can look that up. It's got all sorts of snazzy stuff online these days. 272 00:27:00,280 --> 00:27:05,680 And then the deep and frequent phenotype is feeding into the discovery of of biomarkers. 273 00:27:05,680 --> 00:27:11,230 So this is a this is this is kind of a very, very ambitious set of things that we're putting together. 274 00:27:11,230 --> 00:27:15,850 And, of course, it's not without very significant challenges. 275 00:27:15,850 --> 00:27:24,430 And this is a lovely slide that I've taken from a meeting that I was at recently from the OED and the Oxford Internet Institute, 276 00:27:24,430 --> 00:27:28,780 where they put together some of the challenges for open science. 277 00:27:28,780 --> 00:27:36,170 I think and I think I think the era that we're moving into is is will be characterised by being open science. 278 00:27:36,170 --> 00:27:42,520 So we've had we've had decades of people making a mating discoveries in our field, but only in their little silos, 279 00:27:42,520 --> 00:27:48,580 in their little pyramid structures usually won by their research group, working away at their particular problem. 280 00:27:48,580 --> 00:27:54,280 And I think that to make a significant impact in this disease, we have to think again about that. 281 00:27:54,280 --> 00:27:58,660 And I think the open science and if you're given the grant to collect data, 282 00:27:58,660 --> 00:28:08,200 then your imperative is to share that data as quickly as possible so that the best can be made of it by the by the whole community and their. 283 00:28:08,200 --> 00:28:14,020 I'm not going to go through each of these challenges, but there are some significant there are some significant funding challenges, 284 00:28:14,020 --> 00:28:22,870 you can't necessarily assume that the appropriate consent has been collected from from participants and when when cohort's were originally conceived. 285 00:28:22,870 --> 00:28:26,170 And you can see that this is this has been conceptualised as an iceberg. 286 00:28:26,170 --> 00:28:31,480 So the technology challenge being the tip of the iceberg really is not it's not 287 00:28:31,480 --> 00:28:36,070 that easy to to and to pull data together in terms of the technological challenge. 288 00:28:36,070 --> 00:28:44,230 But actually that's in some ways the least of our problems. So I'm going to leave you with with something a little bit different. 289 00:28:44,230 --> 00:28:49,480 Who knows what this is yet for the Large Hadron Collider. 290 00:28:49,480 --> 00:29:00,910 So Large Hadron Collider was it was the is the result of something that high energy physics community, 291 00:29:00,910 --> 00:29:07,750 the entire high energy physics community have of achieved by all working together. 292 00:29:07,750 --> 00:29:18,610 So this is the and they would be at the LHC is a collaboration between 10000 scientists and engineers from over 100 countries. 293 00:29:18,610 --> 00:29:24,220 It came it was it was conceived. It was the this community decided that there was no other way they were going to be 294 00:29:24,220 --> 00:29:30,130 able to solve their problems other than to have a Large Hadron Collider in 1984. 295 00:29:30,130 --> 00:29:34,270 And I think one of the nicest bits about this story is that they actually dug the tunnel pretty quickly, 296 00:29:34,270 --> 00:29:38,380 this 27 kilometres big ring that was dug under Geneva. 297 00:29:38,380 --> 00:29:40,510 They actually did that in the late 80s. 298 00:29:40,510 --> 00:29:46,150 And that point they still didn't know what the experiments would be or indeed what the particle accelerator, how it would be designed. 299 00:29:46,150 --> 00:29:49,870 So they already, you know, they as a community, they said, we've just got to do this. 300 00:29:49,870 --> 00:29:53,410 We're going to dig the tunnel anyway, even though we don't know what the answers are yet. 301 00:29:53,410 --> 00:30:02,260 And then so they designed the LHC itself and experiments in the 90s and that it took 10 years to build the kit itself. 302 00:30:02,260 --> 00:30:05,830 And then, as you know, the the discovery, the Higgs, the probable discovery, 303 00:30:05,830 --> 00:30:10,240 the Higgs boson was announced in 2012 and it cost about six billion pounds. 304 00:30:10,240 --> 00:30:12,040 So this is an enormous investment. 305 00:30:12,040 --> 00:30:20,170 But this was an entire scientific community coming together and and together deciding that they're not going to go for personal glory. 306 00:30:20,170 --> 00:30:22,540 They're not going to worry about that their next research grant. 307 00:30:22,540 --> 00:30:28,690 They're going to all work together because they care so much about finding the Higgs boson together that it's worth it. 308 00:30:28,690 --> 00:30:33,730 It's worth their collective 30, 30 years of their careers to do it. 309 00:30:33,730 --> 00:30:40,060 And the other Higgs boson paper, when it came out, has 2900 authors. 310 00:30:40,060 --> 00:30:47,480 I Lauffer. I don't think I think that's what we're stuck with. So I'm I'm telling you this because you're the next generation. 311 00:30:47,480 --> 00:30:50,000 So this is it's not going to be us. It's not going to be made. 312 00:30:50,000 --> 00:30:55,090 All of this it's going to be you lot when you come through creating the LHC for dementia research. 313 00:30:55,090 --> 00:31:00,702 That's going to make the difference. Thank you.