1 00:00:06,460 --> 00:00:12,160 Well, ladies and gentlemen, welcome to the Oxford Summit 2021. 2 00:00:12,160 --> 00:00:16,930 I think the past year, of course, it's been horrendous for all of us and for the whole planet. 3 00:00:16,930 --> 00:00:20,470 But I hope and I believe we've learnt lots of lessons. 4 00:00:20,470 --> 00:00:25,690 So what I'd like to do is just share with you some of the lessons I've learnt over the past 15 months or 18 months, 5 00:00:25,690 --> 00:00:33,670 et cetera, with five brief stories. But the big message is I'd like to give is that sort of across the planet? 6 00:00:33,670 --> 00:00:41,050 We're facing some major challenges. And the only way to come up with solutions to these is by working together. 7 00:00:41,050 --> 00:00:44,760 And I do believe by working together, we can do the impossible. 8 00:00:44,760 --> 00:00:50,980 So let me share these five sort of narratives and apologies for the fact that they are largely Oxford based. 9 00:00:50,980 --> 00:00:54,970 So the first story, of course, has to be the Oxford AstraZeneca vaccine. 10 00:00:54,970 --> 00:01:01,390 So the story there is sort of back in March last year, a couple of our senior academics Adrian Hill, 11 00:01:01,390 --> 00:01:09,610 Sarah Gilbert, both the household names now they had created a company called Vaccine Tech about four years ago. 12 00:01:09,610 --> 00:01:15,790 And then last year, when the pandemic hit us, they got together with senior faculty in the university. 13 00:01:15,790 --> 00:01:24,580 In fact, I read Professor John Bell, the vice chancellor Louise Richardson and head of medical sciences division Cabinet agrees. 14 00:01:24,580 --> 00:01:33,160 But they also pulled together colleagues from the UK government and the UK regulators from the funders, but importantly from AstraZeneca, 15 00:01:33,160 --> 00:01:41,020 a large global pharmaceutical company and in particular their CEO, Pascal Soriot and the head of R&D many penguins. 16 00:01:41,020 --> 00:01:46,600 And together they said, How can we generate a vaccine for this pandemic as quickly as possible? 17 00:01:46,600 --> 00:01:52,660 We're not worried about making money. We need to identify a vaccine that's going to get the world out of this mess. 18 00:01:52,660 --> 00:02:00,190 And it is absolutely stunning what my colleagues have done in the space of 10 months, something that would have normally taken them 10 years. 19 00:02:00,190 --> 00:02:06,850 So the big lessons for me from that are that if we get all the stakeholders together and we create one goal, 20 00:02:06,850 --> 00:02:11,320 one vision, one focus, then I think we can do the impossible. 21 00:02:11,320 --> 00:02:20,740 And here, you know, we had colleagues from government and university, from industry funders and then of course, from the regulators as well. 22 00:02:20,740 --> 00:02:25,630 And together they had this one single vision that's generating vaccine as quickly as possible. 23 00:02:25,630 --> 00:02:32,410 So the key thing? Collaborate, collaborate, collaborate. The second thing I would say is that in all of these organisations, 24 00:02:32,410 --> 00:02:38,320 the people who came together are great leaders, the great innovators and their great entrepreneurs. 25 00:02:38,320 --> 00:02:45,970 So inside AstraZeneca, Pascal and many inside the university, inside government, inside the regulators, inside the fund. 26 00:02:45,970 --> 00:02:49,960 So it's about people. People make these big things happen. 27 00:02:49,960 --> 00:02:58,910 The third lesson for me is being that sort of, you know, the reason Oxford was able to do this is that in the previous two decades. 28 00:02:58,910 --> 00:03:04,460 There had been sustained investment in some major infrastructures, so the Jenner Institute, 29 00:03:04,460 --> 00:03:12,320 set up by Adrian Hill, the global health institutes at Oxford, has in Kenya and Thailand and Vietnam. 30 00:03:12,320 --> 00:03:19,880 The clinical by manufacturing facility that we have here in the university. All of these enabled us to pounce on this problem quickly. 31 00:03:19,880 --> 00:03:26,360 I think it's also fair to say that members of the public society they all recognise now, 32 00:03:26,360 --> 00:03:32,030 I believe that science is incredibly important and the universities are incredibly important. 33 00:03:32,030 --> 00:03:40,100 You know, April, May last year, everyone was looking to people like Sarah Gilbert and Adrian Hill to get us out of this mess. 34 00:03:40,100 --> 00:03:45,050 So that was the first and the second story is the recovery trial. 35 00:03:45,050 --> 00:03:51,560 So this was headed up by a couple of my clinical colleagues, Martin Landray and Peter Hornby. 36 00:03:51,560 --> 00:03:57,590 And together, what they've done with lots of clinicians across the NHS, across the UK working in many, 37 00:03:57,590 --> 00:04:04,220 many hospitals, they tested a number of existing drugs to see if they would be effective against. 38 00:04:04,220 --> 00:04:12,890 And they've shown that hydroxychloroquine was ineffective, and they've also shown that lopinavir ritonavir were also ineffective. 39 00:04:12,890 --> 00:04:17,570 But importantly, they showed that three existing drugs are effective. 40 00:04:17,570 --> 00:04:24,320 Dexamethasone, a cheap, generic anti-inflammatory found in all pharmacy stores, was shown to be effective. 41 00:04:24,320 --> 00:04:28,670 More recently, they've shown tocilizumab is effective, and most recently of all, 42 00:04:28,670 --> 00:04:34,820 they've shown that this Regeneron monoclonal antibody combination is also plenty. 43 00:04:34,820 --> 00:04:38,300 So again, the lessons from that are in the UK, 44 00:04:38,300 --> 00:04:48,080 the NHS is a wonderful resource for us to sort of help generate new therapies for patients and improve the lives of patients. 45 00:04:48,080 --> 00:04:52,650 It's a wonderful resource. I think the second lesson for me is that. 46 00:04:52,650 --> 00:05:02,130 The regulators here have been absolutely remarkable. So dexamethasone, you know, in June 16th last year, 47 00:05:02,130 --> 00:05:09,660 the prime minister announced this at one of the lunchtime presentations that he was giving to the nation. 48 00:05:09,660 --> 00:05:13,620 And by that night, it had become policy. 49 00:05:13,620 --> 00:05:22,080 By the weekend, it was already saving lives and that one drug, dexamethasone, has saved more than a million lives in the past year or so. 50 00:05:22,080 --> 00:05:28,230 Remarkable success. The third story is a programme called the Moonshot Programme. 51 00:05:28,230 --> 00:05:33,210 So this was set up by Dave Stewart, Yvonne Jones, Martin Walsh, Frank Blundell. 52 00:05:33,210 --> 00:05:39,360 And what they did was they took the main protease in code, which is a potential drug target. 53 00:05:39,360 --> 00:05:42,060 They screened it against a library of compounds. 54 00:05:42,060 --> 00:05:49,110 They identified a number of chemicals starting points, and then they didn't keep those chemicals starting points for themselves in Oxford. 55 00:05:49,110 --> 00:05:50,940 They shared them with the whole world. 56 00:05:50,940 --> 00:05:57,960 So they had colleagues in all parts of the world, in South Africa, in Australia, in Brazil, working on these chemicals, 57 00:05:57,960 --> 00:06:06,240 starting points, optimising them, making them more potent, trying to convert them into drug molecules that we could give to patients. 58 00:06:06,240 --> 00:06:11,520 And literally, within a few weeks, they identified nanomoles a potent culprit. 59 00:06:11,520 --> 00:06:18,870 So again, the lessons for me from this story are that open science sharing all your data and knowledge accelerates science. 60 00:06:18,870 --> 00:06:27,000 That's been wonderful. I think the other success has been that sort of some of these infrastructures that we've got in the UK, 61 00:06:27,000 --> 00:06:36,540 like the diamond light synchrotron at Harwell or the Rosalind Franklin Institute or others infrastructures like the Crick, 62 00:06:36,540 --> 00:06:44,310 the Sanger, the these are amazing resources that we can use to tackle some of these big global problems. 63 00:06:44,310 --> 00:06:53,730 The fourth story is a project that we started about three years ago focussed on trying to treat multimorbidity associated with ageing. 64 00:06:53,730 --> 00:06:57,840 So we all recognise that we've got ageing societies all over the world. 65 00:06:57,840 --> 00:07:03,180 A lot of these elderly patients, they don't have one disease. They normally have half a dozen diseases. 66 00:07:03,180 --> 00:07:09,900 They're usually taking a drug for each of those diseases, and then they're taking two or three drugs to manage the side effects of those. 67 00:07:09,900 --> 00:07:13,620 So often these individuals are taking maybe eight, nine 10 drugs a day. 68 00:07:13,620 --> 00:07:21,870 So now we now believe it may be possible to treat multimorbidity associated with ageing with single treatments. 69 00:07:21,870 --> 00:07:25,950 And so this is something that's not currently being done in the pharmaceutical industry. 70 00:07:25,950 --> 00:07:27,750 It's a completely new approach. 71 00:07:27,750 --> 00:07:36,990 So what we did was we set up a partnership with Mike Ferguson, University of Dundee with David Adams and Janet Lawd at the University of Birmingham. 72 00:07:36,990 --> 00:07:43,620 Obviously ourselves here in Oxford, but we also partnered with the Medicines Discovery Catapult in Manchester. 73 00:07:43,620 --> 00:07:49,980 So Chris Malloy. And we partnered with colleagues at the Crick through interaction and together what 74 00:07:49,980 --> 00:07:54,570 we've done in the past three years is we've started to build a pipeline of new targets. 75 00:07:54,570 --> 00:07:58,530 We've come up with new biomarkers, new ways of stratifying patients, 76 00:07:58,530 --> 00:08:05,580 and we're now also looking at how we can repurpose existing drugs, but also what we've done in the past three years. 77 00:08:05,580 --> 00:08:09,390 We've pulled in other university, we've pulled in some biotechs. 78 00:08:09,390 --> 00:08:16,710 We've had conversations with a lot of venture capitalists and patient groups, and we're in discussions with a number of pharma companies. 79 00:08:16,710 --> 00:08:24,900 So we've created this national network to focus on how we can treat multimorbidity associated with ageing. 80 00:08:24,900 --> 00:08:29,400 So the lesson to me from this are that even in this wonderful place in Oxford, 81 00:08:29,400 --> 00:08:36,180 we don't have all the resources and the expertise and the infrastructure. We need to tackle problems like multimorbidity. 82 00:08:36,180 --> 00:08:42,420 We have to partner with other universities with big infrastructures like the catapult in the crick. 83 00:08:42,420 --> 00:08:48,090 We have to bring in industry, we have to bring in biotech, we have to bring in patient groups, et cetera. 84 00:08:48,090 --> 00:08:53,370 And now we're also working with universities in Israel as part of this project. 85 00:08:53,370 --> 00:09:01,380 So the lessons that universities are undoubtedly in my mind, the engines of innovation, 86 00:09:01,380 --> 00:09:09,310 what we have to work together and not just work together in the UK, but work together with universities all over the world. 87 00:09:09,310 --> 00:09:13,560 The final story is a story around rare diseases. 88 00:09:13,560 --> 00:09:18,330 So many of you are aware there are 7000 rare diseases across the world. 89 00:09:18,330 --> 00:09:22,830 If you add up all the patients, it's more than 350 million patients. 90 00:09:22,830 --> 00:09:28,830 30 percent of these kids do not reach the age of five. It can take between six to eight years to get a diagnosis. 91 00:09:28,830 --> 00:09:35,430 For some of these individuals and 95 percent of these patients, ninety five percent have no drug treatment. 92 00:09:35,430 --> 00:09:39,660 So we set up a project with a colleague named Hani Chowdhury, 93 00:09:39,660 --> 00:09:45,420 who did his DPhil here in Oslo that supervised by Peter Ratcliffe, our recent Nobel prise winner. 94 00:09:45,420 --> 00:09:52,110 So Hani is now moved back to the King Abdullah Aziz University in Saudi Arabia, and we're working together to see. 95 00:09:52,110 --> 00:09:57,450 How we can use A.I. to accelerate new therapeutics for rare diseases. 96 00:09:57,450 --> 00:10:02,160 So the big lesson for me from this is that sort of great mentors like Peter 97 00:10:02,160 --> 00:10:08,100 actually helped produce great leaders and visionaries who go all over the world. 98 00:10:08,100 --> 00:10:14,040 And I think together we can continue to work together to solve some of these big global problems. 99 00:10:14,040 --> 00:10:20,430 So five stories, I hope some lessons that you may consider debating over the next three days. 100 00:10:20,430 --> 00:10:26,780 But I think it's fair to say we all recognise this over the past 12 months, 15 months, 18 months. 101 00:10:26,780 --> 00:10:35,510 As a consequence of this pandemic, close to three million people have died, tens of millions of families, their lives have been destroyed. 102 00:10:35,510 --> 00:10:40,220 Tens of millions of people are going to be living with the consequences of long COVID. 103 00:10:40,220 --> 00:10:47,750 They're going to have to deal with the challenges of mental health. A whole generation of school kids have missed a whole year of schooling. 104 00:10:47,750 --> 00:10:58,520 The impact of that, we've yet to feel the governments all over the world have had to spend trillions of dollars literally protecting the vulnerable, 105 00:10:58,520 --> 00:11:03,140 trying to sort of safeguard jobs, trying to protect businesses. 106 00:11:03,140 --> 00:11:12,050 And we're still not yet out of this pandemic. So. It's been a horrendous year, but I hope will a year of many lessons. 107 00:11:12,050 --> 00:11:18,230 I hope we can take all of those lessons and apply them to some of the challenges that we're facing in the future. 108 00:11:18,230 --> 00:11:20,960 Now, in my own space, I care about health care, 109 00:11:20,960 --> 00:11:28,340 so I worry about things like dementia and mental health and antimicrobial resistance and how we can cure cancer, 110 00:11:28,340 --> 00:11:32,690 etc., etc. But across the world, we've got other bigger challenges. 111 00:11:32,690 --> 00:11:40,640 You could argue climate change, pollution, clean water, more energy, food for the population ET. 112 00:11:40,640 --> 00:11:47,300 And the only way we're going to tackle these is by coming together. So I think I'd leave you with the following messages. 113 00:11:47,300 --> 00:11:52,940 Let's come together. Let's be more ambitious. Let's be willing to take risks. 114 00:11:52,940 --> 00:12:00,500 Let's pool our infrastructures and resources and expertise. And I do believe that together we can do the impossible. 115 00:12:00,500 --> 00:12:03,770 So thank you very much. I hope you enjoy the next three days. 116 00:12:03,770 --> 00:12:08,330 I'm sure you will enjoy the next three days, and I'm sure I will learn a lot from all of you. 117 00:12:08,330 --> 00:12:14,378 So thank you.