[Script Info]
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[Events]
Format: Layer, Start, End, Style, Name, MarginL, MarginR, MarginV, Effect, Text
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,So how are we going to beat\Nthis novel coronavirus?
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,By using our best tools:
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,our science and our technology.
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,In my lab, we're using\Nthe tools of artificial intelligence
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,and synthetic biology
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,to speed up the fight\Nagainst this pandemic.
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,Our work was originally designed
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,to tackle the antibiotic\Nresistance crisis.
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,Our project seeks to harness\Nthe power of machine learning
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,to replenish our antibiotic arsenal
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,and avoid a globally devastating\Npost-antibiotic era.
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,Importantly, the same technology\Ncan be used to search
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,for antiviral compounds
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,that could help us fight\Nthe current pandemic.
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,Machine learning is turning\Nthe traditional model of drug discovery
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,on its head.
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,With this approach,
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,instead of painstakingly testing\Nthousands of existing molecules
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,one by one in a lab\Nfor their effectiveness,
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,we can train a computer
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,to explore the exponentially larger space
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,of essentially all possible molecules\Nthat could be synthesized,
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,and thus instead of looking\Nfor a needle in a haystack,
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,we can use the giant magnet\Nof computing power
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,to find many needles\Nin multiple haystacks simultaneously.
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,We've already had some early success.
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,Recently, we used machine learning
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,to discover new antibiotics\Nthat can help us fight off
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,the bacterial infections that can occur\Nalongside SARS-CoV-2 infections.
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,Two months ago, TED's Audacious Project
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,approved funding for us\Nto massively scale up our work
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,with the goal of discovering\Nseven new classes of antibiotics
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,against seven of the world's\Ndeadly bacterial pathogens
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,over the next seven years.
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,For context,
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,the number of new class of antibiotics
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,that have been discovered\Nover the last three decades is zero.
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,While the quest for new antibiotics\Nis for our medium-term future,
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,the novel coronavirus\Nposes an immediate deadly threat,
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,and I'm excited to share that we think\Nwe can use the same technology
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,to search for therapeutics\Nto fight this virus.
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,So how are we going to do it?
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,Well, we're creating\Na compound training library,
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,and with collaborators\Napplying these molecules
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,to SARS-CoV-2-infected cells
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,to see which of them exhibit\Neffective activity.
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,These data will be use to train\Na machine learning model
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,that will be applied to a [?]\Nlibrary of over a billion molecules
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,to search for potential\Nnovel antiviral compounds.
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,We will synthesize and test\Nthe top predictions
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,and advance the most promising\Ncandidates into the clinic.
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,Sound too good to be true?
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,Well, it shouldn't.
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,The Antibiotics AI Project is founded\Non our proof of concept research
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,that led to the discovery\Nof a novel broad spectrum antibiotic
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,called Halocin.
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,Halocin has potent antibacterial activity
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,against almost all antibiotic-resistant\Nbacterial pathogens,
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,including untreatable\Npan-resistant infections.
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,Importantly, in contrast\Nto current antibiotics,
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,the frequency at which bacteria\Ndevelop resistance against Halocin
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,is remarkably low.
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,We tested the ability of bacteria\Nto evolve resistance against Halocin
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,as well as Cipro in the lab.
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,In the case of Cipro,
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,after just one day, we saw resistance.
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,In the case of Halocin,
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,after one day we didn't\Nsee any resistance.
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,Amazingly, after even 30 days,
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,we didn't see any\Nresistance against Halocin.
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,In this pilot project, we first tested\Nroughly 2,500 compounds against E. coli.
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,This training set included\Nknown antibiotics,
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,such as Cipro and penicillin,
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,as well as many drugs\Nthat are not antibiotics.
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,These data we used to train a model
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,to learn molecular features\Nassociated with antibacterial activity.
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,We then applied this model\Nto a drug repurposing library
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,consisting of several thousand molecules,
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,and asked the model to identify molecules
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,that are predicted\Nto have antibacterial properties
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,but don't look like existing antibiotics.
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,Interestingly, only one molecule\Nin that library fit these criteria,
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,and that molecule\Nturned out to be Halocin.
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,Given that Halocin does not look\Nlike any existing antibiotic,
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,it would have been impossible for a human,\Nincluding an antibiotic expert,
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,to identify Halocin in this manner.
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,Imagine now what we could do\Nwith this technology
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,against SARS-CoV-2.
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,And that's not all.
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,We're also using the tools\Nof synthetic biology,
Dialogue: 0,9:59:59.99,9:59:59.99,Default,,0000,0000,0000,,tinkering with DNA and other cellular machinery, to serve human purposes like combating COVID-19 [??] we are working to develop a protective mask that can also serve as a rapid diagnostic test. How does that work? Well, we recently showed that you can take the cellular machinery out of a living cell and freeze-dry it along with RNA sensors onto paper in order to create low-cost diagnostics for Ebola and Zika. The sensors are activated when they're rehydrated by a patient sample that could consist of blood or saliva, for example. It turns out this technology is not limited to paper and can be applied to other materials, including cloth. For the COVID-19 pandemic, we're designing RNA sensors to detect the virus and freeze-drying these along with the needed cellular machinery into the fabric of a face mask, where the simple act of breathing, along with the water vapor that comes with it, can activate the test. Now, if the patient is infected with SARS-CoV-2, the mask will produce a fluorescent signal that can be detected by a simple, inexpensive handheld device. In one or two hours, a patient could those be diagnosed safely, remotely and accurately. We're also using synthetic biology to design a candidate vaccine for COVID-19. We are repurposing the BCG vaccine, which has been used against TB for almost a century. It's a live attenuated vaccine, and we're engineering it to express SARS-CoV-2 antigens, which should trigger the production of protective antibodies by the immune system. Importantly, BCG is massively scalable and has a safety profile that's among the best of any reported vaccine. With the tools of synthetic biology and artificial intelligence, we can win the fight against this novel coronavirus. This work is in its very early stages, but the promise is real. Science and technology can give us an important advantage in the battle of human wits versus the genes of superbugs, a battle we can win. Thank you.