[Script Info]
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[Events]
Format: Layer, Start, End, Style, Name, MarginL, MarginR, MarginV, Effect, Text
Dialogue: 0,0:00:01.00,0:00:03.86,Default,,0000,0000,0000,,So how are we going to beat\Nthis novel coronavirus?
Dialogue: 0,0:00:04.09,0:00:06.95,Default,,0000,0000,0000,,By using our best tools:
Dialogue: 0,0:00:07.22,0:00:09.58,Default,,0000,0000,0000,,our science and our technology.
Dialogue: 0,0:00:09.80,0:00:12.99,Default,,0000,0000,0000,,In my lab, we're using\Nthe tools of artificial intelligence
Dialogue: 0,0:00:12.99,0:00:14.66,Default,,0000,0000,0000,,and synthetic biology
Dialogue: 0,0:00:14.66,0:00:18.28,Default,,0000,0000,0000,,to speed up the fight\Nagainst this pandemic.
Dialogue: 0,0:00:18.28,0:00:20.52,Default,,0000,0000,0000,,Our work was originally designed
Dialogue: 0,0:00:20.52,0:00:23.09,Default,,0000,0000,0000,,to tackle the antibiotic\Nresistance crisis.
Dialogue: 0,0:00:23.09,0:00:26.05,Default,,0000,0000,0000,,Our project seeks to harness\Nthe power of machine learning
Dialogue: 0,0:00:26.05,0:00:29.52,Default,,0000,0000,0000,,to replenish our antibiotic arsenal
Dialogue: 0,0:00:29.52,0:00:33.12,Default,,0000,0000,0000,,and avoid a globally devastating\Npost-antibiotic era.
Dialogue: 0,0:00:33.75,0:00:37.08,Default,,0000,0000,0000,,Importantly, the same technology\Ncan be used to search
Dialogue: 0,0:00:37.08,0:00:38.78,Default,,0000,0000,0000,,for antiviral compounds
Dialogue: 0,0:00:38.78,0:00:41.51,Default,,0000,0000,0000,,that could help us fight\Nthe current pandemic.
Dialogue: 0,0:00:42.31,0:00:46.48,Default,,0000,0000,0000,,Machine learning is turning\Nthe traditional model of drug discovery
Dialogue: 0,0:00:46.48,0:00:47.53,Default,,0000,0000,0000,,on its head.
Dialogue: 0,0:00:47.53,0:00:49.21,Default,,0000,0000,0000,,With this approach,
Dialogue: 0,0:00:49.21,0:00:51.46,Default,,0000,0000,0000,,instead of painstakingly testing\Nthousands of existing molecules
Dialogue: 0,0:00:51.46,0:00:53.22,Default,,0000,0000,0000,,one by one in a lab\Nfor their effectiveness,
Dialogue: 0,0:00:53.22,0:00:56.20,Default,,0000,0000,0000,,we can train a computer
Dialogue: 0,0:00:56.20,0:01:00.43,Default,,0000,0000,0000,,to explore the exponentially larger space
Dialogue: 0,0:01:00.43,0:01:04.44,Default,,0000,0000,0000,,of essentially all possible molecules\Nthat could be synthesized,
Dialogue: 0,0:01:04.44,0:01:10.01,Default,,0000,0000,0000,,and thus instead of looking\Nfor a needle in a haystack,
Dialogue: 0,0:01:10.01,0:01:13.78,Default,,0000,0000,0000,,we can use the giant magnet\Nof computing power
Dialogue: 0,0:01:13.78,0:01:18.68,Default,,0000,0000,0000,,to find many needles\Nin multiple haystacks simultaneously.
Dialogue: 0,0:01:18.68,0:01:20.46,Default,,0000,0000,0000,,We've already had some early success.
Dialogue: 0,0:01:20.46,0:01:24.78,Default,,0000,0000,0000,,Recently, we used machine learning
Dialogue: 0,0:01:24.78,0:01:28.08,Default,,0000,0000,0000,,to discover new antibiotics\Nthat can help us fight off
Dialogue: 0,0:01:28.08,0:01:32.55,Default,,0000,0000,0000,,the bacterial infections that can occur\Nalongside SARS-CoV-2 infections.
Dialogue: 0,0:01:33.35,0:01:35.78,Default,,0000,0000,0000,,Two months ago, TED's Audacious Project
Dialogue: 0,0:01:35.78,0:01:39.38,Default,,0000,0000,0000,,approved funding for us\Nto massively scale up our work
Dialogue: 0,0:01:39.38,0:01:44.42,Default,,0000,0000,0000,,with the goal of discovering\Nseven new classes of antibiotics
Dialogue: 0,0:01:44.42,0:01:47.38,Default,,0000,0000,0000,,against seven of the world's\Ndeadly bacterial pathogens
Dialogue: 0,0:01:47.99,0:01:50.53,Default,,0000,0000,0000,,over the next seven years.
Dialogue: 0,0:01:50.73,0:01:52.43,Default,,0000,0000,0000,,For context,
Dialogue: 0,0:01:52.43,0:01:55.07,Default,,0000,0000,0000,,the number of new class of antibiotics
Dialogue: 0,0:01:55.07,0:01:58.29,Default,,0000,0000,0000,,that have been discovered\Nover the last three decades is zero.
Dialogue: 0,0:01:58.40,0:02:01.93,Default,,0000,0000,0000,,While the quest for new antibiotics\Nis for our medium-term future,
Dialogue: 0,0:02:01.93,0:02:06.44,Default,,0000,0000,0000,,the novel coronavirus\Nposes an immediate deadly threat,
Dialogue: 0,0:02:06.60,0:02:10.39,Default,,0000,0000,0000,,and I'm excited to share that we think\Nwe can use the same technology
Dialogue: 0,0:02:10.39,0:02:13.55,Default,,0000,0000,0000,,to search for therapeutics\Nto fight this virus.
Dialogue: 0,0:02:13.75,0:02:15.55,Default,,0000,0000,0000,,So how are we going to do it?
Dialogue: 0,0:02:15.55,0:02:18.40,Default,,0000,0000,0000,,Well, we're creating\Na compound training library,
Dialogue: 0,0:02:18.40,0:02:21.64,Default,,0000,0000,0000,,and with collaborators\Napplying these molecules
Dialogue: 0,0:02:21.64,0:02:23.96,Default,,0000,0000,0000,,to SARS-CoV-2-infected cells
Dialogue: 0,0:02:23.96,0:02:28.40,Default,,0000,0000,0000,,to see which of them exhibit\Neffective activity.
Dialogue: 0,0:02:28.40,0:02:31.54,Default,,0000,0000,0000,,These data will be use to train\Na machine learning model
Dialogue: 0,0:02:31.54,0:02:35.71,Default,,0000,0000,0000,,that will be applied to a [?]\Nlibrary of over a billion molecules
Dialogue: 0,0:02:35.71,0:02:40.57,Default,,0000,0000,0000,,to search for potential\Nnovel antiviral compounds.
Dialogue: 0,0:02:40.57,0:02:43.29,Default,,0000,0000,0000,,We will synthesize and test\Nthe top predictions
Dialogue: 0,0:02:43.29,0:02:46.28,Default,,0000,0000,0000,,and advance the most promising\Ncandidates into the clinic.
Dialogue: 0,0:02:46.51,0:02:48.70,Default,,0000,0000,0000,,Sound too good to be true?
Dialogue: 0,0:02:48.70,0:02:49.87,Default,,0000,0000,0000,,Well, it shouldn't.
Dialogue: 0,0:02:49.87,0:02:53.28,Default,,0000,0000,0000,,The Antibiotics AI Project is founded\Non our proof of concept research
Dialogue: 0,0:02:53.28,0:02:56.67,Default,,0000,0000,0000,,that led to the discovery\Nof a novel broad spectrum antibiotic
Dialogue: 0,0:02:56.67,0:02:57.86,Default,,0000,0000,0000,,called Halocin.
Dialogue: 0,0:02:58.64,0:03:01.48,Default,,0000,0000,0000,,Halocin has potent antibacterial activity
Dialogue: 0,0:03:01.48,0:03:05.62,Default,,0000,0000,0000,,against almost all antibiotic-resistant\Nbacterial pathogens,
Dialogue: 0,0:03:05.80,0:03:09.44,Default,,0000,0000,0000,,including untreatable\Npan-resistant infections.
Dialogue: 0,0:03:09.94,0:03:12.21,Default,,0000,0000,0000,,Importantly, in contrast\Nto current antibiotics,
Dialogue: 0,0:03:12.21,0:03:16.22,Default,,0000,0000,0000,,the frequency at which bacteria\Ndevelop resistance against Halocin
Dialogue: 0,0:03:16.22,0:03:17.67,Default,,0000,0000,0000,,is remarkably low.
Dialogue: 0,0:03:18.22,0:03:23.18,Default,,0000,0000,0000,,We tested the ability of bacteria\Nto evolve resistance against Halocin
Dialogue: 0,0:03:23.18,0:03:25.30,Default,,0000,0000,0000,,as well as Cipro in the lab.
Dialogue: 0,0:03:25.30,0:03:27.13,Default,,0000,0000,0000,,In the case of Cipro,
Dialogue: 0,0:03:27.13,0:03:30.18,Default,,0000,0000,0000,,after just one day, we saw resistance.
Dialogue: 0,0:03:30.39,0:03:31.96,Default,,0000,0000,0000,,In the case of Halocin,
Dialogue: 0,0:03:31.96,0:03:34.65,Default,,0000,0000,0000,,after one day we didn't\Nsee any resistance.
Dialogue: 0,0:03:34.65,0:03:38.04,Default,,0000,0000,0000,,Amazingly, after even 30 days,
Dialogue: 0,0:03:38.04,0:03:40.99,Default,,0000,0000,0000,,we didn't see any\Nresistance against Halocin.
Dialogue: 0,0:03:41.24,0:03:46.98,Default,,0000,0000,0000,,In this pilot project, we first tested\Nroughly 2,500 compounds against E. coli.
Dialogue: 0,0:03:47.21,0:03:50.27,Default,,0000,0000,0000,,This training set included\Nknown antibiotics,
Dialogue: 0,0:03:50.27,0:03:52.18,Default,,0000,0000,0000,,such as Cipro and penicillin,
Dialogue: 0,0:03:52.18,0:03:55.13,Default,,0000,0000,0000,,as well as many drugs\Nthat are not antibiotics.
Dialogue: 0,0:03:55.29,0:03:57.90,Default,,0000,0000,0000,,These data we used to train a model
Dialogue: 0,0:03:57.90,0:04:02.49,Default,,0000,0000,0000,,to learn molecular features\Nassociated with antibacterial activity.
Dialogue: 0,0:04:02.49,0:04:05.54,Default,,0000,0000,0000,,We then applied this model\Nto a drug repurposing library
Dialogue: 0,0:04:05.100,0:04:08.19,Default,,0000,0000,0000,,consisting of several thousand molecules,
Dialogue: 0,0:04:08.19,0:04:10.46,Default,,0000,0000,0000,,and asked the model to identify molecules
Dialogue: 0,0:04:10.46,0:04:13.22,Default,,0000,0000,0000,,that are predicted\Nto have antibacterial properties
Dialogue: 0,0:04:13.22,0:04:15.91,Default,,0000,0000,0000,,but don't look like existing antibiotics.
Dialogue: 0,0:04:16.19,0:04:21.30,Default,,0000,0000,0000,,Interestingly, only one molecule\Nin that library fit these criteria,
Dialogue: 0,0:04:21.51,0:04:24.34,Default,,0000,0000,0000,,and that molecule\Nturned out to be Halocin.
Dialogue: 0,0:04:24.69,0:04:27.77,Default,,0000,0000,0000,,Given that Halocin does not look\Nlike any existing antibiotic,
Dialogue: 0,0:04:27.77,0:04:31.82,Default,,0000,0000,0000,,it would have been impossible for a human,\Nincluding an antibiotic expert,
Dialogue: 0,0:04:31.82,0:04:34.72,Default,,0000,0000,0000,,to identify Halocin in this manner.
Dialogue: 0,0:04:34.89,0:04:37.54,Default,,0000,0000,0000,,Imagine now what we could do\Nwith this technology
Dialogue: 0,0:04:37.54,0:04:40.05,Default,,0000,0000,0000,,against SARS-CoV-2.
Dialogue: 0,0:04:40.05,0:04:43.11,Default,,0000,0000,0000,,And that's not all.
Dialogue: 0,0:04:43.11,0:04:44.42,Default,,0000,0000,0000,,We're also using the tools\Nof synthetic biology,
Dialogue: 0,0:04:44.42,0:04:46.89,Default,,0000,0000,0000,,tinkering with DNA\Nand other cellular machinery,
Dialogue: 0,0:04:46.89,0:04:50.05,Default,,0000,0000,0000,,to serve human purposes\Nlike combating COVID-19,
Dialogue: 0,0:04:50.40,0:04:54.31,Default,,0000,0000,0000,,and at [??] we are working\Nto develop a protective mask
Dialogue: 0,0:04:54.41,0:04:58.19,Default,,0000,0000,0000,,that can also serve\Nas a rapid diagnostic test.
Dialogue: 0,0:04:58.41,0:04:59.94,Default,,0000,0000,0000,,So how does that work?
Dialogue: 0,0:04:59.94,0:05:02.62,Default,,0000,0000,0000,,Well, we recently showed that you can take
Dialogue: 0,0:05:02.62,0:05:04.36,Default,,0000,0000,0000,,the cellular machinery\Nout of a living cell
Dialogue: 0,0:05:04.36,0:05:07.91,Default,,0000,0000,0000,,and freeze-dry it along with\NRNA sensors onto paper
Dialogue: 0,0:05:08.26,0:05:12.92,Default,,0000,0000,0000,,in order to create low-cost\Ndiagnostics for Ebola and Zika.
Dialogue: 0,0:05:13.75,0:05:18.43,Default,,0000,0000,0000,,The sensors are activated when\Nthey're rehydrated by a patient sample
Dialogue: 0,0:05:18.43,0:05:21.56,Default,,0000,0000,0000,,that could consist of blood\Nor saliva, for example.
Dialogue: 0,0:05:21.78,0:05:25.04,Default,,0000,0000,0000,,It turns out this technology\Nis not limited to paper
Dialogue: 0,0:05:25.04,0:05:28.89,Default,,0000,0000,0000,,and can be applied\Nto other materials, including cloth.
Dialogue: 0,0:05:28.89,0:05:31.16,Default,,0000,0000,0000,,For the COVID-19 pandemic,\Nwe're designing RNA sensors
Dialogue: 0,0:05:31.16,0:05:33.01,Default,,0000,0000,0000,,to detect the virus
Dialogue: 0,0:05:33.01,0:05:38.41,Default,,0000,0000,0000,,and freeze-drying these\Nalong with the needed cellular machinery
Dialogue: 0,0:05:38.41,0:05:40.56,Default,,0000,0000,0000,,into the fabric of a face mask,
Dialogue: 0,0:05:40.56,0:05:42.85,Default,,0000,0000,0000,,where the simple act of breathing,
Dialogue: 0,0:05:43.41,0:05:47.72,Default,,0000,0000,0000,,along with the water vapor\Nthat comes with it, can activate the test.
Dialogue: 0,0:05:48.04,0:05:51.50,Default,,0000,0000,0000,,Now, if the patient\Nis infected with SARS-CoV-2,
Dialogue: 0,0:05:52.26,0:05:56.35,Default,,0000,0000,0000,,the mask will produce a fluorescent signal\Nthat can be detected by a simple,
Dialogue: 0,0:05:56.35,0:05:58.86,Default,,0000,0000,0000,,inexpensive handheld device.
Dialogue: 0,0:05:58.86,0:06:01.11,Default,,0000,0000,0000,,In one or two hours, a patient\Ncould those be diagnosed
Dialogue: 0,0:06:01.11,0:06:06.34,Default,,0000,0000,0000,,safely, remotely and accurately.
Dialogue: 0,0:06:07.01,0:06:10.35,Default,,0000,0000,0000,,We're also using synthetic biology
Dialogue: 0,0:06:10.35,0:06:12.68,Default,,0000,0000,0000,,to design a candidate\Nvaccine for COVID-19.
Dialogue: 0,0:06:12.91,0:06:15.83,Default,,0000,0000,0000,,We are repurposing the BCG vaccine,
Dialogue: 0,0:06:15.83,0:06:18.98,Default,,0000,0000,0000,,which has been used against TB\Nfor almost a century.
Dialogue: 0,0:06:18.98,0:06:20.46,Default,,0000,0000,0000,,It's a live attenuated vaccine,
Dialogue: 0,0:06:20.46,0:06:24.23,Default,,0000,0000,0000,,and we're engineering it\Nto express SARS-CoV-2 antigens,
Dialogue: 0,0:06:24.78,0:06:27.83,Default,,0000,0000,0000,,which should trigger the production\Nof protective antibodies
Dialogue: 0,0:06:27.83,0:06:29.65,Default,,0000,0000,0000,,by the immune system.
Dialogue: 0,0:06:29.65,0:06:33.54,Default,,0000,0000,0000,,Importantly, BCG is massively scalable\Nand has a safety profile
Dialogue: 0,0:06:33.54,0:06:37.01,Default,,0000,0000,0000,,that's among the best\Nof any reported vaccine.
Dialogue: 0,0:06:38.10,0:06:43.22,Default,,0000,0000,0000,,With the tools of synthetic biology\Nand artificial intelligence,
Dialogue: 0,0:06:43.22,0:06:46.61,Default,,0000,0000,0000,,we can win the fight\Nagainst this novel coronavirus.
Dialogue: 0,0:06:46.84,0:06:50.35,Default,,0000,0000,0000,,This work is in its very early stages,\Nbut the promise is real.
Dialogue: 0,0:06:50.35,0:06:54.59,Default,,0000,0000,0000,,Science and technology\Ncan give us an important advantage
Dialogue: 0,0:06:54.59,0:06:57.70,Default,,0000,0000,0000,,in the battle of human wits\Nversus the genes of superbugs,
Dialogue: 0,0:06:57.70,0:06:59.87,Default,,0000,0000,0000,,a battle we can win.
Dialogue: 0,0:06:59.87,0:07:01.66,Default,,0000,0000,0000,,Thank you.